Beyond the Water's Edge: Charting the Course of Managed Care for People with Disabilities--Conference Resource Book (continued)

TAB 6: Track I: Managed Care for Children and Adults with Disabilities

PDF Version


OVERVIEW
Moderator Biographics
Managed Care for Children and Adults with Disabilities (Burwell and Tanenbaum)
SESSION 1: IMPACT OF MANAGED CARE ON CHILDREN WITH DISABILITIES
Reactor Biographies
Evaluation of the District of Columbia's Demonstration Program: Managed Care System for Disabled and Special Needs Children (Irvin)
Families' Out-of-Pocket Expenses When Caring for Children With Special Needs: A Preliminary Report Comparing Children in Medicaid and a Commercial Product Line-- Presentation Summary (Shenkman)
The Managed Care Enhancement Project for Children with Special Health Care Needs (Allen)
Planning Grant: Services for Children with Chronic Illness and Disease in an HMO (Staub)
State Medicaid Managed Care Policies Affecting Children with Chronic or Disabling Conditions (Fox, McManus)
Families' Out-of-Pocket Expenses When Caring for Children With Special Needs: A Preliminary Report Comparing Children in Medicaid and a Commercial Product Line (Shenkman)
Managed Care Enhancement Project for Children with Special Health Care Needs: Family and Primary Care Clinician Needs Assessment Methods and Description of Survey Respondents
Managed Care Enhancement Project for Children with Special Health Care Needs: Primary Care Clinician Survey--Mail Survey
Managed Care for Children with Special Health Needs: Parent Survey
Overall Findings of Needs Assessment
SESSION 2: IMPACT OF MANAGED CARE ON ADULTS WITH MENTAL ILLNESS
Reactor Biographies
Severely Mentally Ill HMO Members (McFarland)
Colorado's Early and Preliminary Experience with Capitation for the Severely and Persistently Mentally Ill Adults (Bloom)
The Effects of Private Sector Mental Health Carve-Outs (McGuire)
The Massachusetts Mental Health System Change (Dickey)
Costs and Incentives in a Mental Health and Substance Abuse Carve Out (Ma, McGuire
Enrollment Duration, Service Use, and Costs of Care for Severely Mentally Ill Members of a Health Maintenance Organization (McFarland, Johnson, Hornbrook)
Managing the Care of Schizophrenia: Lessons From a 4-Year Massachusetts Medicaid Study (Dickey, Normand, Norton, Azeni, Fisher, Altaffer)
SESSION 3: IMPACT OF MANAGED CARE ON ADULTS WITH AIDS OR PHYSICAL DISABILITIES
Reactor Biographies
Access, Use, and Satisfaction of the Under 65 Medicare-Disabled in HMOs and Fee-for-Service (Gruenberg)
How the Oregon Health Plan Serves People With Disabilities: System Design Issues and First-Year Impacts (Rosenbach)
Comparison of Physician and Hospital Use Among People with Chronic Illness in HMO and FFS Plans (Fama)
A Managed Care Program for Working-Age Persons with Physical Disabilities (Batavia, DeJong, Burns, Smith, Melus, Butler)
A Vision for the Future: Interview with Gerben DeJong, Ph.D. (Prince, Haas)
Perspective and Analysis--Market Forces: Medical Rehabilitation Undergoing Major Shakeup in Advanced Managed Care Markets (DeJong, Wheatley, Sutton)
Surviving Managed Care and Preparing for the Next Revolution in American Health Care (DeJong)


OVERVIEW

Moderator Biographies

Brian O. Burwell
Brian Burwell is the Director of Healthcare Organization and Economics within the Research and Policy Division of The MEDSTAT Group. The MEDSTAT Group is a healthcare information company which provides databases, analytical software and consulting services to employers, managed care companies, insurers, providers, and government, with headquarters in Ann Arbor, MI. Mr. Burwell has been conducting healthcare services research for 17 years, with a career focus on Medicaid, disability and long-term care policy. He has published extensively on Medicaid eligibility policies for long-term care, home and community-based care waiver programs, Medicaid spend-down, asset transfers, community-based approaches to supporting persons with developmental disabilities, and managed care models for persons with disabilities. He is currently working with the Department of Health and Human Services in Delaware on a project to develop managed long-term care policy options for all the Department's long-term care populations.

Sandra J. Tanenbaum, Ph.D.
Sandra Tanenbaum is Associate Professor of Health Services Management and Policy at the Ohio State University College of Medicine. A political scientist by training, Dr. Tanenbaum's research focuses on the Medicaid program, disability policy, and clinical decision-making. She is the author of Engineering Disability: Public Policy and Compensatory Technology (Temple, 1986) and serves as Book Review Editor of the Journal of Health Politics, Policy and Law.

Managed Care for Children and Adults with Disabilities: A Step in Which Direction?

Brian Burwell and Sandra Tanenbaum

INTRODUCTION

Managed care financing and delivery models have considerable potential for improving the value and quality of health care and supportive services provided to children and adults with disabilities. Managed care models that encourage flexibility in benefit coverage and which coordinate care across the full spectrum of the insurance benefit package are features that are particularly attractive to persons with disabilities. At the same time, however, managed care incentives to eliminate "inappropriate care" or care that is not "medically necessary" are of great concern to people with disabilities whose experience in obtaining access to needed health care services in the fee-for-service system is already problematic.

Both positive and negative effects of managed care for persons with disabilities are similarly reflected in the limited empirical research that has been conducted to date on the impacts of managed care on disabled populations. Some studies point to improvements in outcomes, while others have found significant reductions in service levels under managed care incentives. In brief, the jury is still out on how managed care models effect the health care status of persons with disabilities, and the challenge to the health care services research community is to monitor the enrollment of persons with disabilities into managed care systems closely, and to identify those factors which contribute to improved and worsened outcomes for these vulnerable populations.


CHILDREN AND ADULTS WITH DISABILITIES: WHO ARE THEY?

Part of the challenge in assessing the impact of managed care on persons with disabilities is that the population of children and adults with disabling conditions is extremely diverse, with broad-ranging differences in both types and levels of impairment. At the same time, managed care models are evolving into a variety of permutations that make the generalizability of managed care impact studies increasingly hazardous. In conceptualizing a research agenda for examining managed care impacts, it is critical that we begin with a fundamental understanding of the defined populations, and how the structure and incentives of managed care models may impact access, cost and quality outcomes for persons with severe and chronic disabling conditions.

Children with Disabilities

National survey data indicate that approximately one in ten children have a "severe chronic illness" (Neff and Anderson, 1995). This estimate obscures dramatic diversity in the characteristics of children with disabling conditions--many children with disabilities have conditions which do not result in health care use or costs significantly higher than the population of children without disabilities, while a significant minority of children with disabilities have severe and multiple conditions that require continuous and expert medical attention. Health care and supportive services for the population of children with special health care needs are also fragmented across a variety of financing and service settings that renders the transition from a fee-for-service framework to a managed care framework operationally cumbersome.

Importantly, within the population of children with high health care needs, there is a subset of children with extremely severe medical conditions that require continuous and highly specialized care. For example, within the target population of SSI children receiving services under the District of Columbia's Managed Care System for Disabled and Special Needs Children Demonstration, a Medicaid Section 1115 waiver program, children with Medicaid expenditures of over $50,000 per year constituted less than three percent of all SSI children in the District in the year prior to implementation of the demonstration program, yet they accounted for about 54 percent of all Medicaid spending for SSI children (Blanchon, 1996).

Childhood disability differs from disability in adulthood in that the nature and extent of the disability frequently changes during the developmental process. Many children experience improvements in functioning as they develop, and the disability may become less limiting with time. Other children with extremely severe medical conditions do not survive childhood at all. Moreover, the health care needs of children with disabilities is confounded over time by the interaction of the disability with the child's normal development, such as the onset of puberty. Consequently, access to appropriate pediatric and adolescent specialists may change frequently during the developmental process.

In regard to accessing health care, parents obviously take an active role in negotiating the health care system for their children. In brief, many parents take on the "coordination of care" role that is generally lacking in the fee-for-service system. Consequently, their interactions with the care coordination function of a managed care system may require a new accommodation of respective roles in managing the care of the disabled child. Managed care organizations are generally not used to the level of advocacy and health care system knowledge exhibited by parents of children with disabilities, and may not know how to positively incorporate that energy and knowledge into their internal care coordination systems.

A common concern of parents is the ability to maintain relationships with pediatric specialists, many of which have developed over the lifetime of the child, once the child is enrolled into a managed care plan. Consequently, in some Medicaid managed care initiatives, states require participating plans to continue to pay for ongoing physician-patient relationships, even if the specialty physician is not otherwise enrolled in the plan. This issue is of obvious concern to plans who feel that they are being paid to manage the care of the enrollee, but may not be given all the requisite tools to do so.

Children with disabilities differ from adults with disabilities in one other important respect--children are more likely to receive their health care through a fragmented financing system. Expansions in SSI and Medicaid eligibility for children with disabilities in recent years has meant that there are a growing number of children who have both private health care insurance and Medicaid coverage. Since the Medicaid benefit package is more comprehensive than private health insurance coverage, children and families often use their Medicaid coverage to finance services that are supplemental to their private insurance benefits, particularly home and community-based services and extended therapies. In addition, under the Individuals with Disabilities Education Act, local school systems are required to provide children with disabilities with educationally related services that often extend into the health care arena, particularly in the case of children with severe medical conditions. Lastly, under the Title V Program for Children with Special Health Care Needs, many states provide direct care services to children with disabilities on a categorical basis, not as part of the child's health insurance benefit. Since the implementation of managed care systems generally occurs within payers, not across payers, these multiple financing streams for children with disabilities create special challenges for the managed care marketplace.

Adults with Mental Illness and Substance Abuse Problems

Purchasers of health care services in both the private and public sectors have targeted services to persons with mental illness as prime candidates for managed care financing and delivery initiatives. In the private sector, many large companies have "carved-out" mental health and substance abuse benefits from their mainstream health care benefit programs, and have contracted with specialized vendors to administer these benefits. In the public sector as well, state Medicaid programs are building upon the infrastructure that has developed in managed behavioral health care to similarly "carve-out" at least a subset of mental health and substance abuse-related services covered under their own benefit packages to companies that specialize in the management of these services. On the research side, there is a larger body of research available on the impacts of managed mental health care than on how managed care impacts other services and/or populations.

While there has been significant penetration of managed care systems in the mental health/substance abuse market, it is important to recognize the differences in private and public markets as they relate to persons with mental health and substance abuse problems. In the private sector, purchasers finance mental health and substance abuse care for their employees, retirees and dependents. This population of workers and dependents is predominantly middle class and employed, with the concomitant array of mental health conditions that are most prevalent in this socio-demographic group. Depression and substance abuse disorders are diagnoses of high concern to private purchasers of health care, and the health care benefit programs of employers are structured to maximize value in the early identification and treatment of these conditions, with the objective of sustaining the productivity of their workforces.

In regard to coverage of mental health and substance abuse services for the dependents of employees, the goals are to provide coverage that is sufficiently attractive to recruit and retain a quality workforce (i.e. remaining competitive in the market for qualified workers) while limiting corporate expenditures for mental health and substance abuse care. Coverage of mental health and substance abuse care for adolescents with mental health conditions is often a major benefit issue for employers, since this population includes a subset of persons who account for a high percentage of total expenditures for these services.

In the public sector, the primary population of interest is persons with severe and persistent mental illnesses, particularly persons with disabilities associated with schizophrenia-related disorders. Approximately 30 percent of all adults under the age of 65 receiving SSI benefits, or about 1.5 million persons, qualified for SSI benefits on the basis of a mental disorder other than mental retardation (SSA, 1996). In addition, about 1 million persons with mental disorders received SSDI benefits, and are therefore insured under the Medicare program. As opposed to individuals receiving SSI benefits, persons receiving SSDI benefits have had a sufficient work history to obtain insured status under the Social Security disability system. On the whole, it is therefore reasonable to assume that SSDI beneficiaries have somewhat higher levels of functioning than persons receiving SSI.

Persons with severe and persistent mental illness have a broad range of medical, therapeutic, and supportive care needs, and a key issue in the application of managed care models to this population is what part of the care spectrum should be "managed." Although a number of state Medicaid programs have implemented mental health "carve-out" programs, it is important to recognize that states generally have only "carved-out" acute mental health services under these programs--inpatient care and outpatient follow-up care. Long-term supportive services, such as residential care programs, vocational training, day program services, and intensive case management services, have generally been excluded from the managed care contracts with carve-out vendors. Basic health care services are also usually provided by mainstream plans or the fee-for-service system.

The characteristics of persons with severe and persistent mental illness and their health and supportive service needs forcefully underscore the challenges of applying managed care models to the financing and delivery of services to this population. As a consequence, we are seeing a variety of managed care models emerging. Conceptually, one relatively simplistic way of classifying the service needs of this population is in three broad categories: (1) basic health care needs; (2) mental health-related services needed to deal with acute episodes of mental illness (short-term hospitalization, crisis intervention services); and (3) long-term supportive services intended to maintain individuals in independent or semi-independent community care settings.

As discussed above, most managed care initiatives for persons with severe and persistent mental illness have focused only on the management of one part of the total service continuum, i.e. the management of short-term hospitalizations and outpatient services. Basic health care services and long-term supportive services have, with few exceptions, not been made part of state managed care initiatives, as yet. A major reason for this segmentation of the total benefit package is related to infrastructure issues--states are building upon the infrastructure of managed behavioral health care vendors that have developed from demand created in the commercial marketplace. Another reason for this segmentation relates to the fragmentation of payments sources; Medicaid is generally the primary payer for acute mental health services for this population, while state Departments of Mental Health remain the primary payer for longer-term supportive services.

The limited scope of managed care initiatives for persons with severe and persistent mental illness has created "boundary" issues that affect the operationalization of these programs in critical ways, as well as how this population receives services. One fundamental issue is the boundary between mental health care and basic health care. Does it make sense for persons with severe mental illness to receive their primary health care through one system but have their "mental health" services managed by a separate system? If so, how is medication management coordinated across these dual systems? One major rationale for managed care is to coordinate care across a comprehensive benefit package for an enrolled population, and managed care initiatives which simply mirror the fragmentation of service delivery existent in the fee-for-service system are likely to fall short of this goal.

On the other hand, some state Medicaid programs have "carved-out" mental health services from managed care contracts for basic health care as a means to protect the population from the financial incentives of managed care to reduce services that may not be considered "medically necessary." There is considerable controversy in the commercial insurance market about the "savings" that have been achieved for health care purchasers by behavioral managed care vendors, and whether these savings are affecting mental health outcomes. Thus, in the public sector, mental health carve-outs have been used as a policy tool to protect mental health benefits from the incentives of managed care plans, most of whom have little experience in providing services to persons with severe and persistent mental illness. However, another factor in states' decisions to carve out mental health benefits has been advocacy by the specialized provider systems that serve this population to protect their market share.

Another boundary issue in designing managed care systems for persons with severe and persistent mental illness is whether to combine substance abuse programs with mental health services into an integrated managed care system. Although programmatically, there are strong reasons for bundling mental health and substance abuse benefits for this population in an integrated system, infrastructure issues and provider concerns often act to keep these services unbundled.

A final issue regarding the application of managed care models to persons with severe and persistent mental illness concerns the measurement of plan performance. What measures should purchasers (public or private) use to assess whether plans are doing a "good job?" Persons who support individuals with severe mental illness know that interventions of the highest quality can still lead to undesired outcomes in some individuals, while in other cases, people with mental illness somehow seem to get better or do okay despite inferior care or the absence of care. The relationship between good care and positive outcomes in this population is not straightforward, and the assessment of performance probably needs to measure average outcomes over sufficiently large samples of individuals, wherein the differentiation between inferior and superior care can be more reliability discerned.

Adults with Physical Disabilities and Persons with AIDS

The population of persons with severe and chronic physical disabilities, including persons with multiple sclerosis, cerebral palsy, muscular dystrophy, quadriplegia, and other conditions, encompasses a very broad range of disabilities and impairment levels. Persons with severe physical disabilities are often not well served by the fee-for-service health care system, and many experience the frustration of referrals to multiple specialists without any single physician taking overall responsibility for the oversight of their health care. If the care coordination functions of managed care models truly take hold, then managed care holds some promise for improving access and quality for persons with severe physical disabilities.

However, as with other disabled populations, many people with severe physical disabilities are skeptical that managed care organizations will provide them with access to comprehensive and coordinated medical care. Many worry that managed care organizations will be stringent in the allocation of resources in meeting their medical needs and will perceive them as "undesirable" enrollees, particularly if the cost of their care exceeds the average premium paid by their sponsor, be it an employer, Medicare, or Medicaid. For persons who require highly specialized care, many worry whether managed care plans will deny access to the most qualified specialists, and/or specialists with whom they have developed long-standing relationships.

On the purchaser side, private employers generally place little emphasis on ensuring that covered individuals with severe disabilities are adequately served in the managed care system. The disability programs of employers generally focus on short-term disability issues; the integrated management of their health insurance, workmen's compensation, and disability insurance programs; and rehabilitation initiatives which assist injured workers' to return to work as quickly as possible. The quality of health care provided to persons with severe and chronic conditions is generally not an issue of high concern to most private employers. Furthermore, the assessment of the performance of managed care plans by employers has largely focused on measures that are pertinent to large segments of their covered populations (e.g. prenatal care, immunizations, etc.) rather than on how plans treat individuals with rare conditions.

For persons with severe disabilities who do not have private insurance and are covered by Medicaid, it appears that mandatory enrollment in some kind of managed care system is increasingly inevitable. With completion of the enrollment of non-disabled Medicaid populations into managed care, states are now focusing their attention on the more difficult challenge of enrolling SSI recipients into managed care (Checkett, 1996). And unlike persons with severe mental illness, mental retardation and/or developmental disabilities, persons with severe physical disabilities generally do not have specific "sponsors" or "programs" within state government whose responsibility it is to look out for their welfare. Just as the needs of persons with physical disabilities often fall through the cracks in the current Medicaid system, there is equal danger that the needs of this population will be largely ignored in the headlong rush to achieve Medicaid savings through managed care approaches.

In contrast, persons with AIDS are receiving special attention in the development of Medicaid managed care models. Led by the model developed by the Community Medical Alliance in Boston, the concept of "specialized health plans" (SHPs) which target a single population type, is now being replicated in other states such as Maryland and New York. Specialized health plans are generally perceived as voluntary alternatives to mainstream managed care plans, rather than mandatory alternatives that persons with certain conditions would be required to enroll in. The development of specialized plans is not totally attributable to demand side factors. Another factor is that specialized provider networks with experience in providing health care services to specific populations want to be able to preserve their "product line" without having to diversify into being mainstream health plans.

The Community Medical Alliance model for managing the care of persons with AIDS places strong emphasis on the substitution of non-institutional care arrangements for institutional care, particularly during the terminal phases of the illness. The recruitment and training of medical care professionals that are committed to the treatment philosophy and culture of the Community Medical Alliance is another key component of the model.

Areas of Commonality Across Populations

Although children with severe disabilities, persons with severe and persistent mental illness, and adults with physical disabilities possess diverse characteristics that raise unique issues in the application of managed care models, there are some common characteristics shared by all of these populations. First, persons with severe disabilities of all types require access to specialty services that may be limited under managed care approaches. Closed panel plans may have few or no physicians with expertise in the care of conditions with low prevalence rates in the general population. Point-of-Service plans may allow enrollees to seek care outside of their networks, but at a higher cost to enrollees, who may have limited financial resources to utilize out-of-network providers.

Second, the health care costs of disabled populations are more predictable than the health care costs of non-disabled populations. Not only are they more predictable at the population level, but also, in many cases, at the individual level. This creates opportunities for health plans to maximize profitability by adopting business strategies to limit the enrollment (or increase disenrollment) of individuals whose health care costs are predictably above the payment rate made to the plan. Risk adjustment strategies which pay plans fairly for the expected costs of persons with disabilities, yet which still reward plans for efficient care, are critical to the application of managed care models to these populations, as well as to ensuring that persons with disabilities are provided quality care by the plans in which they are enrolled (Kronick et al, 1996). However, alternative mechanisms, other than risk adjusted capitated rates, for financially rewarding plans which enroll higher-cost individuals and providing quality services, also need to be explored. Risk-adjusted capitation may prove not to be the best solution to addressing these incentive issues, particularly given the technical and operational challenges of measuring risk and adjusting payments appropriately.

Third, the development of performance measures, which reliably assess the relative performance of plans in providing medical and supportive care to persons with disabilities of all types, is an area that requires extensive work and development. Workable approaches to eliciting the perspective of consumers, many of whom may have disabilities which impede traditional survey methods, is a key issue in the development of such measures.

Fourth, it is frequently the case that people with disabilities are receiving services from multiple payment sources and programs concurrently. The development of managed care models for these populations must respond to a set of needs that are broader than the financing and delivery of medical care. If care for these populations is to be truly integrated, then models need to be developed which consolidate the financing and delivery of health care services, rehabilitative services, long term care services, family supports, respite care, occupational supports, and personal counseling within integrated organizational structures. It may not be necessary for a single organization to possess all of these capabilities, but a managed care approach to these populations must include mechanisms for effectively coordinating the full array of medical and related services that are needed to help persons with disabilities maintain the highest level of independence possible.

What Does the Research Tell Us About the Impacts of Managed Care?

Empirical research which directly measures the health outcomes of persons with disabilities in fee-for-service versus managed care settings is extremely limited, and the research which has been conducted does not paint a consistent picture of the impacts of managed care. Research on the impacts of targeted managed care initiatives seems to paint a more positive picture, while general population studies of managed care impacts are more pessimistic. Also, considerably more research has been conducted of the impact of managed care on mental health populations than on populations with other types of disabilities.

Master et al (1996) describe improved outcomes among persons with severe disability and AIDS in a targeted Medicaid managed care program in Massachusetts. Positive outcomes included increased patient satisfaction, reduced inpatient hospital days, and improved decubitus ulcers and PCP. The study suggests that managed care can improve care for persons with severe disability through the use of innovative providers providing care in innovative settings, relative to the fee-for-service system. The results of this research may be questioned, however, given that the researchers also represent the senior management team of the managed care organization being studied. Similarly, Meyers et al (1987) found improved outcomes from managed care in a population of severely disabled adults in an independent living center, largely associated with increased resource allocation to care provided in the individual's home and centered around the person's individualized needs.

In an 11-year longitudinal study of persons with rheumatoid arthritis receiving care in fee-for-service settings versus prepaid group practice, Yelin et al (1996) found no evidence of differences in either the quantity of health care provided or in health care outcomes on either an annual or long-term basis across the systems of care.

Studies of populations in mainstream managed care plans seem less positive. An analysis of data from the Medical Outcomes Study (Ware et al, 1996) found that while health outcomes for the average patient did not differ between fee-for-service and managed care settings, health outcomes were decidedly poorer for patients who reported ill health at baseline. The study suggests that while managed care plans do quite well in maintaining the health of healthy patients, relative to fee-for-service, that people with higher medical needs fare less well in managed care, due to financial incentives among plans to reduce the level of resources applied to medical interventions. The findings of the Medical Outcomes Study support similar findings by the same research team ten years previously (Ware et al, 1986). Although the population of interest in the Ware study encompassed "chronically ill" persons, not persons with severe disabilities, it is reasonable to generalize the study findings to all populations with higher-than-average medical care needs. In another study of data from the Medical Outcomes Study, Safran et al (1992) found notable differences in dimensions of primary care provided to persons with chronic illness across fee-for-service plans, IPA-model plans, and traditional HMOs, but did not specifically associate these differing primary care paradigms with patient outcomes.

Research on the impacts of mental health managed care models is decidedly richer. The Medical Outcomes Study reported above found superior mental health outcomes in managed care for nonpoverty populations, but inferior outcomes in the poverty group (Ware et al, 1996). Wells et al (1990) found that one managed care network provided less intensive mental health services to their covered population but a higher quantity of services. Lurie et al (1992) found few differences in mental health outcomes among patients served in managed care versus fee-for-service with one exception--persons with schizophrenia showed superior outcomes in a fee-for-service setting. And in a study focusing on a population of persons with depression, Rogers et al (1993) reported that depressed patients declined, on average, in managed care settings, declines that were likely attributable to a drop-off in the prescription of anti-depressant drugs.

Other studies have reported more positive impacts of mental health managed care initiatives. Superior mental health outcomes under managed care, as well as reduced financial impacts on patients, were reported by Babigan et al (1992). Shern et al (1995) also reported greater reductions in problems, fewer unmet needs, and higher adherence to clinical protocols, among mental health clients in a managed care demonstration than in a comparison fee-for-service population.

A few studies have evaluated the impacts of mental health carve-out programs for Medicaid populations, and thus far, have generally reported favorable outcomes. Callahan et al (1995) conducted an evaluation of a Medicaid mental health carve-out in Massachusetts and reported that the carve-out vendor was successful in substantially lowering Medicaid costs for acute mental health services without any overall reduction in quality or access. Christianson et al (1995) also reported significant reductions in Medicaid expenditures for mental health services in the first year of a carve-out initiative, primarily due to reductions in inpatient admissions for mental health treatment, although mental health outcomes were not measured.

Studies that assess the impact of managed care on children with disabilities are very few, although a number of researchers have published on the potential dangers of managed care systems on children with disabilities. Fox et al (1993) reported findings from a survey of parents of children with disabilities, with mixed results. Parents were pleased with the reduced out-of-pocket costs associated with managed care systems, and with improved access to medical services, but at the same time reported increased difficulty obtaining access to specialty services and mental health care. The focus of managed care plans on requiring specialty care interventions to demonstrate rapid improvement was cited as a significant concern, and a barrier to care continuity.

Discussion: Is Managed Care for Children and Adults with Disabilities a Step Forward or a Step Backward?

Research on the impacts of managed care on children and adults with disabilities is decidedly mixed. The limited body of research published to date seems to suggest that the incentives of capitated financing mechanisms are not, in and of themselves, the primary determinants of outcomes. Rather, the research suggests that operational variables, i.e. how managed care models are applied, are equally important, if not more important, in determining how people with disabilities fare in the managed care world. Of particular interest is the nature of the managed care entity with whom the purchaser has contracted to provide care. Managed care organizations with missions to serve persons with disabilities, and organizations who provide specialized services, appear to achieve better outcomes for persons with disabilities than do mainstream plans which have no special focus on the needs of disabled populations.

As managed care models continue to evolve, and as purchasers increasingly pursue innovative managed care purchasing strategies, it will be increasingly important for researchers to help sort out which managed care models are associated with improved outcomes and reduced costs versus those managed care models which achieve reductions in health care costs only to the detriment of the populations they are intended to serve.


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Sturm, Roland, Elizabeth A. McGlynn, Lisa S. Meredith, Kenneth B. Wells, Willard G. Manning, William H. Rogers. 1994. Switches Between Prepaid and Fee-for-Service Health Systems Among Depressed Outpatients: Results from the Medical Outcomes Study. Medical Care 32(9): 917-929.

Sturm, Roland, Lisa S. Meredith, Kenneth B. Wells. 1996. Provider Choice and Continuity for the Treatment of Depression. Medical Care 34(7): 723-34.

U.S. General Accounting Office. 1996.Medicaid Managed Care: Serving the Disabled Challenges State Programs. July, GAO/HEHS-96-136.

Ware, John, Jr., William H. Rogers, Allyson Ross Davies, George A. Goldberg, Robert H. Brook, Emmet B. Keeler, Cathy Donald Sherbourne, Patricia Camp, Joseph P. Newhouse. 1986. Comparison of Health Outcomes at a Health Maintenance Organization with Those of Fee-for-Service Care. Lancet (May 3): 1017-1022.

Ware, John E., Jr., Martha S. Bayliss, William H. Rogers, Mark Kosinski, Alvin R. Tarlov. 1996. Differences in 4-Year Health Outcomes for Elderly and Poor, Chronically Ill Patients Treated in HMO and Fee-for-Service Systems. JAMA 276 (13): 1039-1047.

Wells, Kenneth B., Boris M. Astrachan, Gary L. Tischler and Jurgen Unutger. 1995. Issues and Approaches in Evaluating Managed Mental Health Care. Milbank Quarterly 17(1): 57-75.

Wells, Kenneth B., M. Audrey Burnam and Patti Camp. 1995. Severity of Depression in Prepaid and Fee-for-Service General Medical and Mental Health Specialty Practices. Medical Care 33(4): 350-364.

Wells, Kenneth B., Willard G. Manning, Jr. and R. Burciaga Valdez. 1990. The Effects of a Prepaid Group Practice on Mental Health Outcomes. Health Services Research 25(4): 615-625.

Wells, Kenneth B., Roland Sturm, Cathy Sherbourne and Lisa Meredith. 1996. Caring for Depression. A Rand Study. (Uncorrected page proofs.) Cambridge: Harvard University Press.

Yelin, Edward H., Martin A. Shearn, Wallace V. Epstein. 1986. Health Outcomes for a Chronic Disease in Prepaid Group Practice and Fee for Service Settings: The Case of Rheumatoid Arthritis. Medical Care 24(3): 236-247.

Yelin, Edward H., Lindsey A. Criswell, Paul G. Feigenbaum. 1996. Health Care Utilization and Outcomes Among Persons with Rheumatoid Arthritis in Fee-for-Service and Prepaid Group Practice Settings. JAMA 276(13): 1048-1053.

[Table of Contents]


SESSION 1: IMPACT ON MANAGED CARE ON CHILDREN WITH DISABILITIES

Reactor Biographies

Ruth E.K. Stein, M.D.
Ruth Stein is Professor and Vice Chairman of the Department of Pediatrics and Director of General Pediatrics at Albert Einstein College of Medicine. She is also Pediatrician-in-Chief at Jacobi Medical Center. She has been involved in developing models of care for children with special health care needs for many years. Her research is on chronic physical disorders in childhood and their psychological and social consequences. From 1983 to 1995, she was also the Principal Investigator of the Preventive Intervention Research Center for Child Health at the Albert Einstein College of Medicine/Montefiore Medical Center. She recently spent a sabbatical at the United Hospital Fund examining issues for the pediatric population under managed care.

Nancy R. Thaler
Nancy Thaler has been Deputy Secretary for Mental Retardation in the Pennsylvania Department of Public Welfare since 1992. She served as the Director, Bureau of Community Programs, for six years prior to being appointed Deputy Secretary. Before her career in State government, she worked for 16 years in a large nonprofit agency in southeastern Pennsylvania, Ken-Crest Services. While with that agency, she served eight years as a direct care worker, including four years as a houseparent and another eight years in administrative positions.

As Deputy Secretary for Mental Retardation, Ms. Thaler is responsible for the State's services to people with mental retardation. These services affect 3,240 people in State institutions, and 63,000 people in the community.

[Table of Contents]


Evaluation of the District of Columbia's Demonstration Program: Managed Care System for Disabled and Special Needs Children

Carol Irvin, Ph.D.
As a Health Economist at Abt Associates, Inc., Carol Irvin has conducted numerous studies on the use, costs, and outcomes of health care services provided under managed care and fee-for-service arrangements. In current work she is analyzing enrollment patterns among applicants to the Program for All-Inclusive Care for the Elderly (PACE)--a capitated day health center program for frail elders. Dr. Irvin is also currently involved in analyzing the impacts of a new pharmaceutical product on the use and costs of health care services and labor market participation among individuals with chronic progressive multiple sclerosis. In earlier work funded by the Health Care Financing Administration, she has done comparisons of care and customer satisfaction of families in Florida, Michigan, and Maine enrolled in Medicaid managed care and fee-for-service providers. She has also analyzed the impact on health care use and economic outcomes of a national capitation demonstration project among mine workers--a high risk industry population.

Dr. Irvin has also been actively researching health care issues pertaining to the maternal and child populations. Research in this area include assessing Missouri's 1988 Medicaid expansion and its impacts on enrollment patterns of pregnant women and infants, prenatal care, birth outcomes, and infant health care. Related work includes on-going analysis of the Community Integrated Service Systems (CISS) serving women and children and a series of analyses of the Special Supplemental Food Program for Women, Infants, and Children (WIC) program.

THE DEMONSTRATION

ENROLLMENT

COMPONENTS OF THE EVALUATION

DATA TO BE COLLECTED

PRIMARY RESEARCH QUESTIONS

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Families' Out-of-Pocket Expenses When Caring for Children With Special Needs: A Preliminary Report Comparing Children in Medicaid and a Commercial Product Line

Elizabeth A. Shenkman, Ph.D.
Elizabeth Shenkman is the Coordinator of Research and Program Evaluation at the Institute for Child Health Policy of the State University System of Florida, and an Assistant Professor of Pediatrics at the University of Florida. Dr. Shenkman is the Principal Investigator on the following research projects: Contractual Arrangements with Physicians: Implications for Pediatric Health Care, funded by the Robert Wood Johnson Foundation; Managed Care: Implications for Families' Out-of-Pocket Expenses When Caring for Children with Special Health Care Needs, funded by the Department of Health and Human Services, Assistant Secretary for Planning and Evaluation, Office of Health Policy; and the School Enrollment-Based Health Insurance (SEBHI) Program Evaluation, funded by the Florida Healthy Kids Corporation. In addition, she is the Co-Principal Investigator for the following project: Children with Special Health Care Needs Within Managed Care: the Department of Empirically-Based Models, funded by the Department of Health and Human Services, Maternal and Child Health Bureau.

BACKGROUND

PURPOSE

THE THIRD PARTY PAYERS

THE BENEFIT PACKAGE

HOW WERE THE CHILDREN SELECTED?

OUT-OF-POCKET EXPENSES MEASURED

CAREGIVERS' OUT-OF-POCKET EXPENSE SURVEY

WHAT WAS CONSIDERED AN OUT-OF-POCKET EXPENSE

OTHER CATEGORIES MEASURED:

DIAGNOSTIC CATEGORIES

SUMMARY AND RECOMMENDATIONS

FUTURE WORK

TABLE 1. Total Number of Children Identified
Category Florida Medicaid Commercially Insured
Total number of children screened for ICD-9-CM codes 307,241 27,487
Total number of children enrolled within the last three months of selecting the sample 253,562 13,591
Total number of children with at least one ICD-9-CM code enrolled in the last three months of selecting the sample 84,315 1,916
Percentage of enrollees with at least one ICD-9-CM code and enrolled within the last three months of selecting the sample 33% 14%


TABLE 2. Families Screened for Study Participation and Surveys Completed
Category Florida Medicaid Commercially Insured
Completed screening questions 112 547
Did not qualify 12 (10%) 128 (23%)
Qualified but refused to participate 24 32
Qualified and completed a survey 76 387


TABLE 3. Demographic Characteristics of the Study Sample
Category Children Receiving Medicaid Commercially Insured Children
Respondent Gender
- Female
- Male
 
97%
3%
 
95%
5%
Respondent Age 37.43 ± 10.90 39.55 ± 9.99
Child's Age 9.23 ± 5.23 10.48 ± 6.21
FSII (R) Score 78.53 ± 18.69
(range 17 to 100)
87.20 ± 15.33
(range 21 to 100)
Child's Racial Background
- White
- African-American
- Other
 
80%
15%
5%
 
85%
8%
7%
Child's Ethnicity
- Hispanic
- Non-Hispanic
 
11%
89%
 
12%
88%
Family Income
     Average Family Income
- less than $9,999
- $10,000 to 14,999
- $15,000 to 19,999
- $20,000 to 24,999
- $25,000 to 34,999
- $35,000 to 44,999
- $45,000 or more
- Don't know/refused
 
 
30%
17%
14%
12%
10%
7%
7%
2%
 
 
13%
22%
19%
15%
12%
8%
5%
7%
Cash Assistance-SSI for Child
- Used actual records to respond to questions
- Use an estimate of expenses
35%
35%
65%
0%
47%
53%


TABLE 4. Children's Primary Diagnostic Categories and FSII(R) Scores
Category Children Receiving Medicaid (N=76) Commercially Insured Children (N=387)
Percent Children FSII(R) Mean Core and Standard Dev Percent Children FSII(R) Mean Core and Standard Dev
Mental and Emotional Disorders 16% 67 ± 20 39% 75 ± 22
Respiratory System 13% 69 ± 206 40% 90 ± 15
Neurological 25% 76 ± 19 4% 82 ± 18
Musculoskeletal System 17% 86 ± 13 2% 92 ± 10
Special Sense Organs 8% 80 ± 18 4% 86 ± 15
Endocrine System <1% 71 ± 0 3% 90 ± 12
Cardiovascular 4% 88 ± 12 <1% 88 ± 0
Digestive System 3% 88 ± 20 <1% 90 ± 0
Multiple Body Systems 6% 88 ± 09 0% NA
Genito-Urinary System 1% 76 ± 10 1% 86 ± 18
Hemic and Lympathic System <1% 67 ± 0 0% NA
Neoplastic Diseases--Malignant <1% 100 ± 0 <1% 86 ± 0
Immune System 2% 87 ± 13 <1% 87 ± 0
Growth Impairment 2% 96 ± 7 0% NA


TABLE 5. Direct and Other Direct Expenses for the Month and Year in Dollars
Category Children Receiving Medicaid Commercially Insured Children
% Reporting Expense Mean % Reporting Expense Mean
Direct Expenses Per Month 37% 131.89 ± 393.35 87% 28.59 ± 139.2
Direct Expenses Per Year 38% 1,072 ± 1,4629.1 86% 384.11 ± 1,582
Other Direct Expenses Per Month 89% 162.57 ± 305.93 63% 30.79 ± 69.8
Other Direct Expenses Per Year 89% 1,444.1 ± 1,779.2 63% 689.4 ± 2,502.6


TABLE 6. Direct and Other Direct Expenses as a Percent of Family Income
Category Children Receiving Medicaid Commercially Insured Children
% Reporting Expense Mean % Reporting Expense Mean
Direct Expenses Per Month 37% 4.87 ± 32.4 87% 2.32 ± 10.38
Direct Expenses Per Year 36% 4.33 ± 12.2 87% 2.8 ± 12.78
Other Direct Expenses Per Month 89% 12.79 ± 21.9 63% 2.11 ± 6.20
Other Direct Expenses Per Year 88% 11.25 ± 25.6 63% 2.25 ± 10.98


TABLE 7. Caregiving Time
Category Percent Reporting Mean Hours and Standard Deviation
Medicaid 85% 15.33 ± 9.19
Commercially Insured 48% 8.76 ± 3.2













[Table of Contents]


The Managed Care Enhancement Project for Children with Special Health Care Needs

Deborah Allen
As the Director of the Division for Children with Special Health Care Needs of the Massachusetts Department of Public Health, Deborah Allen is responsible for assuring family-centered, community-based care for children with special health care needs and their families. Her division is the lead agency for implementation of Part H of the IDEA in Massachusetts and for the provision of case management services to SSI-eligible children. Ms. Allen is the Principal Investigator for the federally funded Managed Care Enhancement Project for Children with Special Health Care Needs. She is also responsible for two grants funded by Title IV of the Ryan White Care Act: MassCARE (Massachusetts Community AIDS Resource Enhancement), which focuses on pediatric and family care needs, and MCAP (the Massachusetts Women's HIV Care and Advocacy Project), which promotes identification and care of women with HIV prior to or early in pregnancy.

Ms. Allen has master's degrees in Health Policy and Management and Maternal and Child Health from the Harvard School of Public Health and is, as we speak, in the final stages of her doctoral research on "Predictors of Voluntary HIV Testing During Pregnancy," also at Harvard. She is absolutely committed to making this the last formal education she ever undertakes.

OUTLINE OF PRESENTATION

HEALTH CARE IN MASSACHUSETTS--A WHIRLWIND TOUR

MASSHEALTH OVERVIEW

SSI RECIPIENTS IN MASSHEALTH

MASSHEALTH COMPONENTS

PCC PROGRAM

PCC PROGRAM OPERATIONS

PCC PROGRAM ENROLLMENT

HMO PROGRAM

MANAGED CARE ENHANCEMENT PROJECT OVERVIEW

MCEP GOALS

MCEP NEEDS ASSESSMENT

FINDINGS ON UTILIZATION

FAMILY SURVEY METHODS

FAMILY SURVEY FINDINGS

PROVIDER SURVEY METHODS

PROVIDER SURVEY FINDINGS

OTHER NEEDS ASSESSMENT STRATEGIES

INTERVENTIONS

EVALUATION OF SCC INTERVENTION

EVALUATION OF MANUAL

CONCLUDING THOUGHTS

TABLE 1. Costs of Care for CSHCN
Average per member per month
   CSHSN
   Other children in MassHealth
$360
$58
Maximum per member per month
   CSHSN
   Other children in MassHealth
$26,519
$12,769


TABLE 2. Service Types as Percent of Total Cost for CSHCN
Home health 23%
Inpatient care 22%
Prescriptions 13%
DME 6%
Primary care visits 6%
Specialty visits 6%
ER, transportation, dental <2%
Other 13%

[Table of Contents]


Planning Grant: Services for Children with Chronic Illness and Disease in an HMO

Barbara E. Staub, M.D.
Barbara Staub has been at the White Bear Lake Clinic for 13½ years and enjoys her practice. As a general pediatrician, she sees a wide range of illness as well as doing a lot of preventive, well-child care. Dr. Staub's special interests are in chronic illness and disability.

Dr. Staub received her medical degree at the Albany Medical College in 1980. She did her pediatric internship and residency at the University of Minnesota Medical School and was board certified in 1986. Her other professional activities have been a Clinical Assistant Professor, Department of Pediatrics, University of Minnesota Medical School; and Fellow, American Board of Pediatrics.

A COLLABORATIVE PROJECT

STUDY OBJECTIVES

STUDY COMPONENTS

PARENTAL ASSESSMENT

PARENT ADVISORY BOARD

PHYSICIAN SURVEY

COMMUNITY ADVISORY COUNCIL

HEALTHPARTNERS PROVIDES

NEXT STEPS

TABLE 1. The Sample by Condition and Age
Diagnoses Ages 1-4 years Ages 5-11 years Ages 12-20 years
Cystic Fibrosis 2 2 2
Cerebral Palsy 2 2 2
Trisomy 21 2 2 2
Muscular Dystrophy 1 1 1
Juvenile Onset Diabetes Mellitus 1 1 1
Myelomeningocele 2 2 2
Autism 1 1 1
Blind/Deaf   2  


TABLE 2. Demographics Data
Ethnicity N %
White 33 94.3
Hispanic 1 2.9
Other 1 2.9
Parent Education    
Vocational School 3 8.6
Some College 14 40.0
College 12 34.3
Graduate 5 14.3
Family Income    
$20,000-40,000 13 37.1
$40,000-70,000 15 42.9
$70,000+ 7 14.3


TABLE 3. Impact: Does Child's Condition Affect Ability of Parent to be Employed?
Response N %
No 25 71.4
Yes 10 28.6


TABLE 4. Supplemental Funding/Insurance Source
Funding Source Yes (receive) No (did not receive)
TEFRA 19 (54.3%) 16 (45.7%)
SSI 4 (11.4%) 31 (88.6%)
Medicaid 4 (11.4%) 31 (88.6%)
Vocational Rehabilitation 4 (11.4%) 31 (88.6%)
WIC 3 (8.6%) 32 (91.4%)
Family Subsidy 2 (5.7%) 33 (94.2%)
Title V - 35 (100%)
AFDC - 35 (100%)


TABLE 5. Services Received and Payment Source
Service # Received Payment Sources*
(N) HP TEFRA School Other
OT 19 3 3 16 1
PT 15 5 4 10 1
Speech and Language 13 - 4 10 1
Skilled Nursing 3 1 2 1 1
Personal Care Attendant 12 - 7 2 4
Respiratory Therapy 6 3 2 1 -
Mental Health 2 2 - - -
Medication 28 24 11 - 21
DME 12 9 6 - 8
*Many families receive more than one payment source.







[Table of Contents]


State Medicaid Managed Care Policies Affecting Children with Chronic or Disabling Conditions

Harriette B. Fox
Harriette Fox is the President of Fox Health Policy Consultants, a small Washington-based consulting firm specializing in the financing and delivery of maternal and child health services, and the co-director of the Maternal and Child Health Policy Research Center. She has had extensive experience managing projects examining Medicaid, private health insurance, and other financing arrangements to support services to children, with a particular focus on issues pertaining to managed care and health insurance reform. Her work has included analyses of Federal laws and policy options; evaluations of State Medicaid and maternal and child health programs; surveys of State and private industry insurance practices; and consultation to numerous State and private organizations. She has published extensively on the subject of health care financing and children. Before establishing Fox Health Policy Consultants in 1982, Ms. Fox was the Senior Program Analyst for the Select Panel for the Promotion of Child Health. She also had served as a consultant to the Institute of Medicine and the National Health Policy Forum.

Margaret McManus
Margaret McManus is President of McManus Health Policy, Inc., a small consulting firm which specializes in managed care and health insurance reform affecting children. She also co-directs a Maternal and Child Health Policy Research Center for Paul Newacheck and Harriette Fox, funded by the Federal Maternal and Child Health Bureau. For the past 15 years, Ms. McManus has consulted with the American Academy of Pediatrics' Committee on Child Health Financing and a variety of other national, State, and local organizations. She has recently assisted the Maternal and Child Health Bureau in convening a series of managed care work groups on definitions, capitation and risk adjustment, quality of care, and family participation. Ms. McManus has published extensively on the subject of health care financing and children. Most recently, with Harriette Fox, she has completed a report entitled, Medicaid Managed Care for Children with Chronic or Disabling Conditions: Improved Strategies for States and Plans.

TABLE 1. State Medicaid Policies Regarding Children Served by Fully Capitated Plans
DRAFT-Not for Publication
State Categorical Groups Enrolled Voluntary or Mandatory Enrollment1 Specific Exemptions for Non-institutionalized Special-Needs Children Pediatric Services Carved Out of Managed Care Contracts2
Arizona AFDC, AFDC-related, SSI Mandatory Children receiving developmental disability services Mental health and substance abuse (capitated), hospice, personal care, specialty services for CSHN-eligible children
California4 AFDC, AFDC-related, SSI, Foster Care Mandatory in 3 counties; voluntary in 17 counties; mandatory for AFDC only in one county None Mental health services for SED-eligible children, intensive substance abuse, early intervention, health-related special education, dental5(capitated), certain comprehensive case management, specialty services for CSHN-eligible children
Colorado AFDC, AFDC-related, SSI, Foster Care Voluntary None Intensive mental health, certain substance abuse, intensive ancillary therapies, dental, hospice, personal care
Delaware AFDC, AFDC-related, SSI, Foster Care Voluntary None Mental health, substance abuse, health-related special education, dental, prescription drugs
District of Columbia AFDC, AFDC-related Voluntary None Mental health, substance abuse, early intervention, health-related special education, dental, vision
Florida AFDC, AFDC-related, SSI, Foster Care Voluntary Children receiving CSHN services Intensive mental health, intensive substance abuse, hospice, dental5, vision5, personal care, multi-handicap assessments, specialized services for foster care children
Hawaii AFDC, AFDC-related, Foster Care, Demonstration Eligibles Mandatory None Mental health services for SED-eligible children (capitated), dental (capitated), personal care
Illinois AFDC Voluntary None Dental (capitated), vision, comprehensive case management
Indiana AFDC, AFDC-related Voluntary None Mental health, substance abuse, vision
Iowa AFDC, AFDC-related6 Voluntary None Substance abuse, health-related special education, dental, prescription drugs5, durable medical equipment5
Maryland AFDC, AFDC-related, SSI Voluntary None Certain early intervention, certain health-related special education, hospice, personal care, certain EPSDT expanded benefits7
Massachusetts AFDC, AFDC-related, SSI Voluntary None Dental, prescription drugs, vision, personal care, intensive durable mental equipment5
Michigan AFDC, AFDC-related, SSI, Foster Care Voluntary Children receiving CSHN services Intensive mental health, health-related special education, certain dental, personal care
Minnesota AFDC, AFDC-related Mandatory in eight counties; voluntary in one county Children who are determined to be seriously emotionally disturbed prior to enrollment, determined blind or disabled but not eligible for SSI, likely to be terminally ill, or receiving an adoption subsidy8 Case management for SED-eligible children
Missouri AFDC Mandatory None Mental health services for SED-eligible children, intensive substance abuse, health-related special education, dental, prescription drugs, hospice, certain case management, EPSDT expanded benefits
New Hampshire AFDC, AFDC-related, Foster Care Voluntary None Intensive mental health, intensive substance abuse, intensive ancillary therapies, early intervention, health-related special education, dental, prescription drugs, intensive personal care, comprehensive case management, durable medical equipment
New Jersey AFDC, AFDC-related, SSI, Foster Care Voluntary Children who have chronic debilitating conditions, language difficulties, or who have a provider relationship that would be substantially disrupted Mental health, substance abuse, intensive ancillary therapies, health-related special education, personal care
New York AFDC, AFDC-related, Foster Care (not in NYC) Mandatory in one borough; voluntary elsewhere Children receiving CSHN services, certain children who have specific medical needs that cannot be met through an HMO Intensive mental health, intensive substance abuse, early intervention, health-related special education, dental5, vision5, hospice, personal care, comprehensive case management, durable medical equipment5
North Carolina AFDC Voluntary None Mental health and substance abuse (both capitated), dental, vision, personal care
Ohio AFDC, AFDC-related Mandatory in two counties; voluntary elsewhere None Hospice
Oregon AFDC, AFDC-related, SSI, Demonstration Eligibles Mandatory in 28 out of 36 counties Children who have an existing provider relationship that would be disrupted or who have specific medical needs that cannot be met through the HMO9 Mental health in all but 3 counties, intensive substance abuse, health-related special education, dental5 (some capitated), personal care
Pennsylvania AFDC, AFDC-related, SSI, Foster Care Mandatory in one county; voluntary elsewhere None Certain intensive mental health, early intervention, personal care, specialized services for foster care children5, certain services for mentally retarded and developmentally disabled children
Rhode Island AFDC, AFDC-related, Demonstration Eligibles Mandatory None Intensive mental health, mental health services for SED-eligible children, intensive substance abuse, certain early intervention, certain health-related special education, dental, personal care, comprehensive case management, EPSDT expanded benefits
Tennessee AFDC, AFDC-related, SSI, Foster Care, Demonstration Eligibles Mandatory None Intensive mental health, personal care
Texas AFDC, AFDC-related Mandatory None Intensive mental health, early intervention, health-related special education, dental, vision, prescription drugs, comprehensive case management, durable medical equipment, EPSDT expanded benefits
Utah AFDC, AFDC-related, SSI, Foster Care Voluntary None Mental health (capitated), substance abuse, early intervention, health related special education, dental5, prescription drugs5, certain services for mentally retarded and developmentally disabled children
Virginia AFDC, AFDC-related Voluntary None Intensive mental health, health-related special education
Washington AFDC, AFDC-related Mandatory Children whose distance from delivery sites makes enrollment impractical, who have language difficulties, who have an existing provider relationship that would be substantially disrupted, or who have a significant medical need that cannot be met through the HMO10 Most mental health (capitated in some areas), substance abuse, early intervention, health-related special education, dental, eyeglasses, personal care, comprehensive case management
Wisconsin AFDC, AFDC-related Mandatory None Dental5
AFDC-related = children who qualify for Medicaid because of their poverty-level status as regular or optional Medicaid eligibles as well as children whose families meet the AFDC income criteria but do not receive AFDC benefits.
CSHN = state Title V program for children with special health care needs
SED = state comprehensive community mental health services program for children and adolescents with serious emotional disturbances
  1. In some states, Medicaid-eligible children were required to choose between enrollment in a fully capitated plan or in another form of managed care, such as a primary care case management program. These states are shown as having voluntary enrollment.
  2. Use of the qualifying term "inclusive" in this column means services beyond plan limits or services required by special high-need populations. The use of the qualifying term "certain" means only particular services within a category or services provided by a specific type of provider (usually a publicly-funded provider). Where the word "capitated" appears in parentheses after a service, this means that the state had developed a separate capitated arrangement for this service.
  3. Arizona enrolls children in foster care in a separate fully capitated plan.
  4. California is operating a number of different Medicaid managed care arrangements and policies differ across arrangements. Information in the table is correct for the geographic managed care model.
  5. Plans have the option of including this service in their contracts.
  6. Iowa allows AFDC and AFDC-related children who enter into foster care to continue to receive care through an HMO, if they elect to do so. In such instances, specialized services for foster care children are paid for separately.
  7. A carve-out of "EPSDT expanded benefits" means that a state had carved out of its contract federally-allowable Medicaid services that would not otherwise be covered under its regular Medicaid plan or expanded coverage of services that otherwise would have limitations.
  8. Minnesota also exempts children who are refugees or who have a primary care provider outside of Itasca County from HMO enrollment.
  9. Oregon also exempts children who are Native Americans from HMO enrollment.
  10. Washington also exempts children who are Native Americans or homeless from HMO enrollment.
SOURCE: Information was obtained by Fox Health Policy Consultants through telephone interviews with state Medicaid agency staff during the spring and summer of 1994 and was verified by the states as being accurate as of March 31, 1995.


TABLE 2. Medicaid Services to Children Excluded from Contracts
DRAFT-Not for Publication
Services Carved Out of Contracts Number of States (n=29) Percent of States
Dental services 20 69%
Health-related special education services 16 55
Personal care 15 52
Some mental health services 13 45
Early intervention services 10 34
Case management 9 31
All mental health services 9 31
Vision services 9 31
Prescription drugs 7 24
Hospice 7 28
Durable medical equipment 5 17
EPSDT expanded benefits 4 14
Some ancillary therapies 3 10
CSHN specialty services 2 7
Specialized services for foster care children 2 7
SOURCE: Information was obtained by Fox Health Policy Consultants through telephone interviews with state Medicaid agency staff in March 1995, and was verified by the states as being accurate as of March 31, 1995.


TABLE 3. EPSDT Language in State Medicaid Managed Care Contracts Regarding Diagnosis and Treatment
State Specifies and Explains the EPSDT Benefit1 Includes Core Elements of OBRA '89 EPSDT Language Incorporates Federal EPSDT Law or Rules by Reference Incorporates State EPSDT Law or Rules by Reference
Requires services to correct or ameliorate identified defects, illnesses, or conditions Requires services for both physical and mental health problems Requires all federally allowable diagnostic, treatment, and other health care services
Arizona X X X X   X
California X         X
Colorado X       X  
Delaware X X X X X  
District of Columbia            
Florida X     X X X
Hawaii X X X X X  
Illinois X X X   X  
Indiana X       X  
Iowa X       X  
Maryland X X   X    
Massachusetts X X   X X X
Michigan X       X  
Minnesota X       X  
Missouri2 X     n/a X  
New Hampshire X X X X X  
New Jersey X X X   X  
New York X X X X    
North Carolina X X X      
Ohio X         X
Oregon3 n/a n/a n/a n/a n/a n/a
Pennsylvania X X X X X  
Rhode Island2 X X   n/a    
Tennessee X       X  
Texas2 X     n/a X  
Utah X X X X    
Virginia X X X X    
Washington X   X   X X
Wisconsin X X X X X X
TOTAL 27 of 28 15 of 28 13 of 28 12 of 25 18 of 28 7 of 28
  1. Certain states substitute their own program names for the Early Periodic Screening, Diagnosis and Treatment benefit. For the Purposes of this analysis, these states were considered to have specified and explained the EPSDT benefit if their contracts explicitly addressed each component (screening, diagnosis and treatment) in their definition of the benefit.
  2. This state's contract excludes all expanded EPSDT benefits (services beyond those included in the state plan). However, the contractor is responsible for all other diagnostic and treatment services.
  3. Oregon has waived EPSDT requirements under a Section 1115 waiver.
SOURCE: Information is based on an analysis of contracts in effect in December 1995, performed by Fox Health Policy Consultants. Provider manuals, administrative rules, and other documents referenced in the state contracts were included in the analysis.


TABLE 4. Medical Necessity Language in State Medicaid Managed Care Contracts
State Medical Necessity Defined in Contract If included in contract, Criteria Used to Define Medical Necessity
General Child-Specific Includes Services for Preventive Purposes as well as Diagnostic and Treatment Purposes Includes Treatments for a "Condition," "Disability," or "Handicap" in Addition to an "Illness or Injury" Qualifies Terms Such as "Disability," "Handicap" or "pain" with "severe" of "significant" Requires Conformance with Standards of Good Medical Practice or Prevailing Community Standards Requires the most appropriate level of services that can be provided safely Requires the Least Costly Alternative Treatment of Equal or Reasonably Equal Effectiveness Requires Evidence of Effectiveness or Proven Medical Value
Arizona X   X X          
California                  
Colorado X   X X   X X    
Delaware                  
District of Columbia                  
Florida X   X X X X X X  
Hawaii X         X      
Illinois X     X   X      
Indiana                  
Iowa X     X   X   X  
Maryland X   X            
Massachusetts X   X X   X      
Michigan                  
Minnesota X   X X X X      
Missouri                  
New Hampshire   X X X          
New Jersey                  
New York X   X X X        
North Carolina                  
Ohio X       X X   X  
Oregon X   X     X X   X
Pennsylvania                  
Rhode Island X     X          
Tennessee X         X X    
Texas                  
Utah                  
Virginia                  
Washington X   X X   X   X  
Wisconsin X   X X   X X X X
TOTAL 16 of 29 1 of 29 11 of 17 with definitions 12 of 17 with definitions 4 of 17 with definitions 12 of 17 with definitions 5 of 17 with definitions 5 of 17 with definitions 2 of 17 with definitions
SOURCE: Information is based on an analysis of contracts in effect in December 1995, preformed by Fox Health Policy Consultants. Provider manuals, administrative rules, and other documents referenced in the state contracts were included in the analysis.

[Table of Contents]


Families' Out-of-Pocket Expenses When Caring for Children With Special Needs: A Preliminary Report Comparing Children in Medicaid and a Commercial Product Line

Elizabeth A. Shenkman, Ph.D.

INTRODUCTION

Despite the growing interest in enrolling children with special health care needs in managed care plans, remarkably little is known about the effects of managed care on this vulnerable group.1, 2 This lack of information is due, in part, to the fact that many private managed care organizations (MCOs) are unwilling to release person level use data so that analyses can be conducted on those enrollees who have special health care needs. In addition, states with Medicaid managed care plans have exempted some or all children with special needs from enrollment in these plans. Therefore very limited data from the public sector are available.3, 4

Many concerns have been raised about how children with special health care needs and their families will fare within a managed care environment. It is not known whether families will be able to obtain the services their children need in an environment where health care use and expenditures are closely monitored. Within the current fee-for-service system, families often face strong financial burdens both in terms of out-of-pocket expenses and caregiving time. These financial burdens are disproportionately borne by lower-income families.5 Some believe that placing children with special health care needs in managed care arrangements will result in even higher out-of-pocket expenses for families as they enter a system with stringent health care utilization management and potential financial disincentives to physicians to provide care or make referrals.6


PURPOSE

The purpose of this paper is to present preliminary information about families' out-of-pocket expenses when caring for children with special health care needs. Families' expenses for two groups of children are presented. The first group are commercially-insured children with special needs who are receiving care through private health maintenance organizations. The second group are children with special needs who are receiving care through Medicaid fee-for-service or primary case management programs.

The information in this paper is preliminary because we are continuing to collect data both for the Commercially insured and the Medicaid populations. In addition, we are presenting the findings from the survey data only. We have actual health care use data from the HMOs and Medicaid from their claims and encounter data bases for each child in the study. However, these data have not been completely analyzed and therefore are not included in this report.


METHODS

The Third Party Payers Participating in the Study

The Third Party Payers--Commercial: The commercially insured children participating in this study to date are insured through a special program designed to provide subsidized insurance premiums to previously uninsured children. Families with incomes below 130% of the federal poverty level (FPL) pay $5.00 per child per month; those between 131% and 185% of the FPL pay $15.00 per child per month; and those at 186% of the FPL or above paid the full premium of $50.00 per child per month. Approximately 30,000 children are currently enrolled. The benefit package is the same as that offered through Medicaid (Table 1). A key program feature is the provision of care through the private sector. The program is not intended to extend Medicaid coverage or to provide health care as a variation of the current Medicaid system for children in Florida. A private not-for-profit corporation negotiates contracts with HMOs to assume the financial risk and to provide health care services for the children. Four HMOs currently have contracts and deliver care through private physicians' offices and clinics in the children's communities. Both pediatricians and family practitioners serve as the children's primary care providers. Extensive specialty networks including tertiary care facilities are available through the HMOs. Program enrollment is voluntary.

The Third Party Payers--Florida Medicaid: The Medicaid Program in Florida offers coverage to the following children: (1) children less than one year of age and pregnant women at 134% to 185% of the FPL; (2) children one to six years of age at 101% to 133% of the FPL; and (3) children six to thirteen years at 100% of the FPL or below. Forty-nine percent of children receiving Medicaid are enrolled in the Medipass Program which is a Primary Care Case Management Program. Physicians provide care coordination for these children on a capitated basis. Any services provided beyond care coordination are reimbursed at a Medicaid fee-for-service rate. Catastrophic coverage is available through Florida Medicaid.

Sample Selection

Children were initially identified for possible inclusion in the study through the following steps:

  1. Each HMO and Florida Medicaid provided child-specific health care use data including International Classification of Diseases, Clinical Modification, 9th Revision (ICD-9-CM) codes for each health care encounter.

  2. In collaboration with two physicians from the University of Florida, Department of Pediatrics, we developed a list of ICD-9-CM codes that might indicate the child had a special health care need. The list was intentionally broad and included conditions of high and low prevalence (Appendix A).

  3. The health care use data bases were searched to identify those children who had at least one health care visit during which an eligible ICD-9-CM code was identified. We then identified those children with an eligible ICD-9-CM code who were enrolled within three months preceding the sample selection. We wanted to include those who were recently enrolled so that the survey data and health care use data were as contemporaneous as possible.

    Table 2 shows the number of children identified across each HMO and Florida Medicaid for possible inclusion in the study. As expected, significantly more children were identified as possibly having a special health care need through the Medicaid data base than through the private HMO data bases (33% versus 14%).

  4. Once the commercially insured children were identified from the data bases, we contacted a census of all those potentially eligible and administered a series of screening questions to determine final eligibility into the study. The screening questions were used to ensure that we only included those children who had moderate to severe health care needs. The following screening questions were used:

    1. Because of a physical or mental condition, does your child require more supervision than other children of his/her age?
    2. Does your child require extra or specialized medical care, therapies, supplies or medical equipment because of a special health care need?
    3. Has your child had his/her special health care need for 6 months or longer?

    Those children whose families answer yes to question a or b and c will be included in the study. That is, a family who has a child (1) requiring increased supervision or has a child who requires specialized medical care, therapies, supplies, or medical equipment because of a special health need; and (2) the child has had the condition for 6 months or longer were included in the study.

    Questions about activities of daily living (ADLS) were not used as initial screening questions because, based on our past work, a significant number of children may have special health care needs with no ADL deficits. For example, a child with mental retardation could have many needs for educational interventions and supervision resulting in additional financial and caregiving burdens on the families; yet have no ADL deficits.

    Table 3 shows the number of parents with commercially insured children meeting the ICD-9-CM criteria who were contacted, the number who met the screening question criteria, and the number who participated in the survey.

  5. Because so many children in the Medicaid data base had an ICD-9-CM code that might qualify them for inclusion in the study, we obtained a simple random sample of the Medicaid enrollees to contact. The same screening questions described in Step 4 also are being used to determine final study eligibility for the Medicaid population. We randomly selected 5,500 children, administered screening questions to 112 parents to date, and obtained 76 completed interviews (Table 3). We expected to find not only a greater number of children with special health care needs in the Medicaid data base, but also more children with significant health care needs when compared to the HMO population. As expected, more children in the Medicaid data base met the screening questions for inclusion into the study when compared to the pediatric HMO population (23% versus 10%).

  6. At the present time, we have completed surveys for 387 children in the commercial product line and 76 children participating in the Medicaid Program. The data for these children are presented in this report. As previously mentioned, we are continuing to conduct surveys among the Medicaid enrollees and also among children who are receiving health insurance through other commercial product lines offered by the HMOs with whom we are working.

Measures of Caregivers' Out-of-Pocket Expenses

We developed the Caregivers' Out-of-Pocket Expense (COPE) Survey to assess the following dimensions for expenses:

Survey items initially were developed based on a literature review of expenses families incur when caring for children with disabilities.7, 8, 9 A panel of reviewers reviewed the first two drafts of the surveys for content. Reviewers included: a generalist pediatrician from an academic health center who specializes in caring for children with special health care needs, a family economist, a health care economist, two state Title V Children with Special Health Care Needs (CSHCN) Program Directors, two families who have children with special health care needs, and two policy analysts from the former Congressional Office of Technology Assessment. Following the content reviews, the survey was revised and field tested with 60 families. Based on the field testing, a final version of the survey was developed and used in this research.

This phase of our research focuses on families reported direct and other direct expenses. Families were determined to have incurred direct or other direct out-of-pocket expenses if the respondent indicated that the child received the particular service or item and it was paid for either entirely or in part by the parent or guardian, another relative residing in the household, or the child's Supplemental Security Income (SSI) check. The respondent was asked what the out-of-pocket expense was for the preceding month and for the preceding year for each service or item the child received. He or she also was asked if the expenditure for the month was typical or not and if the dollar amount provided was based on actual records or an estimate.

If the family was required to pay a co-payment for a service and the payment was made according to the criteria described in the preceding paragraph; the dollar amount was attributed to the particular category for which the co-payment was required. For example, in the commercially insured population, families are required to pay a $3.00 co-payment for an acute care visit to their primary care provider. The $3.00 co-pay would be described as an out-of-pocket expense for a doctor's visit. Thus out-of-pocket expenses could represent a co-payment for a particular service or item; an expenditure for a service or item not covered in the benefit package; or a service or item that was covered by the benefit package but the maximum amount allowed for payment was exceeded and the family had to begin paying.

Measures of Child's Functional Status

We used the Functional Status Rating Scale [FSII(R)], short form, to assess the children's level of functioning. The FSII(R) assess a child's functioning in the areas of social behavior, sleeping, eating, and activities.10 The instrument also was specifically designed to detect changes in a chronically ill child's functioning across time. The short version contains 14 items and has an alpha coefficient of 0.80. An alpha coefficient measures the degree to which the items on an instrument measure the same concept.11 The alpha coefficient of .80 means that the items on the FSII(R) are consistently measuring the same concept.

The instrument is scored from 0 to 100 with 100 representing the highest functioning. The developers established concurrent validity by correlating the FSII(R) measures with established measures of morbidity such as days in hospital and school absences. The correlations were moderate ranging from .24 to .47. A copy of the items are contained in Appendix B.

Demographic Measures

We gathered information about the family's race and ethnicity, respondent's age, total family income, and participation in the SSI Program for children. In addition, we asked about the child's age and diagnosis.

Data Analysis

Descriptive data only are presented for this phase of the study. Specifically we will describe the following:


RESULTS

The Study Sample

Children enrolled in Medicaid varied from children in the commercial program on several characteristics (Table 4). A higher percentage of children in Medicaid were African-American (15% versus 8%) and from lower income homes. Thirty percent of the Medicaid enrollees reported an average family income of less than $9,999 per year compared to only 13% of the commercially insured. However, overall both groups had low incomes with 15% or less of the respondents reporting a family income over $35,000 per year. In addition, children in the Medicaid program had significantly lower scores on the FSII(R) than the commercially insured children (p<.01). When reporting out-of-pocket expenses, it is important to note that a higher percentage of families in the commercially insured group when compared to the Medicare group used actual records rather than recall to report their expenses.

More than 70 different diagnoses are represented in this study. Given the diverse array of diagnoses, children were classified into categories (Table 5). We used the Social Security Administration's diagnostic categories that are contained in their medical listings of impairments. Children in Medicaid had a broader range of diagnoses and more severe diagnoses than children in the commercially insured group. The most striking example can be found in the respiratory category. Ninety-two percent of the commercially insured children in the respiratory category had a diagnosis of asthma compared to only 2% of the children receiving Medicaid. Children who received Medicaid and were classified in the respiratory category had diagnoses including: ventilator dependency, cystic fibrosis, and chronic respiratory failure.

The greatest similarity in diagnoses was found in the category of mental and emotional disorders. Attention deficit disorder (ADD) or attention deficit hyperactivity disorder (ADHD) were the most frequently occurring conditions with 80% of the commercially insured children and 74% of the children in Medicaid in this category having one of these two diagnoses. Depression and mental retardation were also seen in this category for both groups.

In addition to classifying into diagnostic groups, we obtained FSII(R) scores on each child. Prior research has documented that there is wide variability in functioning both between and within diagnoses; therefore classifying children according to their functioning as opposed to a diagnostic label is a valuable approach. The children's FSII(R) score by diagnostic category is contained in Table 5. With the exception of neoplastic diseases, children in Medicaid had lower scores for each diagnostic category when compared to commercially insured children. For both groups, children with mental and emotional disorders had the lowest scores in functioning. However, these low scores may reflect the fact that the instrument used contains many items that could be indicative of a mental or behavioral problem such as items referring to the child's mood, cheerfulness, and crying behavior. Few of the items specifically refer to limitations in physical activity.

The Amount Families Spend on Direct and Other Direct Out-of-Pocket Expenses

Given the higher functional status scores of children in the commercially insured program, it is not surprising that families incurred less out-of-pocket expenses in both absolute dollar amounts and in terms of the amount spent as a percent of family income when compared to Medicaid enrollees. Tables 6 and 7 illustrate the amount families spent out-of-pocket on direct and other direct expenses. Cross-tabulations of families' out-of-pocket expenses by income level reveal that families with incomes below $14,999 per year spend a disproportionate amount of their income on caring for their children when compared to families with incomes above that amount. While the average amount of out-of-pocket expenses as a percent of family income was only about 2% for the commercially insured, these expenses represented 12% of family income for those reporting incomes below $14,999. A similar regressive pattern was noted for Medicaid recipients with families at the lowest income levels paying as much as 32% of their income to care for their children with special needs.

Families with children in the commercial insurance program spent about equal amounts of money per month on direct and other direct expenses. However, families who had children in the Medicaid program spent greater amounts of money on other direct expenses. These other direct expenses included items and services that are not traditionally covered by Medicaid or other third party payers. Table 8 describes specific expenditures by third party payer category. Families incurred expenses for medications, special diets, assistive technologies, and respite care that are not contained in the Medicaid benefit package. Those families who received supplemental security income (SSI) reported spending this money on these and other items that were described in the "other direct expense" category. Ninety percent of families reported using the child's SSI check for one or more of the items or services in this category.

An important but often neglected area of out-of-pocket expenses to the family is that of indirect expenses or the time families spent caring for the child and lost employment opportunities. For this report, we calculated the average amount of time in hours that families reported spending in caregiving activities for their children with special needs. The number of hours spent in caregiving was obtained through the following methods:

We obtained the following results:

We have several more items about families caregiving activities and the impact that this has had on their employment. These data will be analyzed in future work.


SUMMARY

The data contained in this report are preliminary. We are gathering more survey data from Medicaid and from other commercial product lines. However, some patterns are noted in these data that have important implications when designing health care programs and financing mechanisms for children with special health care needs.

Families incur significant out-of-pocket expenses when caring for their children. Lower income families bear the heaviest financial burden with expenses as high as 32% of their total income. While families with children in the HMOs have less expenses than those families with children in Medicaid, they still bear out-of-pocket expenses that take the heaviest toll on the lowest income groups. Benefit packages must be designed that consider the broad array of services required by children with special health care needs including respite care and educational technologies.

Moreover, the impact on the family in terms of their time must be considered. Perhaps health care expenditures can be minimized but at great personal cost to families. Particularly for families receiving Medicaid, more than half of their day can be spent providing care to their children with special needs. The economic impact of this activity must be considered.

Often it is difficult to compare out-of-pocket expenses between different third party payers due to differences in benefit packages. In this phase of our study, all of the children received the same benefits. Although this is a preliminary report, differences in out-of-pocket spending can largely be attributed to differences in the children's health status. Children in Medicaid had much lower scores on functioning when compared to children in the commercially insured group.

Further analytic work will be conducted using regression techniques to more fully describe the factors influencing out-of-pocket expenses. In addition, we will include the children's health care use data from the claims data bases as well as measures of the time families spend in caregiving.


NOTES

  1. Ireys, HT. "Children with Special Health Care Needs: Evaluating Their Needs and Relevant Service Structures." Paper commission by the Institute of Medicine. Baltimore, MD: Johns Hopkins University, November 1994.
  2. Batavia, AI. "Health Care Reform and People with Disabilities." Health Affairs. 1993; 12:40-55.
  3. Ireys, HT. "Children with Special Health Care Needs: Evaluating Their Needs and Relevant Service Structures." Paper commission by the Institute of Medicine. Baltimore, MD: Johns Hopkins University, November 1994.
  4. Butler, P, RL Mollica, and T Riley. Children's Health Plans. Portland, ME: National Academy for State Health Policy, 1993.
  5. Rasell, E, J Bernstein, and K Tang. "The Impact of Health Care Financing on Family Budgets." Challenge. November-December 1993:12-21.
  6. Newacheck, PW, DC Hughes, JJ Stoddard, and N Halfon. "Children with Chronic Illness and Medicaid Managed Care." Pediatrics. 1994; 93:497-500.
  7. Newacheck, PW, and N Halfon. "The Financial Burden of Medical Care Expenses for Children." Medical Care. 1986; 24:1110-1117.
  8. Jacobs, P, and S McDermott. "Family Caregiver Costs of Chronically Ill and Handicapped Children: Method and Literature Review." Public Health Reports. 1989; 104:158-163.
  9. Leonard, B, JD Brust, and JJ Sapienza. "Financial and Time Costs to Parents of Severely Disabled Children." Public Health Reports. 1992; 107:302-312.
  10. Stein, REK, and DJ Jessop. Manual for the Functional Status II(R) Measure. New York: Albert Einstein College of Medicine of Yeshiva University, 1991.
  11. Aday, L. Designing and Conducting Health Surveys. San Francisco, CA: Jossey-Bass, 1991.
TABLE 1. Summary of Medicaid Benefits in Florida*
Category Reimbursement
Durable Medical Equipment
  • Limited to one per day per recipient
  • District service authorization required for certain orthotics, prosthetics, and other equipment for Medicaid eligible EPSDT children under the age of 21
The lesser of the amount billed or the established maximum Medicaid fee.
Home Health Care Services
  • Intermittent and private duty/personal care
The lesser of the amount billed or the maximum allowable
Hospice Care
  • Routine or continuous home care
  • Inpatient respite or general inpatient care
Medicaid allowable rate
Hospital Services--Inpatient 45 day limit
Hospital Services--Outpatient $2.00 co-payment for Medicaid
Laboratory Medicaid allowable rate
Eye Care
  • Refractions
  • Eyeglasses
$3.00 co-payment
Covered every two years with a $10.00 co-pay. Only Medicaid frames.
Physician Services $2.00 co-payment for Medicaid; $3.00 co-payment for commercial product line.
Podiatry Services $2.00 co-payment for Medicaid. Certain limitations.
Prescription Drugs 31 day supply with a $2.00 co-pay; $3.00 co-pay for commercially insured
Occupational Therapy Services One treatment per day; reassessments every 6 months; minimum treatment period; Medicaid allowable rate
Physical Therapy Services One treatment per day; reassessments every 6 months; minimum treatment period; Medicaid allowable rate
Respiratory Therapy Services One therapy per day; minimum treatment period of 30 minutes; reassessment every 6 months; Medicaid allowable rate
Speech Therapy One therapy per day; minimum treatment period of 30 minutes; reassessment every 6 months; Medicaid allowable rate
Mental Health 20 visits per year with $5.00 co-pay
Extended Care Varies by type of extended care required
Transportation Emergency transport covered in full
*Does not include all benefits offered such as special waivers, birth centers, nursing homes.


TABLE 2. Total Number of Children Identified From the Health Care Use Data Bases Using Selected ICD-9-CM Codes
Category Florida
Medicaid
Commercially
Insured
Total number of children screened for ICD-9-CM codes that may reflect a special health care need 307,241 27,487
Total number of children enrolled within the last three months of selecting the sample 253,562 13,591
Total number of children with at least one ICD-9-CM code indicating a possible special health care need enrolled in the last three months of selecting the sample 84,315 1,916
Percentage of enrollees with at least one ICD-9-CM code indicating a possible special health care need and enrolled within the last three months of selecting the sample 33% 14%


TABLE 3. Families Screened for Study Participation and Surveys Completed
Category Florida
Medicaid
Commercially
Insured
Completed screening questions 112 547
Did not qualify 12 (10%) 128 (23%)
Qualified but refused to participate 24 32
Qualified and completed a survey 76 387


TABLE 4. Demographic Characteristics of the Study Sample
Category Children
Receiving
Medicaid
Commercially
Insured
Children
Respondent Gender
  • Female
  • Male
 
97%
3%
 
95%
5%
Respondent Age 37.43 ± 10.90 39.55 ± 9.99
Child's Age 9.23 ± 5.23 10.48 ± 6.21
FSII(R) Score 78.53 ± 18.69
(range 17 to 100)
87.20 ± 15.33
(range 21 to 100)
Child's Racial Background
  • White
  • African-American
  • Other
 
80%
15%
5%
 
85%
8%
7%
Child's Ethnicity
  • Hispanic
  • Non-Hispanic
 
11%
89%
 
12%
88%
Average Family Income
  • Less than $9,999
  • $10,000 to 14,999
  • $15,000 to 19,999
  • $20,000 to 24,999
  • $25,000 to 34,999
  • $35,000 to 44,999
  • $45,000 or more
  • Don't know/refused
 
30%
17%
14%
12%
10%
7%
7%
2%
 
13%
22%
19%
15%
12%
8%
5%
7%
Cash Assistance-SSI for Child
  • Used actual records to respond to question
  • Used an estimate of expenses
 
35%
35%
65%
 
0%
47%
53%


TABLE 5. Children's Primary Diagnostic Categories and FSII(R) Scores
Category Children Receiving Medicaid (N=76) Commercially Insured Children (N=387)
Percent
Children
FSII(R) Mean Score & Standard Deviation Min. Max. Percent
Children
FSII(R) Mean Score & Standard Deviation Min. Max.
Mental and Emotional Disorders** 16% 67 ± 20 18 100 39% 75 ± 22 18 100
Respiratory System 13% 69 ± 206 50 100 40% 90 ± 15 46 100
Neurological 25% 76 ± 19 28 100 4% 82 ± 18 24 100
Musculskeletal System 17% 86 ± 13 31 100 2% 92 ± 10 53 100
Special Sense Organs 8% 80 ± 18 42 100 4% 86 ± 15 44 100
Endocrine System <1% 71 ± 0 71 NA 3% 90 ± 12 20 100
Cardiovascular 4% 88 ± 12 71 100 <1% 88 ± 0 88 NA
Digestive System 3% 88 ± 20 43 100 <1% 90 ± 0 90 NA
Multiple Body Systems* 6% 88 ± 09 67 100 0% NA NA NA
Genito-Urinary System 1% 76 ± 10 64 100 1% 86 ± 18 42 100
Hemic and Lympahtic System <1% 67 ± 0 67 NA 0% NA NA NA
Neoplastic Diseases--Malignant <1% 100 ± 0 100 NA <1% 86 ± 0 86 NA
Immune System 2% 87 ± 13 71 100 <1% 87 ± 0 87 NA
Growth Impairment 2% 96 ± 07 85 100 0% NA NA NA
* Includes Down Syndrome, multiple body dysfunction, and catastrophic congenital anomalies
** Includes mental retardation


TABLE 6. Direct and Other Direct Expenses for the Month and Year in Dollars
Category Children Receiving Medicaid Commercially Insured Children
% Reporting Expense Mean Min. Max. % Reporting Expense Mean Min. Max.
Direct Expenses Per Month
Direct Expenses Per Year
37%
 
38%
131.89 ± 392.25
 
1072 ± 14629.1
0
 
0
3050
 
5780
87%
 
86%
28.59 ± 139.2
 
384.11 ± 1582
0
 
3.00
2562
 
6200
Other Direct Expenses Per Month
Other Direct Expenses Per Year
89%
 
89%
162.57 ± 305.93
 
1444.1 ± 1779.2
0
 
0
3077
 
9680
63%
 
63%
30.79 ± 69.8
 
689.4 ± 2502.6
0
 
1.00
660
 
2890


TABLE 7. Direct and Other Direct Expenses for the Month and Year Expressed as a Percent of Family Income
Category Children Receiving Medicaid Commercially Insured Children
% Reporting Expense Mean Min. Max. % Reporting Expense Mean Min Max.
Direct Expenses Per Month
Direct Expenses Per Year
37%
 
36%
4.87 ± 32.4
 
4.33 ± 12.2
0
 
0
698.0
 
128.95
87%
 
87%
2.32 ± 10.38
 
2.8 ± 12.78
0
 
.10
146.4
 
1698.7
Other Direct Expenses Per Month
Other Direct Expenses Per Year
89%
 
88%
12.79 ± 21.9
 
11.25 ± 25.6
0
 
0
129.8
 
487.0
63%
 
63%
2.11 ± 6.2
 
2.25 ± 10.98
0
 
.04
72.0
 
1587.6


TABLE 8. Specific Expenses in Dollars for Children in Medicaid and Commercially Insured
Category Children Receiving Medicaid Commercially Insured Children
Percent Incurring Expense Cost/Month in Dollars Mean and Standard Deviation Percent Incurring Expense Cost/Month in Dollars Mean and Standard Deviation
Physical Therapy 1% 70.0 ± 98.9 <1% 175 ± 168.5
Occupational Therapy 1% 71.0 ± 97.6 0% 0
Speech Therapy 1% 50.1 ± 86.5 <1% 15.0 ± 21.2
Skilled Nursing 0% 0 <1% 600 ± 848.6
Personal Attendant <1% 400.0 ± 0 <1% 85 ± 0
Respiratory Therapy and Supplies 1% 45.0 ± 35.3 9% 7.5 ± 26.4
Day Care 2% 147.25 ± 97.2 <1% 50.0 ± 70.7
Counseling 3% 25.2 ± 21.7 22% 7.8 ± 13.7
Doctors Visits 11% 82.1 ± 123.78 88% 8.5 ± 27.6
Hospital 4% 500.0 ± 1,110.0 9% 16.5 ± 80
Respite Care 11% 85.7 ± 226.8 2% 59.3 ± 119.2
Medications 24% 31.0 ± 52.7 90% 10.3 ± 31.5
Special Diet 14% 110.5 ± 98.7 6% 94.0 ± 132.6
Medical Supplies 17% 24.6 ± 32.7 11% 6.5 ± 10.7
Special Clothing 18% 62.8 ± 54.1 5% 30.1 ± 31.5
Home Medical Equipment 7% 31.4 ± 60.9 7% 16.9 ± 54.9
Diapers 38% 61.8 ± 66.3 3% 31.33 ± 45.7
Assistive Technologies 3% 339.1 ± 328.2 0% 0
Educational Services 2% 37.1 ± 38.9 2% 21.6 ± 41.8
Additional Phone Charges 24% 20.0 ± 25.1 10% 13.4 ± 24.0
Additional Utility Bills 13% 56.4 ± 58.7 11% 45.8 ± 48.9
Higher Health Insurance Premiums 1% 167.6 ± 143.0 2% 21.5 ± 27.7
Additional Health Insurance 1% 237.6 ± 217.2 <1% 16.6 ± 28.7
Transportation to Doctor 31% 41.4 ± 63.9 58% 7.5 ± 15.2
Emergency Transportation 0% 0 0% 0
Home Modifications 7% 52.1 ± 103.6 5% 23.6 ± 65.2


APPENDIX A. ICD-9-CM CODES USED TO IDENTIFY CHILDREN FROM THE CLAIMS/ENCOUNTER DATA

Code Condition
042 Human Immunodeficiency Virus (HIV)/AIDS
  • (Use additional codes to identify all manifestations of HIV)
142
  • 142.0
  • 142.1
  • 142.2
  • 142.8
  • 142.9
  • 147.0
  • 147.1
  • 147.2
  • 147.3
  • 147.8
  • 147.9
Malignant Neoplasm of Major Salivary Glands
  • Parotid gland
  • Submandibular gland
  • Sublingual gland
  • Other major salivary glands
  • Salivary gland, unspecified
  • Superior wall
  • Posterior wall
  • Lateral wall
  • Anterior wall
  • Other specified sites of nasopharynx
  • Nasopharynx, unspecified
155
  • 155.0
  • 155.1
  • 155.2
Malignant Neoplasm of Liver and Intrahepatic Bile Ducts
  • Liver, primary
  • Intrahepatic bile ducks
  • Liver, not specified as primary or secondary
158
  • 158.0
  • 158.8
  • 158.9
Malignant Neoplasm of Retroperitoneum and Peritoneum
  • Retroperitoneum
  • Specified parts of peritoneum
  • Peritoneum, unspecified
170
  • 170.0
  • 170.1
  • 170.2
  • 170.3
  • 170.4
  • 170.5
  • 170.6
  • 170.7
  • 170.8
  • 170.9
Malignant Neoplasm of Bone and Articular Cartilage
  • Bones of skull and face, except mandible
  • Mandible
  • Vertebral column, excluding sacrum and caccyx
  • Ribs, sternum, and clavicle
  • Scapula and long bones of upper limb
  • Short bones of upper limb
  • Pelvic bones, sacrum, and coccyx
  • Long bones of lower limb
  • Short bones of lower limb
  • Bone and articular cartilage, site unspecific
171
  • 171.0
  • 171.2
  • 171.3
  • 171.4
  • 171.5
  • 171.6
  • 171.7
  • 171.8
  • 171.9
Malignant Neoplasm of Connective and Other Soft Tissue
  • Head, face, and neck
  • Upper limb, including shoulder
  • Lower limb, including hip
  • Thorax
  • Abdomen
  • Pelvis
  • Trunk, unspecified
  • Other specific sties of connective and other soft tissue
  • Connective and other soft tissue, site unspecified
189
  • 189.0
  • 189.1
  • 189.9
Maligant Neoplasm of Kidney and other Unspecified Urinary Organs
  • Kidney, except pelvis
  • Renal pelvis
  • Urinary organ, site unspecified
190
  • 190.0
  • 190.5
  • 191.0
  • 191.1
  • 191.2
  • 191.3
  • 191.4
  • 191.5
  • 191.6
  • 191.7
  • 191.8
  • 191.9
Malignant Neoplasm of Eye
  • Eyeball, except conjunctiva, cornea, retina, and choriod
  • Retina
  • Cerebrum, except lobes and ventricles
  • Frontal lobe
  • Temporal lobe
  • Parietal lobe
  • Occipital lobe
  • Ventricles
  • Cerebellum NOS
  • Brain stem
  • Other parts of brain
  • Brain, unspecified
192
  • 192.0
  • 192.1
  • 192.2
  • 192.3
  • 192.8
  • 192.9
Malignant Neoplasm of Other Unspecified Parts of Nervous
  • Cranial nerves
  • Cerebral meninges
  • Spinal cord
  • Spinal meninges
  • Other specified sites of nervous system
  • Nervous system, part unspecified
196
  • 196.0
  • 196.1
  • 196.2
  • 196.3
  • 196.5
  • 196.6
  • 196.8
  • 196.9
Secondary and Unspecified Malignant Neoplasm of Lymph Nodes
  • Lymph nodes of head, face, and neck
  • Intrathoracic lymph nodes
  • Intra-abdominal lymph nodes
  • Lymph nodes of axilla and upper limb
  • Lymph nodes of inguinal region and lower limb
  • Intrapelvic lymph nodes
  • Lymph nodes of multiple sides
  • Site unspecific
197
  • 197.0
  • 197.1
  • 197.2
  • 197.3
  • 197.4
  • 197.5
  • 197.6
  • 197.7
  • 197.8
Secondary Maligant Neoplasm of Respiratory and Digestive System
  • Lung
  • Mediastium
  • Pleura
  • Other respiratory organs
  • Small intestine, including duodenum
  • Large intestine and rectum
  • Retroperitoneum and peritoneum
  • Liver, specified as secondary
  • Other digestive organs and spleen
200
  • 200.0
  • 200.1
  • 200.2
  • 200.8
Lymphosarcoma and Reticulosarcoma
  • Reticulosarcoma
  • Lymphosarcoma
  • Burkitt's tumor or lymphoma
  • Other named variants
201
  • 201.0
  • 201.1
  • 201.2
  • 201.4
  • 201.5
  • 201.6
  • 201.7
  • 201.9
Hodgkin's Disease
  • Hodgkin's paragranuloma
  • Hodgkin's granuloma
  • Hodgkin's sarcoma
  • Lymphocytic-histiosytic predominance
  • Nodular sclerosis
  • Mixed cellularity
  • Lymphocytic depletion
  • Hodgkin's disease, unspecified
202
  • 202.3
  • 202.4
  • 202.5
  • 202.8
  • 202.9
Other Malignant Neoplasms of Lymphoid and Histiocytic Tissue
  • Malignant histiocytosis
  • Leukemic reticuloendotheliosis
  • Letter-Siwe disease
  • Other lymphomas
  • Other and unspecified malignant neoplasms of lymphoid and histiocytic tissue
204
  • 204.0
  • 204.1
  • 204.8
Lymphoid Leukemia
  • Acute
  • Chronic
  • Other lymphoid leukemia
205
  • 205.0
  • 205.1
  • 205.2
  • 205.3
  • 205.8
  • 205.9
Myeloid Leukemia
  • Acute
  • Chronic
  • Subacute
  • Myeloid sarcoma
  • Other myeloid leukemia
  • Unspecified myeloid laukemia
206
  • 206.0
  • 206.1
  • 206.2
  • 206.8
  • 206.9
Monocytic Leukemia
  • Acute
  • Chronic
  • Subacute
  • Other monocytic leukemia
  • Unspecified monocytic leukemia
207
  • 207.0
  • 207.1
  • 207.2
  • 207.8
Other Specified Leukemia
  • Acute erythremia and erythroleukemia
  • Chronic erythremia
  • Megakaryocytic leukemia
  • Other specified leukemia
208
  • 208.0
  • 208.1
  • 208.2
  • 208.8
  • 208.9
Leukemia of Unspecified Cell Type
  • Acute
  • Chronic
  • Subacute
  • Other leukemia of unspecified cell type
  • Unspecified leukemia
210
  • 210.0
  • 210.1
  • 210.2
  • 210.4
  • 210.5
  • 210.6
  • 210.7
  • 210.8
  • 210.9
Benign Neoplasm of Lip, Oral Cavity, and Pharynx
  • Lip
  • Tongue
  • Major salivary glands
  • Other and unspecified parts of the mouth
  • Tonsil
  • Other parts of oropharynx
  • Nasopharynx
  • Hypopharynx
  • Pharynx, unspecified
213
  • 213.7
Benign Neoplasm of Bone and Articular Cartilage
  • Long bone of lower limb
215 Other Benign Neoplasm of Connective and Other Soft Tissue
216 Benign Neoplasm of Skin
225
  • 225.0
Benign Neoplasm of Brain and Other Parts of Nervous System
  • Brain
228
  • 228.0
  • 228.00
  • 228.01
  • 228.02
  • 228.03
  • 228.04
  • 228.09
  • 228.1
Hemangioma and Lymphangioma, any site
  • Hemangioma, any site
  • Of unspecified site
  • Of skin and subcutaneous tissue
  • Of intracranial structures
  • Of retina
  • Of intra-abdominal structures
  • Of other sites
  • Lymphangioma, any site
229
  • 229.0
  • 229.8
  • 229.9
Benign Neoplasm of Other and Unspecified Sites
  • Lymph nodes
  • Other specified sites
  • Site unspecified
237
  • 237.70
  • 237.71
  • 237.72
Neoplasm of Uncertain Behavior of Endocrine Glands and Nervous System
  • Neurofibromatosis, unspecified
  • Neurofibromatosis, Type I [von Recklinghousen's disease]
  • Neurofibromatosis, Type II [acoustic neurofibromatosis]
250
  • 250.0
  • 250.1
  • 250.2
  • 250.3
  • 250.4
  • 250.5
Diabetes Mellitos, Type I [insulin dependent type] [IDDM] [ juvenile type], uncontrolled
  • Diabetes mellitus without mention of complication
  • Diabetes with ketoacidosis
  • Diabetes with hyperosmolarity
  • Diabetes with other coma
  • Diabetes with renal manifestations
  • Diabetes with ophthalmic manifestations
277
  • 277.0
  • 277.00
  • 277.01
Other and Unspecified Disorders of Metabolism
  • Cystic fibrosis
  • Without mention of meconium ileus
  • With meconium ileus
282
  • 282.60
  • 282.61
  • 282.62
  • 282.63
  • 282.69
Hereditary Hemolytic Anemias
  • Sickle-cell anemia, unspecified
  • Hb-S disease without mention of crisis
  • Hb-S disease with mention of crisis
  • Sickle-cell/Hb-C disease
  • Other
292
  • 292.0
  • 292.11
  • 292.12
  • 292.2
Drug Psychoses
  • Drug withdrawal syndrome
  • Drug-induced organic delusional syndrome
  • Drug-induced hallucinosis
  • Pathological drug intoxication
293
  • 293.0
  • 293.1
  • 293.8
  • 293.81
  • 293.82
  • 293.83
  • 293.89
  • 293.9
Transient Organic Psychotic Conditions
  • Acute delirium
  • Subacute delirium
  • Other specified transient organic mental disorders
  • Organic delusional syndrome
  • Organic hallucinosis syndrome
  • Organic affective syndrome
  • Other
  • Unspecified transient organic mental disorder
294
  • 294.1
Other Organic Psychotic Conditions (Chronic)
  • Dementia in conditions classified elsewhere
295
  • 295.1
  • 295.2
  • 295.3
  • 295.4
  • 295.5
  • 295.6
  • 295.7
  • 295.8
  • 295.9
Schizophrenic Disorders [0=unspecified] [1=subchronic] [2=chronic] [3=subchronic with acute exacerbation]
  • [4=chronic with acute exacerbation] [5=in remission]
  • Disorganized type
  • Catatonic type
  • Paranoid type
  • Acute schizophrenic episode
  • Latent schizophrenia
  • Residual schizophrenia
  • Schizo-affective type
  • Other specified types of schizophrenia
  • Unspecified schizophrenia
296
  • 296.2
  • 296.3
  • 296.9
Affective Psychoses
  • Major depressive disorder, single episode
  • Major depressive disorder, recurrent episode
  • Other and unspecified affective psychosis
299
  • 299.0
  • 299.1
  • 299.8
  • 299.9
Psychoses with Origin Specific to Childhood
  • Infantile autism
  • Disintegrative psychosis
  • Other specified early childhood psychoses
  • Unspecified
300
  • 300.0
  • 300.00
  • 300.01
  • 300.02
  • 300.09
  • 300.10
  • 300.11
  • 300.12
  • 300.13
  • 300.16
  • 300.19
  • 300.20
  • 300.3
  • 300.4
  • 300.5
  • 300.7
  • 300.8
  • 300.81
  • 300.9
Neurotic Diseases
  • Anxiety states
  • Anxiety states, unspecified
  • Panic disorder
  • Generalized anxiety disorder
  • Other
  • Hysteria, unspecified
  • Conversion disorder
  • Psychogenic amnesia
  • Psychogenic fugue
  • Factitious illness with psychological symptoms
  • Other and unspecified factitious illness
  • Phobia, unspecified
  • Obsessive-compulsive disorder
  • Neurotic depression
  • Neurasthenia
  • Hypochondriasis
  • Other neurotic disorders
  • Somatization disorder
  • Unspecified neurotic disorder
301
  • 301.10
  • 301.20
  • 301.50
  • 301.51
  • 301.59
  • 301.7
Personality Disorders
  • Affective personality disorder, unspecified
  • Schizoid personality disorder, unspecified
  • Histrionic personality disorder, unspecified
  • Chronic factitious illness with physical symptoms
  • Other histrionic personality disorder
  • Antisocial personality disorder
302
  • 302.3
  • 302.50
  • 302.51
  • 302.52
  • 302.53
  • 302.6
  • 302.85
Sexual Deviations and Disorders
  • Transvestitism
  • With unspecified sexual history
  • With asexual history
  • With homosexual history
  • With heterosexual history
  • Disorders of psychosexual identity
  • Gender identify disorder of adolescent or adult life
306
  • 306.0
  • 306.3
  • 306.4
Physiological Malfunction Arising from Mental Factors
  • Musculoskeletal
  • Skin
  • Gastrointestinal
307
  • 307.0
  • 307.1
  • 307.2
  • 307.20
  • 307.21
  • 307.22
  • 307.23
  • 307.3
  • 307.40
  • 307.41
  • 307.42
  • 307.43
  • 307.46
  • 307.47
  • 307.50
  • 307.51
  • 307.52
  • 307.53
  • 307.54
  • 307.59
  • 307.6
  • 307.7
  • 307.80
  • 307.81
  • 307.9
Special Symptoms or syndromes, Not Elsewhere Classified
  • Stammering and stuttering
  • Anorexia nervosa
  • Tics
  • Tic disorder, unspecified
  • Transient tic disorder of childhood
  • Chronic motor tic disorder
  • Gilles de la Tourette's disorder
  • Stereotyped repetitive movements
  • Nonorganic sleep disorder, unspecified
  • Transient disorder of initiating or maintaining sleep
  • Persistent disorder of initiating or maintaining sleep
  • Transient disorder of initiating or maintaining sleep
  • Somnambulism or night terros
  • Other dysfunction's of sleep stages or arousal from sleep
  • Eating disorder, unspecified
  • Bulimia
  • Pica
  • Psychogenic rumination
  • Psychogenic vomiting
  • Other
  • Enuresis
  • Encopresis
  • Psychogenic pain, site unspecified
  • Tension headache
  • Other and unspecified special symptoms or syndromes, not elsewhere classified
308
  • 308.0
  • 308.1
  • 308.2
  • 308.3
  • 308.4
  • 308.9
Acute Reaction to Stress
  • Predominant disturbance of emotions
  • Predominant disturbance of consciousness
  • Predominant psychomotor disturbance
  • Other acute reactions to stress
  • Mixed disorders as reaction to stress
  • Unspecified acute reaction to stress
309
  • 309.0
  • 309.1
  • 309.21
  • 309.22
  • 309.23
  • 309.24
  • 309.28
  • 309.3
  • 309.4
  • 309.82
  • 309.83
  • 309.89
  • 309.9
Adjustment Reaction
  • Brief depressive reaction
  • Prolonged depressive reaction
  • Separation anxiety disorder
  • Emancipation disorder of adolescence and early adult life
  • Specific academic or work inhibition
  • Adjustment reaction with anxious mood
  • Adjustment reaction with mixed emotional features
  • With predominant disturbance of conduct
  • With mixed disturbance of emotions and conduct
  • Adjustment reaction with physical symptoms
  • Adjustment reaction with withdrawal
  • Other
  • Unspecified adjustment reaction
310
  • 310.2
  • 310.8
Specific Nonpsychotic Mental Disorders Due to Organic Brain Damage
  • Postconcussion syndrome
  • Other specified nonpsychotic mental disorders following organic brain damage
312
  • 312.0
  • 312.1
  • 312.2
  • 312.30
  • 312.31
  • 312.32
  • 312.33
  • 312.34
  • 312.35
  • 312.39
  • 312.4
  • 312.8
  • 312.81
  • 312.82
  • 312.89
  • 312.9
Disturbance of Conduct, Not Elsewhere Classified
  • Undersocialized conduct disorder, aggressive type
  • Undersocialized conduct disorder, unaggressive type
  • Socialized conduct disorder
  • Impulse control disorder, unspecified
  • Pathological gambling
  • Kleptomania
  • Pyromania
  • Intermittent explosive disorder
  • Isolated explosive disorder
  • Other
  • Mixed disturbance of conduct and emotions
  • Other specified disturbances of conduct, not elsewhere classified
  • Conduct disorder, childhood onset type
  • Conduct disorder, adolescent onset type
  • Other conduct disorder
  • Unspecified disturbance of conduct
313
  • 313.0
  • 313.1
  • 313.2
  • 313.3
  • 313.81
  • 313.82
  • 313.83
  • 313.89
Disturbance of Emotions Specific to Childhood and Adolescence
  • Overanxious disorder
  • Misery and unhappiness disorder
  • Sensitivity, shyness, and social withdrawal disorder
  • Relationship problems
  • Oppositional disorder
  • Identity disorder
  • Academic underachievement disorder
  • Other
314
  • 314.00
  • 314.01
  • 314.1
  • 314.2
  • 314.8
  • 314.9
Hyperkinetc Syndrome of Childhood
  • Without mention of hyperactivity
  • With hyperactivity
  • Hyperkinesis with developmental delay
  • Hyperdinetic conduct disorder
  • Other specified manifestations of hyperkinetc syndrome
  • Unspecified hyperkinetic syndrome
315
  • 315.0
  • 315.00
  • 315.01
  • 315.02
  • 315.09
  • 315.1
  • 315.2
  • 315.3
  • 315.31
  • 315.39
  • 315.4
  • 315.5
  • 315.8
  • 315.9
Specific Delays in Development
  • Specific reading disorder
  • Reading disorder, unspecified
  • Alexia
  • Developmental dyslexia
  • Other
  • Specific arithmetical disorder
  • Other specific learning difficulties
  • Developmental speech or language disorder
  • Developmental language disorder
  • Other
  • Coordination disorder
  • Mixed development disorder
  • Other specified delays in development
  • Unspecified delay in development
316 Psychic Factors Associated with Diseases Classified Elsewhere
317 Mild Mental Retardation
318
  • 318.0
  • 318.1
  • 318.2
Other Specified Mental Retardation
  • Moderate mental retardation
  • Severe mental retardation
  • Profound mental retardation
319 Unspecified mental retardation
330
  • 330.0
  • 330.1
  • 330.2
  • 330.8
  • 330.9
Cerebral Degenerations Usually Manifest in Childhood
  • Leukodystrophy
  • Cerebral lipidoses
  • Cerebral degeneration in generalized lipidoses
  • Other specified cerebral degenerations in childhood
  • Unspecified cerebral degenerations in childhood
331
  • 331.1
  • 331.3
  • 331.4
Other Cerebral Degenerations
  • Pick's disease
  • Communicating hydrocephalus
  • Obstructive hydrocephalus
343
  • 343.0
  • 343.1
  • 343.2
  • 343.3
  • 343.4
  • 343.8
  • 343.8
  • 343.9
Infantile Cerebral Palsy
  • Diplegic
  • Hemiplegic
  • Quadriplegic
  • Monoplegic
  • Infantile hemiplegia
  • Other specified cerebral palsy
  • Other specified infantile cerebral palsy
  • Infantile cerebral palsy, unspecified
344
  • 344.0
  • 344.00
  • 344.01
  • 344.02
  • 344.03
  • 344.04
  • 344.09
  • 344.1
  • 344.2
  • 344.3
  • 344.30
  • 344.31
  • 344.32
  • 344.4
  • 344.40
  • 344.41
  • 344.42
  • 344.5
  • 344.6
  • 344.60
  • 344.61
  • 344.8
  • 344.81
  • 344.89
Other Paralytic Syndromes
  • Quadriplegia and quadriparesis
  • Quadriplegia, unspecified
  • C1-C4, complete
  • C1-C4, incomplete
  • C5-C7, complete
  • C5-C7, incomplete
  • Other
  • Paraplegia
  • Diplegia of upper limbs
  • Monoplegia of lower limb
  • Affecting unspecified side
  • Affecting dominant side
  • Affecting nondominant side
  • Monoplegia or upper limb
  • Affecting unspecified side
  • Affecting dominant side
  • Affecting nondominant side
  • Unspecified monoplegia
  • Cauda equina syndrome
  • Without mention of neurogenic bladder
  • With neurogenic bladder
  • Other specified paralytic syndromes
  • Locked-in state
  • Other specified paralytic syndrome
345
  • 345.0
  • 345.1
  • 345.2
  • 345.3
  • 345.4
  • 345.5
  • 345.6
  • 345.8
  • 345.9
Epilepsy
  • Generalized nonconvulsive epilepsy
  • Generalized convulsive epilepsy
  • Petit mal status
  • Grand mal status
  • Partial epilepsy, with impairment of consciousness
  • Partial epilepsy, without mention of impairment of consciousness
  • Infantile spasms
  • Other forms of epilepsy
  • Epilepsy, unspecified
369
  • 369.00
  • 369.10
  • 369.3
  • 369.4
  • 369.60
  • 369.61
  • 369.70
Blindness and Low Vision
  • Impairment level not further specified
  • Impairment level not further specified
  • Unqualified visual loss, both eyes
  • Legal blindness, as defined in U.S.A.
  • Impairment level not further specified
  • One eye: total impairment; other eye: not specified
  • Impairment level not further specified
370
  • 370.0
  • 370.00
Keratitis
  • Corneal ulcer
  • Corneal ulcer, unspecified
389
  • 389.00
  • 389.01
  • 389.02
  • 389.03
  • 389.04
  • 389.08
  • 389.1
  • 389.10
  • 389.11
  • 389.12
  • 389.14
  • 389.18
  • 389.2
  • 389.7
  • 389.8
  • 389.9
Hearing Loss
  • Conductive hearing loss
  • Conductive hearing loss, external ear
  • Conductive hearing loss, tympanic membrane
  • Conductive hearing loss, middle ear
  • Conductive hearing loss, inner ear
  • Conductive hearing loss of combined types
  • Sensorineural hearing loss
  • Sensorineural hearing loss, unspecified
  • Sensory hearing loss
  • Neural hearing loss
  • Central hearing loss
  • Sensorineural hearing loss of combined types
  • Mixed conductive and Sensorineural hearing loss
  • Deaf mutism, not elsewhere classifiable
  • Other specified forms of hearing loss
  • Unspecified hearing loss
394
  • 394.0
  • 394.1
  • 394.2
  • 394.9
Diseases of Mitral Valve
  • Mitral stenosis
  • Rheumatic mitral insufficiency
  • Mitral stenosis with insufficiency
  • Other and unspecified mitral valve diseases
395
  • 395.0
  • 395.1
  • 395.2
  • 395.9
Diseases of Aortic Valve
  • Rheumatic aortic stenosis
  • Rheumatic aortic insufficiency
  • Rheumatic aortic stenosis with insufficiency
  • Other and unspecified rheumatic aortic diseases
396
  • 396.0
  • 396.1
  • 396.2
  • 396.3
  • 396.8
  • 396.9
Diseases of Vitral and Aortic Valves
  • Mitral valve stenosis and aortic valve stenosis
  • Mitral valve stenosis and aortic valve insufficiency
  • Mitral valve insufficiency and aortic valve stenosis
  • Mitral valve insufficiency and aortic valve insufficiency
  • Multiple involvement of mitral and aortic valves
  • Mitral and aortic valve diseases, unspecified
493
  • 493.0
  • 493.1
  • 493.2
  • 493.9
Asthma
  • Extrinsci asthma
  • Intrinsic asthma
  • Chronic obstructive asthma
  • Asthma, unspecified
494 Bronchiectasis
580 Acute Glomerulonephritis
581
  • 581.0
  • 581.1
  • 581.2
  • 581.3
  • 581.81
  • 581.89
  • 581.9
Nephrotic Syndrome
  • With lesion of proliferative glomerulonephritis
  • With lesion of membranous glomerulonephritis
  • With lesion of membranoproliferative glomerulonephritis
  • With lesion of minimal change glomerulonephritis
  • Nephrotic syndrome in diseases classified elsewhere
  • Other
  • Nephrotic syndrome with unspecified pathological lesion in kidney
584
  • 584.5
  • 584.6
  • 584.7
  • 584.8
  • 584.9
Acute Renal Failure
  • With lesion of tubular necrosis
  • With lesion of renal cortical necrosis
  • With lesion of renal medullary (papillary) necrosis
  • With other specified pathological lesion in kidney
  • Acute renal failure, unspecified
585 Chronic Renal Failure
586 Renal Failure, Unspecified
587 Renal Sclerosis, Unspecified
588
  • 588.0
  • 588.1
  • 588.8
  • 588.9
Disorders Resulting From Impaired Renal Function
  • Renal osteodystrophy
  • Nephrogenic diabetes insipidus
  • Other specified disorders resulting from impaired renal function
  • Unspecified disorder resulting from impaired renal function
589
  • 589.0
  • 589.1
  • 589.9
Small Kidney of Unknown Cause
  • Unilateral small kidney
  • Bilateral small kidneys
  • Small kidney, unspecified
714
  • 714.3
  • 714.30
  • 714.31
  • 714.32
  • 714.33
Rheumatoid Arthritis and Other Inflammatory Polyarthropathies
  • Juvenile chronic polyarthritis
  • Polyarticular juvenile rheumatoid arthritis, chronic or unspecified
  • Polyarticular juvenile rheumatoid arthritis, acute
  • Pauciarticular juvenile rheumatoid arthritis
  • Monoarticular juvenile rheumatoid arthritis
741
  • 741.0
  • 741.9
  • 742.0
  • 742.1
  • 742.2
  • 742.3
Spina Bifida
  • With hydrocephalus
  • Without mention of hydrocephalus
  • Encephalocele
  • Microcephalus
  • Reduction deformities of brain
  • Congenital hydrocephalus
744
  • 744.5
  • 744.83
  • 744.84
  • 744.9
Congenital Anomalies of Ear, Face, and Neck
  • Webbing of neck
  • Macrostomia
  • Microstomia
  • Unspecified anomalies of face and neck
745
  • 745.0
  • 745.1
  • 745.12
  • 745.19
  • 745.2
  • 745.3
  • 745.4
  • 745.5
  • 745.6
  • 745.60
  • 745.61
  • 745.69
  • 745.7
  • 745.8
  • 745.9
Bulbus Cordis Anomalies and Anomalies of Cardiac Septal Closure
  • Common truncus
  • Transposition of great vessels
  • Carrected transportation of great vessels
  • Other
  • Tetralogy of fallot
  • Common ventricle
  • Ventricular septal defect
  • Ostium secundum type atrial septal defect
  • Endocardial cushion defects
  • Endocardial cushion defect, unspecified type
  • Ostium primum defect
  • Other (absence of atrial septum, atrioventricular canal type ventricular septal defect, common atriventricular canal, common atrium)
  • Cor biolculare
  • Other
  • Unspecified defect of septal closure
746
  • 746.0
  • 746.00
  • 746.01
  • 746.02
  • 746.09
  • 746.1
  • 746.2
  • 746.3
  • 746.4
  • 746.5
  • 746.6
  • 746.7
  • 746.8
  • 746.81
  • 746.82
  • 746.83
  • 746.84
  • 746.85
  • 746.86
  • 746.87
  • 746.89
  • 746.9
Other Congenital Anomalies of Heart
  • Anomalies of pulmonary valve
  • Pulmonary valve anomly, unspecified
  • Atresia, congenital
  • Stenosis, congenital
  • Other
  • Tricuspid atresia and stenosis, congenital
  • Ebstein's anomaly
  • Congenital stenosis of aortic valve
  • Congenital insufficiency of aortic valve
  • Congenital mitral stenosis
  • Congenital mitral insufficiency
  • Hypoplastic left heart syndrome
  • Other specified anomalies of heart
  • Subaortic stenosis
  • Cor triatriatum
  • Infundibular pulmonic stenosis
  • Obstructive anomalies of heart, not elsewhere classified
  • Coronary artery anomaly
  • Congenital heart block
  • Malposition of heart and cardiac apex
  • Other
  • Unspecified anomaly of heart
747
  • 747.0
  • 747.1
  • 747.2
  • 747.20
  • 747.21
  • 747.22
  • 747.29
  • 747.3
  • 747.4
  • 747.40
  • 747.41
  • 747.42
  • 747.49
  • 747.5
  • 747.6
  • 747.60
  • 747.81
Other Congenital Anomalies of Circulatory System
  • Patent ductus arteriosus
  • Coarctation of aorta
  • Other anomalies of aorta
  • Anomaly of aorta, unspecified
  • Anomalies of aortic arch
  • Atresia and stenosis of aorta
  • Other
  • Anomalies of pulmonary artery
  • Anomalies of great veins
  • Anomaly of great veins, unspecified
  • Total anomalous pulmonary venous connection
  • Partial anomalous pulmonary venous connection
  • Other anomalies of great veins
  • Absence or hypoplasia of umbilical artery
  • Other anomalies of peripheral vascular system
  • Anomaly of the peripheral vascular system, unspecified site
  • Anomalies of cerebrovascular system
748
  • 748.0
Congenital Anomalies of Respiratory System
  • Choanal atresia
749
  • 749.00
  • 749.01
  • 749.02
  • 749.03
  • 749.04
  • 749.1
  • 749.10
  • 749.11
  • 749.12
  • 749.13
  • 749.14
  • 749.20
  • 749.21
  • 749.22
  • 749.23
  • 749.24
  • 749.25
Cleft Palate and Cleft Lip
  • Cleft palate, unspecified
  • Unilateral, complete
  • Unilateral, incomplete
  • Bilateral, complete
  • Bilateral, incomplete
  • Cleft lip
  • Cleft lip, unspecified
  • Unilateral, complete
  • Unilateral, incomplete
  • Bilateral, complete
  • Bilateral, incomplete
  • Cleft palate with cleft lip, unspecified
  • Unilateral, complete
  • Unilateral, incomplete
  • Bilateral, complete
  • Bilateral, incomplete
  • Other combinations
750
  • 750.4
  • 750.5
Other Congenital Anomalies of Upper Alimentary Tract
  • Other specified anomalies of esophagus
  • Congenital hypertrophic pyloric stenosis
751
  • 751.0
  • 751.1
  • 751.2
  • 751.3
  • 751.4
  • 751.5
  • 751.6
  • 751.60
  • 751.61
  • 751.62
  • 751.69
  • 751.7
  • 751.8
Other Congenital Anomalies of Stomach
  • Meckel's diverticulum
  • Atresia and stenosis of small intestine
  • Atresia and stenosis of large intestine, rectum, and anal canal
  • Hirschsprung's disease and other congenital functional disorders of colon
  • Anomalies of intestinal fixation
  • Other anomalies of intestine
  • Anomalies of gallbladder, bile ducts, and liver
  • Unspecified anomaly of gallbladder, bile ducts, and liver
  • Biliary atresia
  • Congenital cystic disease of liver
  • Other anomalies of gallbladder, bile ducts, and liver
  • Anomalies of pancreas
  • Other specified anomalies of digestive system
754
  • 754.11
Certain Congenital Musculoskeletal Deformities
  • Double outlet right ventricle
758
  • 758.0
  • 758.1
  • 758.2
  • 758.3
  • 758.4
  • 758.6
  • 758.7
  • 758.8
  • 758.9
Chromosomal Anomalies
  • Down's syndrome
  • Patau's syndrome
  • Edwards's syndrome
  • Autosomal deletion syndomes
  • Balanced autosomal translocation in normal individual
  • Gonadal dysgenesis
  • Klinefelter's syndrome
  • Other conditions due to sex chromosome anomalies
  • Conditions due to anomaly of unspecified chromosome
765
  • 765.0
  • 765.1
Disorders Relating to Short Gestation and Unspecified Low Birth Weight
  • Extreme immaturity
  • Other preterm infants
766
  • 766.0
  • 766.1
  • 766.2
Disorders Relating to Long Gestation and High Birth Weight
  • Exceptionally large baby
  • Other "heavy-for-dates" infants
  • Post-term infant, not "heavy-for-dates"
770
  • 770.0
  • 770.1
  • 770.2
  • 770.3
  • 770.4
  • 770.5
  • 770.6
  • 770.7
  • 770.8
  • 770.9
Other Respiratory Conditions of Fetus and Newborn
  • Congenital pneumonia
  • Meconium aspiration syndrome
  • Interstitial emphysema and related conditions
  • Pulmonary hemorrhage
  • Primary atelectasis
  • Other and unspecified atelectasis
  • Transitory tachypnea of newborn
  • Chronic respiratory disease arising in the perinatal period
  • Other respiratory problems after birth
  • Unspecified respiratory condition of fetus and newborn
771
  • 771.0
  • 771.1
  • 771.2
Infectious Specific to the Perinatal Period
  • Congenital rebella
  • Congenital cytomegalovirus infection
  • Other congenital infections
800
  • 800.0
  • 800.1
  • 800.2
  • 800.3
  • 800.4
  • 800.5
  • 800.6
  • 800.7
  • 800.8
  • 800.9
Fracture of Vault of Skull
  • Closed without mention of intracranial injury
  • Closed with cerebral laceration and contusion
  • Closed with subarachnoid, subdural, and extradural hemorrhage
  • Closed with other and unspecified intracranial hemorrhage
  • Closed with intracranial injury of other and unspecified nature
  • Open without mention of intracranial injury
  • Open with cerebral laceration and contusion
  • Open with subarachnoid, subdural, and extradural hemorrhage
  • Open with other and unspecified intracranial hemorrhage
  • Open with intracranial injury of other and unspecified nature
801
  • 801.0
  • 801.1
  • 801.2
  • 801.3
  • 801.4
  • 801.5
  • 801.6
  • 801.7
  • 801.8
  • 801.9
Fracture of Base of Skull
  • Closed without mention of intracranial injury
  • Closed with cerebral laceration and contusion
  • Closed with subarachnoid, subdural, and extradural hemorrhage
  • Closed with other and unspecified intracranial hemorrhage
  • Closed with intracranial injury of other and unspecified nature
  • Open without mention of intracranial injury
  • Open with cerebral laceration and contusion
  • Open with subarachnoid, subdural, and extradural hemorrhage
  • Open with other and unspecified intracranial hemorrhage
  • Open with intracranial injury of other and unspecified nature
802
  • 802.0
  • 802.1
  • 802.2
  • 802.20
  • 802.21
  • 802.22
  • 802.23
  • 802.24
  • 802.25
  • 802.26
  • 802.27
  • 802.28
  • 802.29
  • 802.3
  • 802.30
  • 802.31
  • 802.32
  • 802.33
  • 802.34
  • 802.35
  • 802.36
  • 802.37
  • 802.38
  • 802.39
  • 802.4
  • 802.5
  • 802.6
  • 802.7
Fracture of Face Bones
  • Nasal bones, closed
  • Nasal bones, open
  • Mandible, closed
  • Unspecified site
  • Condylar process
  • Subcondylar
  • Coronoid process
  • Ramus, unspecified
  • Angle of jaw
  • Symphysis of body
  • Alveolar border of body
  • Body, other and unspecified
  • Multiple sites
  • Mandible, open
  • Unspecified site
  • Condylar process
  • Subcondylar
  • Coronoid process
  • Ramus, unspecified
  • Angle of jaw
  • Symphysis of body
  • Alveolar border of body
  • Body, other and unspecified
  • Multiple sites
  • Malar and maxillary bones, closed
  • Malar and maxillary bones, open
  • Orbital floor (blow-out), closed
  • Orbital floor (blow-out), open
803
  • 803.0
  • 803.1
  • 803.2
  • 803.3
  • 803.4
  • 803.5
  • 803.6
  • 803.7
  • 803.8
  • 803.9
Other Unqualified Skull Fractures
  • Closed without mention of intracranial injury
  • Closed with cerebral laceration and contusion
  • Closed with subarachnoid, subdural, and extradural hemorrhage
  • Closed with other and unspecified intracranial hemorrhage
  • Closed with intracranial injury of other and unspecified nature
  • Open without mention of intracranial injury
  • Open with cerebral laceration and contusion
  • Open with subarachnoid, subdural, and extradural hemorrhage
  • Open with other and unspecified intracranial hemorrhage
  • Open with intracranial injury of other and unspecified nature
806
  • 806.0
  • 806.00
  • 806.01
  • 806.02
  • 806.03
  • 806.04
  • 806.05
  • 806.06
  • 806.07
  • 806.08
  • 806.09
  • 806.1
  • 806.10
  • 806.11
  • 806.12
  • 806.13
  • 806.14
  • 806.15
  • 806.16
  • 806.17
  • 806.18
  • 806.19
  • 806.2
  • 806.20
  • 806.21
  • 806.22
  • 806.23
  • 806.24
  • 806.25
  • 806.26
  • 806.27
  • 806.28
  • 806.29
  • 806.3
  • 806.30
  • 806.31
  • 806.32
  • 806.33
  • 806.34
  • 806.35
  • 806.36
  • 806.37
  • 806.38
  • 806.39
  • 806.4
  • 806.5
  • 806.6
  • 806.60
  • 806.61
  • 806.62
  • 806.69
  • 806.7
  • 806.70
  • 806.71
  • 806.72
  • 806.79
  • 806.8
  • 806.9
Fracture of Vertebral Column with Spinal Cord Injury
  • Cervical, closed
  • C1-C4 level with unspecified spinal cord injury
  • C1-C4 level with complete lesion of cord
  • C1-C4 level with anterior cord syndrome
  • C1-C4 level with central cord syndrome
  • C1-C4 level with other specified spinal cord injury
  • C5-C7 level with unspecified spinal cord injury
  • C5-C7 level with complete lesion of cord
  • C5-C7 level with anterior cord syndrome
  • C5-C7 level with central cord syndrome
  • C5-C7 level with other specified spinal cord injury
  • Cervical, open
  • C1-C4 level with unspecified spinal cord injury
  • C1-C4 level with complete lesion of cord
  • C1-C4 level with anterior cord syndrome
  • C1-C4 level with central cord syndrome
  • C1-C4 level with other specified spinal cord injury
  • C5-C7 level with unspecified spinal cord injury
  • C5-C7 level with complete lesion of cord
  • C5-C7 level with anterior cord syndrome
  • C5-C7 level with central cord syndrome
  • C5-C7 level with other specified spinal cord injury
  • Dorsal [Thoracic], closed
  • T1-T6 level with unspecified spinal cord injury
  • T1-T6 level with complete lesion of cord
  • T1-T6 level with anterior cord syndrome
  • T1-T6 level with central cord syndrome
  • T1-T6 level with other specified spinal cord injury
  • T5-T12 level with unspecified spinal cord injury
  • T5-T12 level with complete lesion of cord
  • T5-T12 level with anterior cord syndrome
  • T5-T12 level with central cord syndrome
  • T5-T12 level with other specified spinal cord injury
  • Dorsal [Thoracic], open
  • T1-T6 level with unspecified spinal cord injury
  • T1-T6 level with complete lesion of cord
  • T1-T6 level with anterior cord syndrome
  • T1-T6 level with central cord syndrome
  • T1-T6 level with other specified spinal cord injury
  • T5-T12 level with unspecified spinal cord injury
  • T5-T12 level with complete lesion of cord
  • T5-T12 level with anterior cord syndrome
  • T5-T12 level with central cord syndrome
  • T5-T12 level with other specified spinal cord injury
  • Lumbar, closed
  • Lumbar,open
  • Sacrum and coccyx, closed
  • With unspecified spinal cord injury
  • With complete cauda equina lesion
  • With other cauda equina injury
  • With other spinal cord injury
  • Sacrum and coccyx, open
  • With unspecified spinal cord injury
  • With complete cauda equina lesion
  • With other cauda equina injury
  • With other spinal cord injury
  • Unspecified, closed
  • Unspecified, open
807 Fracture of Rib(s), Sternum, Larynx, and Trachea
940
  • 940.0
  • 940.1
  • 940.2
  • 940.3
  • 940.4
  • 940.5
  • 940.9
Burn Confined to Eye and Adnexa
  • Chemical burn of eyelids and periocular area
  • Other burns of eyelids and periocular area
  • Alkaline chemical burn of cornea and conjunctival sac
  • Acid chemical burn of cornea and conjunctival sac
  • Other burn of cornea and conjunctival sac
  • Burn with resulting rupture and destruction of eyeball
  • Unspecified burn of eye and adnexa
941
  • 941.0
  • 941.1
  • 941.2
  • 941.3
  • 941.4
  • 941.5
Burns of Face, Head, and Neck (include all 5th digit code)
  • Unspecified degree
  • Erythema (first degree)
  • Blisters, epidermal loss (second degree)
  • Full-thickness skin loss (third degree NOS)
  • Deep necrosis of underlying tissues (deep third degree) without mention of loss of a body part
  • Deep necrosis of underlying tissues (deep third degree) with loss of a body part
942
  • 942.0
  • 942.1
  • 942.2
  • 942.3
  • 942.4
  • 942.5
Burn of Trunk (include all 5th digit codes)
  • Unspecified degree
  • Erythema (first degree)
  • Blisters, epidermal loss (second degree)
  • Full-thickness skin loss (third degree NOS)
  • Deep necrosis of underlying tissues (deep third degree) without mention of loss of a body part
  • Deep necrosis of underlying tissues (deep third degree) with loss of a body part
943
  • 943.0
  • 943.1
  • 943.2
  • 943.3
  • 943.4
  • 943.5
Burn of Trunk (include all 5th digit codes)
  • Unspecified degree
  • Erythema (first degree)
  • Blisters, epidermal loss (second degree)
  • Full-thickness skin loss (third degree NOS)
  • Deep necrosis of underlying tissues (deep third degree) without mention of loss of a body part
  • Deep necrosis of underlying tissues (deep third degree) with loss of a body part
944
  • 944.0
  • 944.1
  • 944.2
  • 944.3
  • 944.4
  • 944.5
Burn of Trunk (include all 5th digit codes)
  • Unspecified degree
  • Erythema (first degree)
  • Blisters, epidermal loss (second degree)
  • Full-thickness skin loss (third degree NOS)
  • Deep necrosis of underlying tissues (deep third degree) without mention of loss of a body part
  • Deep necrosis of underlying tissues (deep third degree) with loss of a body part
945
  • 945.0
  • 945.1
  • 945.2
  • 945.3
  • 945.4
  • 945.5
Burn of Trunk (include all 5th digit codes)
  • Unspecified degree
  • Erythema (first degree)
  • Blisters, epidermal loss (second degree)
  • Full-thickness skin loss (third degree NOS)
  • Deep necrosis of underlying tissues (deep third degree) without mention of loss of a body part
  • Deep necrosis of underlying tissues (deep third degree) with loss of a body part
946
  • 946.0
  • 946.1
  • 946.2
  • 946.3
  • 946.4
  • 946.5
Burns of Multiple Specified Sites
  • Unspecified degree
  • Erythema (first degree)
  • Blisters, epidermal loss (second degree)
  • Full-thickness skin loss (third degree NOS)
  • Deep necrosis of underlying tissues (deep third degree) without mention of loss of a body part
  • Deep necrosis of underlying tissues (deep third degree) with loss of a body part
947
  • 947.0
  • 947.1
  • 947.2
  • 947.3
  • 947.4
  • 947.8
  • 947.9
Burn of Internal Organs
  • Mouth and pharynx
  • Larynx, trachea, and lung
  • Esophagus
  • Gastrointestinal tract
  • Vagina and uterus
  • Other specified sites
  • Unspecified site
948
  • 948.0
  • 948.1
  • 948.2
  • 948.3
  • 948.4
  • 948.5
  • 948.6
  • 948.7
  • 948.8
  • 948.9
Burns Classified According to Extent of Body Surface Involved
  • Burn (any degree) involving less than 10 percent of body surface (include all 5th digit codes)
  • 10-19 percent of body surface
  • 20-29 percent of body surface
  • 30-39 percent of body surface
  • 40-49 percent of body surface
  • 50-59 percent of body surface
  • 60-69 percent of body surface
  • 70-79 percent of body surface
  • 80-89 percent of body surface
  • 90percent or more of body surface
949
  • 949.0
  • 949.1
  • 949.2
  • 949.3
  • 949.4
  • 949.5
Burn, Unspecified
  • Unspecified degree
  • Erythema (first degree)
  • Blisters, epidermal loss (second degree)
  • Full-thickness skin loss (third degree (NOS)
  • Deep necrosis of underlying tissues (deep third degree) without mention of loss of a body part
  • Deep necrosis of underlying tissues (deep third degree) with loss of a body part
995.5 Child maltreatment syndrome


APPENDIX B. ITEMS USED TO MEASURE FUNCTIONAL STATUS

Enter child number and first/last name of child with special health care needs listed in Section 1, #16.

Child Number:__________ First Name:__________ Last Name:__________

FUNCTIONAL STATUS II (R) 14-ITEM VERSION (English)

Here are some statements that mothers have made to describe their children. Thinking about __________ (INDEX CHILD), during the last two weeks did he/she...

  PART 1 PART 2  
Never of Rarely Some of the Time Almost Always Fully Partly Not At All
17. Eat well 0* 1* 2___ 2 1 0___ FS1
18. Sleep well 0* 1* 2___ 2 1 0___ FS2
19. Seem contented and cheerful 0* 1* 2___ 2 1 0___ FS3
20. Act moody 0 1* 2*___ 2 1 0___ FS4
21. Communicate what he/she wanted 0* 1* 2___ 2 1 0___ FS5
22. Seem to feel sick and tired 0 1* 2*___ 2 1 0___ FS6
23. Occupy himself/herself 0* 1* 2___ 2 1 0___ FS7
24. Seem lively and energetic 0* 1* 2___ 2 1 0___ FS8
25. Seem unusually irritable or cross 0 1* 2*___ 2 1 0___ FS9
26. Sleep through the night 0* 1* 2___ 2 1 0___ FS10
27. Respond to your attention 0* 1* 2___ 2 1 0___ FS11
28. Seem unusually difficult 0 1* 2*___ 2 1 0___ FS12
29. Seem interested in what was going on around him/her 0* 1* 2___ 2 1 0___ FS13
30. React to little things by crying 0 1* 2*___ 2 1 0___ FS14

Copyright 1981
Ruth E.K. Stein, M.D.
Catherine K. Riessman, Ph.D.
Dorothy Jones Jessop, Ph.D.

[Table of Contents]


Managed Care Enhancement Project for Children with Special Health Care Needs: Family and Primary Care Clinician Needs Assessment Methods and Description of Survey Respondents

METHODS

A needs assessment was conducted to gain a better understanding of the needs and concerns of families of children with special health care needs enrolled in MassHealth Managed Care and primary care clinicians (PCCs) in the MassHealth Primary Care Clinician Plan. Surveys, which focussed on issues identified by the project Advisory Committee, were utilized to identify the needs and concerns of families and PCCs. Focus groups were then held in order to clarify and enhance survey data. Focus groups also provided a forum in which participants could generate ideas and recommendations for potential interventions to address their concerns. The results of the assessment were used to guide the development of appropriate interventions to enhance the care of children with special health care needs in MassHealth Managed Care.

Criteria Used for Defining MassHealth Population of Children with Special Health Care Needs

In order to identify the population of children with special health care needs enrolled in MassHealth Managed Care, the following criteria were used: Children with special health care needs were defined as those children aged 18 and under who were enrolled continuously (with no more than a 45 day break in eligibility in FY 94) in the MassHealth Managed Care program, and who were either (1) receiving SSI or (2) receiving AFDC and had at least one Early Intervention claim in FY 94.

Surveys

Surveys were sent to a random sample of families of children with special health care needs enrolled in MassHealth and PCCs in the MassHealth PCC Plan. All families were sent both English and Spanish versions of the survey. Three hundred twenty-one family surveys (including 67 Spanish versions of the survey) and 285 PCC surveys were returned. This represents a 32% and 31% response rate, respectively. Analysis of family survey data did not reveal any significant differences in the responses of English and Spanish respondents. Analysis of PCC survey data did not reveal any significant differences in satisfaction or needs between PCCs with high and low proportions of children with special health care needs in their practice, or between PCCs in different practice types.

Focus Groups

Four family and two PCC focus groups were conducted. The family focus groups were held in Lawrence, Boston, Hyannis and Holyoke. The Holyoke focus group was conducted in Spanish. The PCC focus groups, which were comprised of PCCs from a variety of practice types and cities and towns throughout Massachusetts, were conducted as conference calls.


DESCRIPTION OF SURVEY RESPONDENTS

Family Respondents

321 families completed the family survey (32% response rate). The mean age of respondents' children was 9.7 years, with 2.5% under 3 years of age and 52% between 3 and 10 years of age. There was no significant difference in age or race between respondents and non-respondents. When asked to describe their child's current special health care needs, 6% described the need as a physical limitation only, 12.5% described the need as one that requires help with every day activities, and 33% described the need as one resulting in difficulty with social relationships only. The remaining respondents reported a combination of different types of needs.

PC Respondents

285 PCCs completed the PCC survey (31% response rate). 59% were from group practices, 17% were solo practitioners, and 24% were from outpatient departments or community health centers. Of the 285 respondents, 194 were eligible to complete the entire survey. (91 reported that they either did not provide primary care for Medicaid enrolled children under age 18 or did not provide care for children with special health care needs, and were therefore instructed not to continue beyond the first few survey questions.) Therefore, 194 surveys were used for analysis. When asked to describe their patient population by estimating the proportion of children with special health care needs that fall into various categories, the average responses were as follows:

When asked to estimate the proportion of their entire caseload comprised of children with special health care needs, the mean response was 10.4% (range between 1% and 100%). 60% reported that less than 10% of their caseload was comprised of children with special health care needs.

[Table of Contents]


Managed Care Enhancement Project for Children with Special Health Care Needs: Primary Care Clinician Survey--Mail Survey

This publication can be viewed in the PDF version of this document. An HTML version is not available at this time.

[Table of Contents]


Managed Care for Children with Special Health Needs: Parent Survey

This publication can be viewed in the PDF version of this document. An HTML version is not available at this time.

[Table of Contents]


Overall Findings of Needs Assessment

An analysis and integration of survey and focus group data revealed overall satisfaction of families and primary care clinicians (PCCs) of children with special health care needs to be generally high. However, when satisfaction with different aspects of care is compared, both families and PCCs reported being less satisfied in some areas than in others. These areas, information, family supports, and coordination of care (in particular, coordination of care regarding home health services, hospitalization and discharge planning, and school health services) were identified by both families and PCCs as areas that present opportunities for improvement.

This summary report includes key findings of the family needs assessment, followed by key findings of the primary care clinician needs assessment.


FAMILY NEEDS ASSESSMENT

Three hundred twenty-one family surveys were completed, and four family focus groups were held. Tables I-IV describe key survey findings. Table V is a summary of the family needs assessment and incorporates key findings of both the survey and focus groups.

The family survey measured overall parent satisfaction in five different areas of care. Table I describes the responses to the five overall satisfaction questions. Most respondents reported being satisfied in most areas in most areas measured. However, when comparing the responses to the overall satisfaction questions, we see that the provision of information and the availability of supports to help parents care for their children with special health care needs stand out as areas in which fewer parents reported themselves "very satisfied." This comparison, in conjunction with the knowledge that patient satisfaction surveys generally reflect a somewhat positive or favorable bias, suggests that the provision of information and availability of family supports are areas that may benefit from improvement.

Parents reported some types of information and supports to be more accessible than others. Tables II and III list parents' ratings of the accessibility of different types of information and supports.

Although overall satisfaction with primary care physicians' coordination of medical care was high (94%), respondents reported primary care physician involvement to be low in several critical areas of care coordination: discharge planning, home care, and school health services. These areas are highlighted in Table IV. These responses are in striking contrast to the responses in other areas measured regarding the primary care physician's role in care coordination. Other areas of care coordination measured revealed primary care physician involvement to be always/usually present for at least 87% of respondents.

One suggested explanation for parents' high level of overall satisfaction with primary care physicians' coordination of medical care, despite low primary care physician involvement in these areas, is that parents may not view communication and coordination with hospital discharge planning, home care, and schools as part of the role of their child's primary care physician and therefore do not attribute them as contributing to their satisfaction (or dissatisfaction) with the way in which the primary care physician coordinates their child's care.

In order to gain further insights regarding the problems of information, support, and care coordination, parents were asked to elaborate on these areas in focus groups. Highlights of the focus group discussions are described in Table V (on the following page), along with a summary of key findings from the parent survey.

Summary of Family Needs Assessment

Parents of children with special health care needs identified the availability and accessibility of information, family supports and care coordination, particularly coordination of care surrounding hospitalization, discharge planning, home care and school health services, as areas that could benefit from improvement. Focus group discussions confirmed these survey findings. They also provided anecdotal information from parents about concerns regarding uncovered or under-covered services. Areas in which parents felt there to be gaps in services included durable medical equipment; dental health services; mental health services; transportation; and interpreter services.

The problems of family supports and gaps in services are not unrelated to those of information and care coordination. Interventions that improve the dissemination of information to both families and primary care physicians may also address the problem of limited access to family supports and perceived gaps in services.


PRIMARY CARE CLINICIAN NEEDS ASSESSMENT

Surveys were received from 285 PCCs: 194 surveys were used for analysis. (91 PCCs were not eligible to complete the entire survey and were therefore excluded from analysis.) Two PCC focus groups were held. Table VI describes selected survey results. Table VII summarizes the PCC needs assessment by incorporating key findings of both the survey and focus groups.

Overall PCC satisfaction in three areas measured by the survey was high. Most respondents reported being satisfied in most of the specific areas measured. In general, respondents reported that "making a difference," and watching a patient progress, grow and develop were key factors contributing to their satisfaction. However, when probed, several areas emerged as areas in which there is room for improvement. Table VI includes a summary of these findings.

Primary Care Clinicians identified several areas of care that could benefit from improvement. The areas identified were those related to care coordination and information regarding the care of children with special health care needs. A summary of key findings of the PCC needs assessment, highlighting PCC concerns, is presented in Table VII.

Summary of PCC Needs Assessment

PCCs identified coordination of care of children with special health care needs, mostly related to the provision of home care services, hospital discharge planning, specialists, schools and parents, as an area in need of improvement. Coordination of care was described as particularly difficult for those children with multiple needs who are serviced by many agencies. PCCs also identified a lack of information--or difficulty in accessing information--regarding the care of children with special health care needs as a problem both for themselves and for parents. In addition, PCCs reported a concern that time limitations prevent them from meeting all of the needs of the child and family. Interventions that improve the dissemination of information and strategies to improve care coordination may, in fact, reduce this problem of time limitations.

TABLE 1. Survey Findings on Overall Parent Satisfaction
Satisfaction with... Very Satisfied Somewhat Satisfied Somewhat Dissatisfied Very Dissatisfied
The way in which their child's primary care physician provides medical care 71% 23% 4% 2%
The way in which child's primary care physician coordinates the medical care their child receives 71% 23% 4% 2%
Support parent receives for their role in caring for their child with special health care needs 70% 22% 6% 2%
Information parent receives on medical care for their child with special health care needs 56% 31% 9% 4%
Support available to help parent provide care for their child with special health care needs 53% 31% 10% 6%


TABLE 2. Survey Findings on Parent Information
Type of Information: Frequency with which Parent can Obtain Information If Needed Always/
Usually
Sometimes/
Never
Information on child's conditions 87% 13%
Information on child's developmental needs 87% 13%
Information on diagnostic procedures or tests performed on child 86% 14%
Information on MassHealth Managed Care enrollment procedures 71% 29%
Information on rights within MassHealth Managed Care if parent has a problem or disagrees with child's physician 71% 29%
Information on MassHealth Managed Care benefits 70% 30%
Information on research and latest medical discoveries related to child's special health care needs 68% 32%
Information on other programs that might help their child or family 60% 40%


TABLE 3. Survey Findings on Family Supports
Type of Support: Ease or Difficulty with which Parent can Find and Obtain Support If Needed Very/
Somewhat Easy
Very/
Somewhat Difficult
Mental health counseling for other children in the family 80% 20%
Mental health counseling for parent 78% 22%
Support with school enrollment or early intervention services 78% 22%
Assistance coordinating different medical appointments and therapies that child may need 78% 22%
Mental health counseling for child with special health care needs 74% 26%
Locating family-to-family support groups 70% 30%
Assistance finding and arranging for respite care 68% 32%


TABLE 4. Survey Findings on Coordination of Care
Area of Care Coordination: Frequency of Primary Care Physician Involvement Always/
Usually
Sometimes/
Never
Communication with School or Early Intervention Program: when requested to do so by parent, primary care physician communicates with staff of child's early intervention program or school 73% 27%
Discharge Planning: primary care physician plays an active role in the discharge planning process when child is hospitalized 72% 28%
Home Care: primary care physician (or staff) makes arrangements for home care when it is needed 70% 30%
Communication with Home Care Providers: primary care physician (or staff) communications regularly with home care providers about the care child receives 67% 33%


TABLE 5. Summary of Family Needs Assessment
Issue Survey Findings Focus Group Findings
Information Types of information parents have needed but had the most difficulty obtaining include information on:
  • research and the latest medical discoveries related to their child with special health care needs
  • MassHealth Managed Care enrollment procedures, benefits and rights
  • other programs that might help their child or family
Several parents identified the need for all information to be simplified so that more parents could understand it. Types of information noted include:
  • medical information
  • information on other services for their child or family
  • information on benefits
Family Support Types of supports parents have needed but have had difficulty obtaining include:
  • mental health counseling services (for their child with special needs, for themselves, or for their other children)
  • family-to-family support groups
  • respite care
  • assistance coordinating medical appointments
  • support with school enrollment or early intervention services
Several parents recommended that parents have a Parent/Patient Advocate to provide support. Again, they referred to problems with school health services. The role of the Advocate would be:
  • to assist parents at school team meetings in order to ensure that their child's rights are supported
  • to monitor the services the school provides in order to ensure that services are rendered and the recommended treatment plan is followed
Care Coordination Specific areas of care coordination that need improvement include:
  • hospital discharge planning
  • home care
  • school health services
Focus group participants consistently mentioned school health services as a major problem. Problems noted included availability of services as well as parents' limited knowledge of services actually provided to their children.

Focus group discussions confirmed that, while many parents are unhappy with coordination and information related to school health services, they do not necessarily expect their child's primary care physician to play a role in coordinating their child's treatment at school.


TABLE 6. Survey Findings on PCC Satisfaction
Satisfaction with... Very Satisfied Somewhat Satisfied Somewhat Dissatisfied Very Dissatisfied Most Common Factors Associated with Dissatisfaction
The relationships PCC has with parents of patients with special health care needs 57% 35% 7% 1%
  • time constraints
  • poor communication
  • uncooperative families/failure of families to keep appointments and follow through
  • stressed parents
The relationships PCC has with specialists to whom they refer children with special health care needs 45% 49% 6% 0%
  • lack of communication
  • inaccessibility
  • lack of teamwork and cooperation
  • difficulty in coordination of care
Their role as a Primary Care Clinician for children with special health care needs 36% 53% 11% 0%
  • time constraints (33% reported that time constraints made providing primary care to children with special health care needs difficult)
  • red tape/paperwork
  • insurance company rules and restrictions
  • lack of services/programs
  • lack of financial reimbursement
  • inability to coordinate multiple providers


TABLE 7. Summary of PCC Needs Assessment
Issue Key Survey and Focus Group Findings
Coordination with Specialists
  • 27% of survey respondents reported that, when they make a referral to a specialist, they sometimes or never identify specific questions they want the specialist to answer
  • 42% of survey respondents reported that they never specify a time frame for receiving feedback from specialists
  • Lack of communication and delayed feedback by specialists were reported as problems often encountered by focus group participants
  • Focus group participants noted that problems arise when specialists refer their patients to other specialists without the PCC's knowledge
Coordination with Home Care and Hospital Discharge Planning
  • 53% of survey respondents reported that they sometimes or never participate in the development of home care plans for children with special health care needs; 10% reported they always participate in home care plan development
  • 34% of survey respondents reported that, when a child in their practice requires home care, the referral is only sometimes initiated by them. Hospitals were reported as a common source of the home care referral.
  • Some focus group participants felt that the home care system works well for children with acute needs, but is more problematic for children with chronic, complex conditions. Their feeling was that these children require an exceptional amount of time to coordinate all of their various needs.
  • Focus group participants reported burdensome paperwork and high turnover in home care agencies as causing a large drain on PCCs' time. Turnover in home care agencies resulted in little communication between old and new caregivers, presenting PCCs with a greater challenge obtaining information about their patient
Coordination with Schools
  • In focus group discussion, participants noted that coordination with school health services is a major challenge. Their concerns included:
    • insufficient school personnel or resources to meet the needs of children with special health care needs
    • difficulty contacting school providers since parents are not always aware of the name of the school provider and because school providers are usually unavailable at the times when PCCs are available to communicate with them by telephone
Information
  • Survey results revealed that PCC's are most likely to seek information on issues related to the care of children with special health care needs from specialists (96% of respondents), colleagues within their practice (89%), medical libraries (67%) and early intervention providers (61%).
  • Survey respondents reported that they are least likely to seek information on issues related to the care of children with special health care needs from on on-line medical sources and programs run by public and other social service agencies.
  • When asked to elaborate on their information needs during focus groups, participants reported that they typically did not use state agencies as an information resource because of the difficulty in determining the most appropriate agency to contact, as well as the most appropriate person in the agency.
Parent Role
  • 87% of survey respondents reported that parents are one of the most common sources of care coordination.
  • 18% of survey respondents reported that parents are the ones who typically monitor the implementation of home care plans.
  • In focus groups, PCCs reported that they rely heavily on parents to coordinate their child's care. While some PCCs felt that this arrangement works well for some families, they believed that it is very demanding on families and not all parents have the ability, information and support to perform this difficult role well.
  • Focus group participants recommended that there be a centralized patient advocate case management system which would include team meetings with physicians. They reported that the most difficult aspect of caring for children with special health care needs is ensuring that full consideration is given to all of the patient's multiple health and information needs. They strongly believed that a patient advocate case manager could help physicians, patients and their families in this regard.

[Table of Contents]


SESSION 2: IMPACT OF MANAGED CARE ON ADULTS WITH MENTAL ILLNESS

Reactor Biographies

Howard H. Goldman, M.D., M.P.H., Ph.D.
Howard Goldman is Professor of Psychiatry at the University of Maryland, School of Medicine at Baltimore, where he is Director of Mental Health Policy Studies. From 1983-1985 he served as Assistant Institute Director at the NIMH, where he was responsible for mental health care financing policy and related research. He continues to consult to the Federal Government on health care finance, including his service in 1993 on the President's Task Force on Health Care Reform.

As Assistant Director of NIMH, he worked with the Social Security Administration (SSA) on the revision of the mental impairment standards for the disability program. Subsequently, he consulted to the American Psychiatric Association on a SSA contract to assess the reliability and validity of those standards. Dr. Goldman has written several articles in the professional literature on the SSA disability program and recently conducted a published review of measures of functional assessment. He also consulted to Westat on the design of the Disability Examination Study for SSA, and he is a member of the National Academy of Social Insurance Policy Panel on Disability.

Dr. Goldman is a frequent contributor to the professional literature in mental health services research and economics. His resume lists ten books, 20 monographs and reports, and over 150 articles and chapters. Dr. Goldman's editorial board appointments have included Health Affairs, Journal of Mental Health Administration, Psychiatric Services (formerly Hospital and Community Psychiatry), and the American Journal of Psychiatry. In addition, he has just completed the fourth edition of his textbook for medical students, Review of General Psychiatry.

Michael F. Hogan, Ph.D.
Michael Hogan has served as Director of the Ohio Department of Mental Health since March 1991. He was Commissioner of Mental Health in Connecticut from 1987-1991 and was credited with leading that State to a fourth place ranking among the State mental health systems in 1990--tied with Ohio. Previously, he served as a Regional Director and State Hospital Superintendent in Massachusetts, and was responsible for administering mental health and mental retardation programs in Western Massachusetts.

Dr. Hogan holds a bachelor's degree from Cornell University and a Ph.D. from Syracuse University. He is President of the Board of the National Association of State Mental Health Program Directors (NASMHPD) Research Institute and serves on the National Advisory Council, which approves NIHM research grants. He has authored a text and numerous book chapters and papers on mental health care, with his most recent publications focussed on The Organization and Financing of Mental Health Care and Managing the Whole System Under Managed Care. He is married and has three sons.

[Table of Contents]


Severely Mentally Ill HMO Members

Bentson H. McFarland, M.D., Ph.D.
Bentson McFarland is Professor of Psychiatry, Public Health and Preventive Medicine at Oregon Health Sciences University and Adjunct Investigator at the Kaiser Permanente Center for Health Research in Portland, Oregon. He received his M.D. degree and a Ph.D. in biostatistics from the University of Washington in Seattle. He conducts research on mental health services, pharmacoeconomics, and pharmacoepidemiology.

RESEARCHERS

BACKGROUND: MEDICAL OUTCOMES STUDY

OBJECTIVES

SEVERELY MENTALLY ILL HMO MEMBERS

CONTROLS (AGE AND SEX MATCHED)

SEVERELY MENTALLY ILL SURJECTS (COHORT #1)

PREDICTORS OF LONGER ENROLLMENT FOR SEVERELY MENTALLY ILL SUBJECTS (COHORT #1)

Note: HMO costs of care not predictive of enrollment duration

CONCLUSIONS

TABLE 1. Utilization and HMO Costs During Follow-Up (Cohort #1)
  Severely Mentally Ill Controls
Community mental health center 40% 5%
State hospital 12% 1%
Exceeded mental health benefit 12% 0%


TABLE 2. Enrollment Duration (Cohort #1)
  Days in HMO
Diabetic patients 1,424
Severely mentally ill 1,263
Pharmacy controls 1,236
Membership controls 1,023


TABLE 3. Enrollment Duration (Cohort #2)
  Days in HMO
Diabetic patients 1,256
Severely mentally ill 1,158
Pharmacy controls 861
Membership controls 175

[Table of Contents]


Colorado's Early and Preliminary Experience with Capitation for the Severely and Persistently Mentally Ill Adults

Joan R. Bloom, Ph.D.
Joan Bloom is Professor of Health Policy and Administration at the University of California, Berkeley in the School of Public Health. She received her doctorate in Sociology of Education at Stanford University. She is a Co-Investigator at the Center for Mental Health Services Research. In addition, she is an Affiliated Investigator at the Northern California Cancer Center and a Consultant for the Stanford University Medical Center. Her research interests include organizational studies and community services focused on the delivery of medical and mental health services. She has had a long-standing interest in prevention and early detection of chronic disease. She is currently the Principal Investigator of two NIH funded studies: (1) the Colorado Capitation Study in which mental health services are being capitated for the Medicaid eligible population in the State of Colorado funded by the National Institute of Mental Health; and (2) Young Women with Breast Cancer, funded by the National Cancer Institute in which ethnically diverse, newly diagnosed younger women in the greater Bay Area are assessed and provided with a psychosocial support intervention. She is also involved in a longitudinal study focused on work redesign of hospital nurses. She serves on the Board of Directors of the Northern California Cancer Center and on the editorial boards of Cancer Prevention, Epidemiology and Biomarkers and International Journal of PsychoOncology. She serves on the Breast and Cervical Cancer Advisory Committee for the State of California and is Chair of their Evaluation Committee.

Dr. Bloom's teaching interests include organizational sociology, health care management, and program planning and evaluation. She teaches courses in program planning and evaluation, and master and doctoral level courses in organizational studies plus a variety of seminars.

RESEARCHERS

COLORADO'S MENTAL HEALTH SYSTEM

FEATURES OF CAPITATION PROGRAM

SPECIFIC AIMS:

SUBJECT CHARACTERISTICS

*Only for 1994 sample

ORGANIZATIONAL CHANGE MEASURES:

TABLE 1. Research Design
Targets for Each Cell 1994 1995 New to System
Model 1* 128 64 64
Model 2* 128 64 64
Comparison - FFS 128 64 64
Model 1 = Stand Alone/Alliance CMHC
Model 2 = Joint venture between FP managed care firm and Stand Alone/Alliance CMHC


TABLE 2. Status of Consumer Interviews: 9/1/96
  Wave 1
(Baseline)
Wave 2 Wave 3
Completed Interviews 684 521 232
Refused 116 13 3
Deceased n/a 5 4
Unable to Locate 53 11 1
Non-Response 35 7 0
Too Ill 7 3 3
Contacted to Date 895* 560 243
Success Rate 76% 93% 95%
* An additional 361 individuals were assigned for a total of 1265, however, these potential subjects were deemed inappropriate for a variety of administrative and clinical reasons.


TABLE 3. Socio-Demographic Characteristics of Sample for Each Group
Characteristic Model I
(%)
Model II
(%)
F.F.S.
(%)
Gender
   Male
   Female
 
48.5
51.5
 
49.4
50.6
 
47.9
52.1
Ethnicity
   White
   Black
   Hispanic
 
67.7
4.0
6.1
 
46.9
4.9
19.8
 
45.8
18.8
8.3
Age
   21-35
   36-50
   51-65
   65+
 
43.4
41.4
13.1
2.0
 
25.9
46.9
19.8
7.4
 
31.9
53.2
6.4
8.5
Diagnosis
   Schizophrenic
   Bipolar-Affective Disorder
   Other
     
High Cost Client 31.3 39.5 52.1


TABLE 4. Utilization of Mental Health Services for Each Model Before and Following Implementation of Capitation*
Characteristic Model I Model II FFS
Pre- Post- Pre- Post- Pre- Post-
Inpatient
Outpatient
Day Treatment
Crisis Intervention
Individual Therapy
Group Therapy
Case Management
           
* 6 months prior to six months following capitation as of November 1996.


TABLE 5. Costs Per Unit of Payment (Mean and Variance) for Mental Health Services for Each Model Before and Following Implementation of Capitation*
Characteristic Model I Model II FFS
Pre- Post- Pre- Post- Pre- Post-
Inpatient
Outpatient
Day Treatment
Adult Treatment
Crisis Intervention
Individual Therapy
Group Therapy
Case Management
Total Costs
           
* 6 months prior to six months following capitation as of November 1996.


TABLE 6. Outcomes of Mental Health Services for Each Model Six Months Before and Six Months Following Implementation of Capitation*
Characteristic Model I Model II FFS
Pre- Post- Pre- Post- Pre- Post-
Health Status
   (MOS SF36)
   Physical Functioning
   Bodily Pain
   General Health
   Social Functioning
   Mental Health
           
Mental Health
   Symptoms (BPRS)
           
Functional Status
   GAF Score
   Family Contact
   Daily Activity
   Social Contact
           
Quality of Life
   Ever Homeless
   Housing Adequacy
           
Finances
   Self-reported Income
   Income Adequacy
   Average Adequacy
           
* Results as of November 1996.



[Table of Contents]


The Effects of Private Sector Mental Health Carve-Outs

Thomas G. McGuire, Ph.D.
Thomas McGuire is a Professor of Economics at Boston University. He has authored or edited three books and more than 100 published articles on health and mental health economics and policy. In 1983, his book, Financing Psychotherapy, received the Elizur Wright Award from the American Risk and Insurance Association recognizing an outstanding contribution to the literature on risk and insurance. He received the Carl Taube Award for outstanding contributions to mental health services research from the American Public Health Association in 1991. He has served as co-chair of three NIMH-sponsored conferences on economics and mental health, and has been the Research Director of a training program in economics and mental health at the Heller School at Brandeis University since 1981.

Dr. McGuire is the recipient of two sequential five-year Research Scientist Awards from the National Institute of Mental Health to study payment and financing of mental health services. Currently, he is also a recipient of an Investigator Award in Health Policy from the Robert Wood Johnson Foundation (joint with Richard Frank) to study reform of the organization and financing of mental health and substance abuse.

PRESENTATION NOT AVAILABLE AT TIME OF PRINTING. PLEASE REFER TO THE BACKGROUND PAPER COSTS AND INCENTIVES IN A MENTAL HEALTH AND SUBSTANCE ABUSE CARVE OUT.

[Table of Contents]


The Massachusetts Mental Health System Change

Barbara Dickey, Ph.D.
Barbara Dickey is Associate Professor, Department of Psychiatry, Harvard Medical School and Director of Mental Health Services Research at McLean Hospital. She has been studying the costs and outcomes of care for the seriously mentally ill in different treatment settings for many years, including studies of hospital alternatives, community-based systems and comprehensive treatment models that integrate acute and long-term care for the psychiatrically disabled. She has been a frequent contributor to the professional literature and has recently co-edited a book on measuring behavioral health outcomes in clinical practice. With NIMH funding, she recently completed a cost-effectiveness study of housing and treatment for adults who are homeless and mentally ill and she is current the Principal Investigator of an NIMH study of managed care in Massachusetts.

PRESENTATION NOT AVAILABLE AT TIME OF PRINTING. PLEASE REFER TO THE BACKGROUND PAPER MANAGING THE CARE OF SCHIZOPHRENIA.

[Table of Contents]


Costs and Incentives in a Mental Health and Substance Abuse Carve Out

Ching-to Albert Ma and Thomas G. McGuire
Draft; preliminary and unfinished
DO NOT QUOTE OR CIRCULATE

ACKNOWLEDGEMENT

Financial support from National Institute of Drug Abuse Cooperative Agreement 1-P50-DA10233-01 and grant K05-MH01263 from the National Institute of Mental Health is gratefully acknowledged. We thank our research assistant Didem Bernard for her excellent help. We are grateful to the Group Insurance Commission of the Commonwealth of Massachusetts for allowing us access to the data.


ABSTRACT

This paper examines the overall change in costs of mental health and substance abuse services in a carve out program initiated in 1993 by the General Insurance Commission (GIC) of the Commonwealth of Massachusetts. Claims data for two years before (July 1991-June 1993) and two years after (July 1993-June 1995) the carve out were obtained from the GIC. These data were accompanied by an eligibility file for the four-year sample period. The exact financial arrangements in the vendor-payer contract are examined and described. The paper provides a full description of incentives, including multi-year contract renewals, and the payments and incentives associated with the administrative portion of the payments. We use those incentives to generate hypotheses about the effects of managed care on patterns of service use and cost.

The paper quantifies the changes in costs between the two years before the carve out and the two years after. By examining patterns of services in a population of continuously enrolled individuals, we eliminate selection-related changes in characteristics of the population.

The paper's main contribution is to describe and decompose the effect of managed care for mental health and substance abuse and to relate the observed effects to the incentives in the contract. We show the total plan and employee payments by month of service date for all major categories of expenditures, such as inpatient, other residential, and office visits. Trends in medical care prices will be used to adjust the data. Our basic decomposition therefore show impact by type of services, and show this separately for plan and employee-paid costs.

Our findings indicated significant savings after the carve out. Total and plan costs reduced by 50% to 70% over the four-year period. The pattern of cost reductions are similar with respect to outpatient and inpatient services, as well as to mental health and substance abuse services. The estimated average price of a mental health outpatient visit increased over time in the sample period, whereas that of a substance abuse outpatient visit decreased slightly.


INTRODUCTION

Many big employers and payers have contracted with specialty management firms to administer the delivery of mental health and substance abuse (MHSA) benefits to their enrollees. This so-called MHSA "carve out" appears to be a most significant recent development, and has led to a new "behavioral healthcare" industry consisting of firms specializing in this service. Oss (1994) estimates that in 1994 over 50 million people in the U.S. are in some carve out program. "Risk-based" contracts, in which the specialty vendor (usually a for-profit corporation) bears some or all of the financial risk associated with MHSA services, are used in about half of all carve out programs. The rapidly growing use of separate carve-out contracts has been stimulated by reports of very favorable cost experience for many payers, with some savings reported to be in the range of 40 percent or more (Frank, McGuire and Newhouse 1995).

From an employer's or a payer's point of view, a carve out contract addresses the longstanding issues of moral hazard and adverse selection associated with insurance for mental health services (McGuire 1981; Frank, Huskamp, McGuire and Newhouse forthcoming; Frank, Glazer and McGuire 1996). Moral hazard is contained by the techniques associated with managed care--price negotiations, provider network selection and monitoring, prior authorization and utilization review. Adverse selection can be addressed by unification of the financial risks associated with mental health within a single contract; by pooling all persons in the same contract, no plans compete to avoid costly MHSA users.

Although the carve out approach offers these potential advantages in principle, the practical importance of this new form of insurance contract remains to be established. Favorable experience of innovative firms need not be a good predictor of what happens to the typical employer. First, if payers who first adopted carve out methods for MHSA services management are those with below average management efficiency in their previous existing plan ("low-hanging fruit" in the language of the industry), then the effectiveness of carve outs may be much less for payers with well-run plans (Frank, McGuire and Newhouse 1995). Second, the experience of a particular payer and population is often influenced by many specific factors, some of which may not apply to other payers. Therefore, it appears important to study the diversity of payer and population characteristics, vendors' management techniques, and the actual contracts between them carefully, before generalizations are made.

We contribute to the accumulating evidence on carve outs and managed care by reporting on the experience of the MHSA carve out of a major employer in Massachusetts--the Commonwealth itself. In this first paper in a continuing project on this case, we relate the incentives in the contract to the aggregate experience. First, we describe the MHSA carve out contract between the Commonwealth of Massachusetts and the vendor, and identify its incentive implications. Second, we analyze insurance claims data for two-year periods before and after the carve out. We examine the association between the contract incentives and the actual cost outcomes, and use the period before the carve out as a benchmark for comparison. Before-and-after comparisons can be problematic because the underlying population can change. We have therefore selected for detailed analysis a group of enrollees who are continuously covered for the entire four-year data period, and examine the actual use and cost experience for them before and after the carve out.


BACKGROUND AND LITERATURE REVIEW

A behavioral health carve-out program was initiated in 1993 by the GIC of the Commonwealth of Massachusetts. The largest private payer in the state with an enrollment base of about 120,000, the GIC is responsible for providing health insurance to state and some local employees and their dependents. The GIC contracted with a combination of traditional indemnity insurers as well as HMOs since the middle of the 1970s. Between fiscal years 1989 and 1992, the State Hancock Plan, administered by John Hancock Mutual Life Insurance Company, was the indemnity plan for GIC enrollees. This managed fee-for-service plan included preadmission certification, utilization and concurrent reviews, second opinions and discharge planning, as well as pharmacy provider networks as managed-care features. These provisions applied to all areas of medical care, including MHSA services. In addition, GIC contracted with 14 HMOs (staff/group and network models) and offered them as enrollment options to employees.

The GIC voted to change its health benefit plans in late 1991. The stated goal was to improve the value of services to employees given the overall expenditure level, increase enrollment in managed care, and reduce risk fragmentation and adverse selection problems (Group Insurance Commission, Request for Proposal, 1992, p.1-3). To achieve this, the GIC retained services of a management consulting firm to assist with the evaluation of its existing benefits program, and the search for alternative benefit designs. One of the consultant's recommendations adopted by the GIC was the development of a separate MHSA carve-out progarm for enrollees. By a proposal request and subsequent biddings and negotiations, GIC selected a behavioral health care firm, Options Mental Health, Inc., from among five applicants, to set up a managed care mental health network of physicians and providers, and to manage mental health and substance abuse care on a partially at-risk basis.

The trade press contains many favorable reports of the experience of employers with carve out plans. Battagliola (1994) summarizes the experience of IBM which implemented a behavioral health carve out in 1991. In 1989, IBM was spending $106 million on MHSA benefits for its employees and dependents; this was going up at 10 percent per year, and consuming 15 percent of all health benefit costs. The carve out (with Value Behavioral Health [VBH]) consisted of a PPO with differential in-network and out-of-network cost sharing, expansion of alternative treatments, strengthening of an Employee Assistance Plan (EAP), and utilization review. By 1993, IBM's mental health costs had fallen to $59.2 million and only 10 percent of health benefit costs. Clearly, something happened here! The article provides some information about enrollment changes (the number of employees was falling by 3-4 percent per year in the later years of the data), prices (inpatient cost per day fell by 40% between the pre and post periods), and benefit changes, but understanding what happened is difficult because no information is provided on the nature of the contract between IBM and VBH, or on the composition of the expenditure changes. Finally, it is worth mentioning that IBM began the initiative with a very generous plan and very high rates of spending per employee, approximately $660 per employee per year on MHSA, more than double the national average for the period. Reducing costs by 30 percent (in real terms) still leaves IBM far above average rates of spending.1

The formal research literature on carve outs is just emerging. Grazier et al. (1993) examine outpatient utilization data one year before and one year after implementation of a PPO point-of-service plan with a benefit change for 4,220 continuously enrolled, active employees. Overall the rate of outpatient use went up slightly, but the visits per user fell slightly. The employer/vendor contract was "administrative services only" or ASO, so the vendor bore no explicit financial risk associated with utilization.

Frank and McGuire (1996) describe the experience of a carve out plan for MHSA in Massachusetts Medicaid with aggregate data from one-year pre and three and a half years post institution of a behavioral healthcare carve out. Price reductions for inpatient care and the virtual elimination of inpatient treatment for substance abuse appear to have been the main mechanism generating savings of approximately 25 percent per enrollee in real terms. The reduction in services was experienced virtually entirely by the disabled Medicaid beneficiaries. AFDC enrollees saw their costs (adjusted for medical price inflation) go up slightly over the course of the contract. The one-year contracts between the state and the vendor, Mental Health Management of America (MHMA) were almost entirely ASO contracts, and gave the vendor small incentives to reduce costs. Massachusetts began the period ranking third among the state in terms of overall health care spending for per Medicaid beneficiary. [ref]


DATA: ELIGIBILITY AND CLAIMS FILES

Data for this project come from eligibility and health claims files, covering the period July 1991 through June 1995, and provided to us by MEDSTAT. Identifying information about the contract holder was scrambled so that claims data could be merged with eligibility information without identifying contract holders. The eligibility data allow us to calculate the average number of Primary Insured Participations, or PIPs for each month. A PIP is essentially a contract holder.2 Family contracts may cover more than one individual. We use relation, sex and date of birth information to identify individuals.

For some analyses we use a subsample of PIPs consisting of those covered by the GIC for the entire four-year sample period.3 The purpose of identifying this "continuously covered" population was for a better control of sample characteristics. All of these individuals have been covered by the GIC before and after the carve out. Cost outcomes of the continuously covered subsample will be compared to those of the entire sample. About 40,000 individuals are in our continuously covered population.

In the post carve out period after July 1993 we sought information about any claim for MHSA that would be covered by the carve out contract. Inpatient and other residential care was included in the sample. For outpatient care, we extracted any claim with a mental health procedure. A comparable selection criteria was used for the pre period as well, to make utilization in the pre period comparable to utilization in the post period.4

The claims data contain several cost related fields. The contract between GIC and Options is driven by the amount that the GIC has to pay, so some of our analysis will be based on the payments by GIC reported on the claim. Claims also contain information about payment amounts that are the responsibility of the beneficiary such as copayments and deductibles. Finally, covered charges represent the total negotiated price that Options has arrived at with the provider. Normally, the sum of GIC payments, beneficiary payments, and other payer obligations (if any) will be covered charges. Providers also report charges, but we will not use this information in this paper.

Units of services such as length of stay (LOS) and visits on some outpatient claims are also reported on claims. Price per unit will be calculated by dividing covered charges by the appropriate units.

Claims data for the last two months in the sample period appear to be incomplete, apparently because of delays in the submission and processing of claims. We requested data as of November 1995, allowing three months past the final service date, but this was not long enough to accumulate almost all claims for the last quarter of data. For this reason, we discarded the claims data for the last three months in the sample period, and instead base the last year's figures on seasonally adjusted nine-month data.

By any standard the data show a very significant cost reduction after the carve out. Table 1 summarizes the findings for the entire enrolled population; all prices and costs are in current year dollars. For this population, the total net payment from GIC for all MHSA services was about $9.32 million for fiscal year 94 (July 1993-June 1994), and $7.29 million for fiscal 95. These compare to $16.93 million in fiscal 92 and $14.87 million in fiscal 93, the two years before the carve out. The average GIC payment per PIP per month for the four years between 1992 and 1995 were, respectively, $20.32, $17.84, $9.52, and $7.49. The average GIC payment per enrollee per month for these years were, respectively, $13.91, $12.22, $6.04, and $4.76.

Table 2 presents similar cost figures for the continuously covered population, and all price and cost figures are in constant 1995 dollars, with medical price index adjustment. Here the total GIC payment between 1992 and 1995 were, respectively, $10.45, $8.47, $4.60, and $3.89 millions. The average payments per PIP per month were, respectively, $32.41, $26.24, $14.26, and $12.08; per enrollee per month figures were, respectively, $22.03, $17.84, $9.70, and $8.22. Overall various indicators of "costs" have decreased between 50% and 70% in four years. We also find that total costs of MHSA services--the total paid by GIC, enrollees, as well as any third parties--show a similar pattern. Thus, the savings were not simply achieved by shifting costs from the GIC to enrollees or another payer.

Table 3 categorizes the plan and total costs of the continuously enrollees according to inpatient versus outpatient services: inpatient costs declined by about 50% while outpatient costs by more than 60%. The breakdown of these changes according to MHSA care are illustrated in Table 4.


THE CONTRACT BETWEEN THE GIC AND OPTIONS

To understand the contract between Options and the GIC, it is useful to provide some background about the proposal request and negotiation processes. In the Request for Proposal (RFP), each potential bidder was provided with a summary of the plan enrollment, costs, and utilization pattern data for two years before the RFP was released. For each of the two years, the data included hospital admission and outpatient visit rates per 1,000 enrollees, number of hospital days per 1,000 enrollees, costs per hospital admission and outpatient visit, and costs per employee. These data were given for MHSA services, both separate and combined, for all employee groups.5 Utilization pattern data, such as distribution of admissions by diagnosis and outpatient visits, readmission rates, patterns of large claims, were also provided.

The GIC and its consultants first used the data to establish a set of benchmark projections of costs and savings. Each potential vendor was asked to provide its own set of projections, and the two sets of projections were compared and evaluated after the bids were submitted.6 Finally, Options was selected as the winner, and the details of the final MHSA contract were decided.

We now describe the contracts between the GIC and Options. The initial contract was for a one-year duration, and began in July 1993. It was expected at the time that the contract renewal for a second year would happen when the initial contract expired. We will briefly describe the benefit and coverage design. Detailed descriptions of the financial arrangements between GIC and Options will then be provided.

Important dimensions of the new benefit plan for MHSA were dictated by the GIC in the RFP. The MHSA carve out would be a managed care plan, nominally similar to the "managed care" in the previous Hancock plan, but expected to be more aggressive. The GIC specified the in-network and out-of-network benefits, goals for provider networks, and even the utilization levels (10, 20, 30 visits) at which the vendor should be intervening in the care process. Implementation of these features were of course to be left to the vendor. Benefits to enrollees choosing in-network care in the point-of-service plan were expanded from coverage before the carve out. Providers were to be precertified by Options before being admitted to the network. Whether an enrollee receives care from a network provider or not, precertification must be obtained from Options by calling a toll-free telephone number before care began (except for emergencies). A Clinical Case Manager was responsible for precertification. Options must be notified within 24 hours of any hospitalization, whether emergency (life-threatening), urgent, or routine. Complaints and grievances were reviewed by Options representatives, as are disagreements with clinical determinations.7

Financial aspects of the carve out that are relevant to enrollees are as follows.8 Generally, in-network coverage for inpatient services is complete with no deductibles; out-of-network inpatient coverage is 80% of allowed charges, with a 60 days limit per year and with a two-admission or two-episode lifetime limit on substance abuse treatments. In-network outpatient visits are free for the first four, subject to a $20 copayment for the fifth to twenty-fifth, and subject to a $40 copayment thereafter. Out-of-network outpatient coverage is 50% of allowed charges, and subject to a maximum of 15 visits per year. In-network out-of-pocket expenses are limited to $1,000 per individual and $2,000 per family. Finally, the lifetime benefit maximum is $1 million.

Benefits and cost sharing in the MHSA carve out program were substantially better for the enrollees than their previous plan. Before the carve out, mental health inpatient coverage at a general hospital was complete for 120 days (after a $150 deductible), then 96% after annual deductible. But mental health coverage at a psychiatric hospital was complete for only 60 days, and at 80% thereafter with a limit of 300 days. Perhaps, the most striking difference was that before the carve out, substance abuse coverage at a substance abuse facility was at 80% and only up to $10,000 a year after deductible. Outpatient MHSA coverages were respectively at 50% and 80%, with respective limits of $1,500 and $2,500 per year after deductible. The annual benefit limit was $500,000; lifetime, $1,000,000. The benefits after the MHSA carve out represented significant improvements, especially for in-network care.

The financial contract between the GIC and Options consisted of two main parts. First, for the fiscal year beginning July 1993, each month Options received from the GIC a fee (the ASO fee), which was calculated by multiplying the number of PIPs by $3.43. Second, this rate would be adjusted upward by 5% in the second year unless otherwise agreed upon by the GIC and Options.9 The contract for fiscal 1993-4 also specified a target claims cost of $20.72 per month per PIP. Besides serving as a benchmark to evaluate cost effectiveness of the contract, it would be used to adjust the ASO fee. In the actual implementation, for the fiscal year beginning July 1994, the ASO was revised to $3.17 per month per PIP, and the target level lowered to $15.39 per month per PIP.

For the fiscal year beginning July 1993, the target was established at $20.72 per month per PIP. The $20.72 refers to the portion of costs paid by the GIC, and does not include enrollee cost sharing. At the end of the fiscal year, the actual claims costs would be compared with the aggregate claim target (aggregate, because the rate was stated in terms of per month per PIP), and the ASO fee would be reduced by an amount equal to 20% of the excess of actual claims over the target, but this reduction would not be more than 20% of the ASO fee for the contract year. For example, if the claims cost turned out to be $21.72 per month per PIP, then the ASO fee would be reduced by $0.2 (20% of $21.72-$20.72) per month per PIP. The maximum cost overrun for which Options's ASO was reduced was $(20.72+3.43)=$24.15. For fiscal year 1995-6, the target was reduced to $11.19 per month per enrollee, but the ASO fee was raised to $5.18 per enrollee per month. The adjustment of the ASO fee according to the excess of claims costs over target remained unchanged.

Besides the adjustment of the ASO fee according to the discrepancy between actual claims cost and the target, Options was required to satisfy performance targets. During the first year, the set of performance guarantees consisted of five items, but expanded to sixteen in the second. The following is a sample from those in both years:10

It is important to keep in mind that the overall benefit package was expanded substantially after the carve out. In particular, coverage for in-network outpatient care was greatly improved. If enrollees' copayment and deductible remain unchanged, this coverage improvement must tend to increase use. Furthermore, even if use did not increase due to the benefit expansion, the improvement in coverage for in network care would tend to shift costs to the GIC from other payers whohave contracts with the GIC enrollees. Thus, Options would have to implement some cost savings measure simply to be able to maintain costs to the GIC at existing levels. Indeed, the initial claims target of $20.72 per PIP was such a level that savings by Options would just offset any cost increasing effects of the benefit expansion.


INCENTIVES IN THE CONTRACT

First consider the explicit incentives in the first year of the contract, and focus on the financial penalty and rewards associated with the claims target. Up to 20% of the ASO fee could be refunded to the GIC in case the actual cost was higher than the target level. The ASO fee to Options was the result to negotiations, and was paid regardless of the costs actually incurred in administration; thus, it was a type of prospective payment. The ASO fee included a profit allowance, but the actual profit or loss might be higher or lower depending on the costs actually incurred by Options.

Clearly, Options would attempt to economize on its own administrative expenses. If controlling MHSA costs requires Options' resources, such resources would only be provided if Options is properly motivated. Indeed, the carve-out contract does contain explicit incentives for Options to control MHSA service costs. The most explicit of such incentives is associated with the claims target. The ASO fee could be reduced by up to 20% in response to costs accumulating above the claims target. To such a small company, this probably represented a significant amount of potential earnings. Nevertheless, most of the financial risks remain with the GIC. In spite of the fact that the contract is written in terms of a per PIP per month payment, the contract is very far from being a "capitation" contract in which risk is shifted largely to the vendor.

These points are extremely important and illustrated in different ways in Figures 1 and 2. Figure 1 shows how the ASO fee to Options, and costs to the GIC vary with the actual level of claims costs per PIP in the contract's first year. Options faces some risk, but this is quite small in comparison with the possible cost variations faced by the GIC. Given the different sizes of Options and the Commonwealth of Massachusetts, the risk sharing arrangement appears to be sensible. Although GIC does bear most of the MHSA service costs, the remaining cost responsibility assumed by Options still seems significant for providing incentives for Options to meet the cost target. Figure 2 depicts the same risk sharing arrangement in a "proportional" way. Here, it is clear that the carve-out contract does not shift all cost responsibilities to the vendor.

As we noted above, the contract between GIC and Options was subject to renewal after the first year. The initial contract did specify an automatic adjustment on the ASO fee by 5% but other details of the contracts were open to revisions. In fact, in the second year, the same type of contract was signed by the GIC and Options, but the cost target was lowered from $20.72 per month per enrollee to $15.39 (or about 25%).


INTERPRETATION: INCENTIVE CONTRACTS AND PERFORMANCE

The ASO fee arrangements for Options contained a number of very interesting features. First, the contract did not allow the ASO fee to increase when Options was able to lower costs below the target level, but was subject to the risk of up to 20% of the fee for cost overruns. For a company of the size of Options, the total risk does not appear to be totally insignificant. This perhaps contrasts with the Massachusetts Medicaid behavioral health carve out (see Frank and McGuire, 1996), where the "at-risk" contract imposed a maximum penalty of $300,000 in the first year of the contract. In contrast, if the ASO fee was $3.43 per month per enrollee, for a population of 70,000 PIPs, Option's potential penalty in a year could be more than $560,000. If the use of aggressive managed care to reduce claims costs meant higher administrative expenses, the incentives established by the ASO fee mechanism would imply that costs should not be expected to fall significantly below the target level. But in actual fact, the first-year claims costs did fall significantly below the target. This brings us to the second point.

Options might have correctly anticipated that significant cost savings in the first year could have two effects. First, its superior performance might prompt the GIC to raise its expectation about cost saving potentials. A likely consequence was that GIC would lower the target rate. This phenomenon of superior contract performance resulting in more demanding terms in the future is called the "ratchet effect" in the contracting literature (see Laffont and Tirole, 1986, for example). Second, Options might think that it could convince the GIC that its value to the behavioral mental health carve out was high by demonstrating excellent performance in the first fiscal year. This could enhance Options's bargaining power in the contract renewal for the third year. In addition, it might also be a good signal to the market, so that Options's prospect of winning new contracts would be improved. We will call this the "reputation effect."

Clearly, the ratchet and reputation effects act against each other: the former induces Options to lower its performance, but the latter provides the opposite inducement. We can argue that Options in fact chose a performance level that traded off these two opposing effects. It was interesting to observe that the target rate was lowered in the second year by about 25% (in normal terms), and further reduced in the third year, but the administrative fee was reduced by a little in the second year, and then raised significantly in the third year.

From the perspective of incentives, the existence of a penalty for cost levels that are above the target does not necessarily imply that the target level will be achieved. In fact, Options might optimally choose to violate the target, incurring some penalty while saving administrative expenses. Nevertheless, the contract did not provide any incentive for Options to lower costs below the target level, since Options was unable to keep any savings. Therefore, it seems to us that what needs to be explained was the fact that Options achieved much more: in each of the years after the carve out, the actual costs were lower than the target level by a significant amount. Here, our hypothesis is that the reputation effect initially dominated the ratchet effect: for small cost reductions beyond the target level, Options's reputation began to build up, but the ratchet effect did not become important until significant savings beyond the target level was attained.

To understand the impact of the carve out, it is important to distinguish different two sets of relationship changes. First, Options was brought in to implement the provision of MHSA services by managed care. Whereas before the carve out, only those enrollees with the HMOs had their care delivered via managed care, all enrollees were under the management of Options since the carve out. This is a form of demand-side management. Second, Options set up a network of providers for enrollees. Before the carve out, providers negotiated individually with the GIC. After the carve out, Options, on behalf of the GIC, centralized all negotiations with providers. This affects the supply side. The first change may have the effect of reducing inappropriate use of MHSA services, since preadmission authorization, utilization review, and other monitoring may deter or screen out some demands for services. The centralization of bargaining makes Options a "monopsonist" buyer with market power, and enables it to use the size of the GIC population to secure a lower price from providers.

The above arguments suggest the following decomposition analysis. Consider any single type of service, say an outpatient visit. By definition, the total cost of this service in a given period of time is equal to the total number of times this service is used multiplied by the average price of each service. A reduction in total cost of this service can come about through a reduction in the quantity, the price, or both. From the claims data, we calculate the total number of outpatient visits for the periods before and after the carve out. Using the data of outpatient costs, we can estimate the average price per visit. For inpatient services, we calculate LOS of each episode and obtain the average LOS by dividing by the number of inpatient episodes. Using the inpatient costs data, we then estimate the average price per inpatient day. As it turns out, after the carve out, the claims data separated out from all inpatient services an additional class: inpatient service at an alternative setting. These are inpatient services performed at a less intensive setting such as residential facility, partial facility, intensive outpatient, residential professional and partial professional settings.

Table 5 and 6 present the decomposition of MHSA outpatient services and costs. For the continuously enrolled population, we estimate the prices per MHSA outpatient visit by dividing the total outpatient plan costs (after discarding outliers that may simply reflect adjustments to previous claims) by the total number of visits. We express the estimates both in terms of current year dollars and constant 1995 dollar. Table 5 shows an upward trend for MH outpatient prices, but a downward trend for SA. Nevertheless, we should note that the outpatient coverage of MH was significantly improved after the carve out; before the carve out, MH outpatient coverage was at 50% while SA at 80%. Table 6 presents the our own analysis and that from Options on number of admissions and average LOS per admission. While the data we received from MEDSTAT gave us numbers of admissions that were comparable to those Options reported, the total number of inpatient days were higher from our own analysis. Furthermore, we were unsuccessful in decomposing from our data total inpatient days into "conventional" and "alternative setting" inpatient services. Nevertheless, there is a slight decrease in the total of admissions as well as the ALOS in both analyses. From Table 5 suggests that the dramatic decrease in outpatient costs could be due to reduction in quantities, since "prices" either increased or remained relatively stable. On the other hand, Table 6 suggests that the reduction in inpatient plan costs mainly could be a result of price reduction, since numbers of admissions as well as ALOS did not decreaseas much as the total plan costs.


CONCLUSIONS


NOTES

  1. For other examples, see Alexander Consulting Group (1990) on McDonnell Douglas; Altman and Price (1993) on Alcan; and Umland (1995).
  2. According to the contract, a PIP is a covered person who is an employee, a retired employee (of various classes), a covered student age 24 or over, an individual not part of a family unit covered under some continuation provision (see Appendix D of the Agreement for Managed Mental Health Services by and between Commonwealth of Massachusetts Group Insurance Commission and Options Incs. 1993). Thus, the total number of PIPs does not correspond to the total of all enrollees; rather each PIP roughly corresponds to a unique employee identification number in the enrollment records. In particular, spouses and most dependents are not PIPs.
  3. We actually selected these enrollees by identifying contracts with months of enrollment of 46 or greater of a possible 48.
  4. Some cost shifting between MHSA and general medical care is possible. For instance, inpatient treatment for alcohol abuse could be reclassified by a clinician as treatment for gastrointestinal problems and paid for under the general health insurance benefit. We are not in a position to evaluate how much of such cost shifting has occurred. For study of this in another context, see Norton et al. (1996).
  5. Active employees, retiree and survivors, and all groups.
  6. In many instances, potential vendors were asked to justify their projections, or to provide information on the basis of which those calculations were obtained.
  7. It is unclear whether any outside arbitration would be allowed.
  8. The benefit and enrollees' out-of-pocket payment designs for fiscal years 93-94 and 94-95 are identical.
  9. An implementation fee was also paid by the GIC in the first few months. This was calculated at $.35 per PIP per month.
  10. See Merrick (1996) for more discussion of the performance targets.


REFERENCES

Altman, L. And W. Price. "Alcan Aluminum: Development of a Mental Health 'Carve Out'." New Directions for Mental Health Services, Fall 1993, pp.55-65.

Alexander Consulting Group. "The Impact of the ASSIST Program During 1989 at the McDonnell Douglas Helicopter Company." Health Straties Group, May 1990, Westport, CT.

Battagliola, Monica. "Breaking with Tradition." Business and Health, June 1994, pp.53-56.

Frank, Richard G., Haiden A. Huskamp, Thomas G. McGuire, and Joseph P. Newhouse. "Some Economics of Mental Health Carve Outs." Archives of General Psychiatry, forthcoming, 1996.

Frank, Richard G. And Thomas G. McGuire. "Massachusetts Medicaid..." Psychiatric Services, forthcoming, 1996.

Frank, Richard G., Thomas G. McGuire, and Joseph P. Newhouse. "Risk Contracts in Managed Mental Health Care." Health Affairs, 1995, 14:3, pp.50-64.

General Insurance Commission, Commonwealth of Massachusetts. "Request for Proposal for Integrated Employee Assistance and Mental Health and Substance Abuse Program." October 16, 1992.

Grazier, K.L., R.M. Scheffler, S. Bender-Kitz, and P. Chase. "The Effect of Managed Mental Health Care on Use of Outpatient Mental Health Services in and Employed Population." In R.M. Scheffler and L.F. Rossiter, Advances in Health Economics and Health Services Research, 1993, Volume 14, pp.71-78, Greenwich, CT: JAI Press.

McGuire, Thomas G. Financing Psychotherapy: Costs Effects and Public Policy, 1981, Ballinger Publishing, Cambridge.

Merrick, Elizabeth. "Dissertation draft." 1996, Brandeis University.

Oss, Monica. "Managed Behavioral Health Market Shares in the United States." Open Minds, 1994, Gettysburg, PA.

Umland, Beth. "Behavioral Healthcare Benefit Strategies of Self-Insured Employers." Behavioral Healthcare Tomorrow, November/December 1995, pp.65-70.

TABLE 1. Mental Health and Substance Abuse Costs
Entire Set of Enrollees FY 92 FY 93 FY 94 FY 95
Average monthly PIPs (92 is est)
Average monthly enrolled
69,440
101,373
69,212
101,012
81,571
128,496
81,062
127,486
Total cost
Total plan cost
$22,345,087
$16,928,806
$20,001,460
$14,817,617
$12,429,902
$9,316,278
$9,710,747
$7,290,191
Total cost per PIP per month
Plan cost per PIP per month
$26.82
$20.32
$24.08
$17.84
$12.70
$9.52
$9.98
$7.49
Total cost per enrollee per month
Plan cost per enrollee per month
$18.37
$13.92
$16.50
$12.22
$8.06
$6.04
$6.35
$4.77


TABLE 2. Mental Health and Substance Abuse Costs (adjusted for inflation, in 1995 $)
Continuously Covered Enrollees FY 92 FY 93 FY 94 FY 95
Average monthly PIPs
Average monthly enrolled
26,887
39,541
26,887
39,541
26,887
39,541
26,887
39,541
Total cost
Total plan cost
$14,103,476
$10,455,369
$11,915,996
$8,467,091
$6,331,853
$4,601,074
$4,697,196
$3,898,639
Total cost per PIP per month
Plan cost per PIP per month
$43.71
$32.41
$36.93
$26.24
$19.62
$14.26
$14.56
$12.08
Total cost per enrollee per month
Plan cost per enrollee per month
$29,72
$22.03
$25.11
$17.84
$13.34
$9.70
$9.90
$8.22


TABLE 3. Inpatient and Outpatient Costs
Continuously Covered Enrollees FY 92 FY 93 FY 94 FY 95 % Change
Total outpatient cost
Plan outpatient cost
$8,120,662
$4,577,179
$7,714,771
$4,394,690
$4,187,579
$2,647,443
$2,983,368
$2,068,618
0.55
0.47
Total inpatient cost
Plan inpatient cost
$5,982,814
$5,878,191
$4,201,225
$4,072,402
$2,144,274
$1,953,631
$1,713,828
$1,830,021
0.62
0.62


TABLE 4. Breakdown of Mental Health and Substance Abuse Costs
Continuously Covered Enrollees FY 92 FY 93 FY 94 FY 95 % Change
Plan total outpatient MH cost
Plan total outpatient SA cost
$4,291,262
$285,917
$4,056,528
$338,162
$2,547,510
$99,932
$1,835,488
$71,890
0.47
0.72
Plan total inpatient MH cost
Conventional inpatient MH
Alternative level MH
$4,689,307 $3,246,222 $1,605,253
$1,425,635
$173,575
$1,294,947
$1,112,972
$176,184
0.63
Plan total inpatient SA cost
Conventional inpatient SA
Alernative level SA
$1,188,883 $826,180 $332,671
$292,813
$39,740
$323,205
$276,173
$46,993
0.67
NOTE: Inpatient MH, inpatient SA cost figures are from service claim file.


TABLE 5. Price Estimates of Outpatient Mental Health and Substance Abuse
Current Year Dollar FY 92 FY 93 FY 94 FY 95
Continuous set: MH outpatient
Continuous set: SA outpatient
$40.29
$56.27
$42.68
$59.02
$54.23
$53.08
$52.95
$53.11
Contant 1995 Dollar FY 92 FY 93 FY 94 FY 95
Continuous set: MH outpatient
Continuous set: SA outpatient
$46.52
$64.98
$46.59
$64.43
$56.49
$55.29
$52.95
$53.11


TABLE 6. Inpatient Quantity of Mental Health and Substance Abuse
Data from MEDSTAT FY 92 FY 93 FY 94 FY 95
Number of admissions
Total number of days
ALOS
944
13,098
13.88
876
10,443
11.92
1,007
13,827
13.73
985
10,934
11.10
Data from OPTIONS Annual Report FY 92 FY 93 FY 94 FY 95
Number of admissions
Total number of inpatient days
Total number of alternative setting days
Total number of days
ALOS (counting only inpatient days)
ALOS (counting all days)
    1,079
9,121
3,211
12,332
8.4
11.43
969
7,031
3,190
10,221
7.2
10.55




[Table of Contents]


Enrollment Duration, Service Use, and Costs of Care for Severely Mentally Ill Members of a Health Maintenance Organization

Bentson H. McFarland, M.D., Ph.D.; Richard E. Johnson, Ph.D.; and Mark C. Hornbrook, Ph.D.
Archives of General Psychiatry 53:938-944 (October 1996)

Background: The rapid growth of prepaid health care and the increasing enrollment of Medicaid clients in health maintenance organizations (HMOs) raise concerns about the adequacy of services for persons with severe mental illness in capitated health plans. Uncontrolled studies have suggested that enrollment of HMO members with mental illness may be prematurely terminated.

Methods: We identified 250 adult Kaiser Permanente Northwest Region (Portland, OR) members who were enrolled during 1986 or 1987 and had chart diagnoses of schizophrenia or bipolar disorder. Severely mentally ill subjects were matched by age and sex with control HMO members with and without diabetes mellitus. Records of the HMO and the state mental health agency were reviewed to determine HMO enrollment duration, private and public service utilization, and HMO costs of care during the 4-year follow-up period.

Results: The severely mentally ill subjects had 42 months of HMO enrollment during the follow-up period compared with 37 months for the controls without diabetes mellitus and 47 months for the patients with diabetes mellitus (P<.001). When HMO enrollment prior to the study was taken into account, the severely mentally ill subjects and those with diabetes mellitus had similar membership duration. Among the severely mentally ill subjects, community mental health service use was related to longer duration of HMO enrollment (P<.05) but HMO costs of care per member per month were not related to retention. The severely mentally ill subjects were high users of mental health services but their use of general medical care was similar to that of the controls without diabetes mellitus.

Conclusions: This controlled study found no evidence for early termination of HMO members with costly mental illness. Use of community mental health care was associated with longer duration of HMO enrollment.

The dramatic growth in health maintenance organization (HMO) enrollment has heightened concern about the adequacy of treatment available for persons with severe mental illness in prepaid systems.1, 2 This topic is of particular interest to the dozens of states3, 4 that are now in the process of replacing fee-for-service with capitated health care systems for Medicaid clients, many of whom have severe mental disorders.5 Indeed, Mechanic6 has suggested that public mental health programs should be gradually integrated into the larger, prepaid health care system while bearing in mind the many challenges involved.7 Conversely, Scheffler et al.8 have recommended that programs for persons with severe mental illness remain "carved out" of general health care. Furthermore, editorial writers have claimed that traditional HMOs "disenroll individuals who develop serious mental disorders"9 and have stated that "HMOs have routinely excluded any coverage of chronic mental illness."10 On the other hand, HMOs have also been described in which persons with severe mental illness "receive relative priority."11 Inconveniently, there have been few empirical data with which to inform this debate.1, 2

One of the few pertinent studies is the 1987 Minnesota project, which included a comparison of health status for chronically mentally ill Medicaid clients who had been randomized to fee-for-service vs prepaid (HMO) health care.2, 12, 13, 14 Unfortunately, the project ended prematurely after only a year of operation. Few if any differences were found for chronically mentally ill persons, although the subset of this group with schizophrenia may have been adversely affected by assignment to the independent practice association model HMOs that participated in the project.2, 14

Somewhat related to this issue is the RAND observational Medical Outcomes Study,15, 16 which raised the possibility that during 1986 through 1988 psychiatric patients with major depressive disorder in prepaid health care may have switched insurance coverage (i.e., terminated HMO enrollment) sooner than their counterparts in the fee-for-service sector. It was suggested that the limited mental health services provided to these subjects (referred to as HMO "skimping") may have contributed to their departure from the HMO.16, 17 However, the Medical Outcomes Study lacked a control group within the HMO.

To address these issues, we conducted a multiyear longitudinal cohort study of HMO members with severe mental illnesses such as schizophrenia or bipolar disorder. Based on the existing literature,9, 15 we hypothesized that the severely mentally ill HMO members would disenroll earlier than their lower-cost counterparts.9, 10 We also wished to learn if there was a relation between HMO members' use of public mental health services and their duration of enrollment.


METHODS

Study Site

The study was conducted in the Northwest Region of Kaiser Permanente, a nonprofit, prepaid, group-practice HMO that currently serves some 385000 members in greater Portland, OR. The HMO has been in operation for over 50 years, provides comprehensive medical benefits, and includes a specialty mental health department presently consisting of about 20 psychiatrists and 80 other mental health professionals.18 The HMO's mental health and substance abuse benefits conform to those mandated by Oregon law. Since 1987, Oregon insurers have been required to cover up to $2000 of outpatient and up to $8500 of inpatient, residential, or day treatment mental health and/or substance abuse services every 24 months for adult beneficiaries. The HMO allows substitution of inpatient for outpatient benefits. However, the total adult mental health and/or substance abuse benefit is a maximum of $10500 per 24 months. In addition, the vast majority of HMO members have a pharmacy benefit. A 1995 survey of the membership showed that 84% of enrollees obtain all of their prescriptions and 12% obtain some or most of their prescriptions (including those written by non-HMO clinicians) at the HMO's pharmacies. The HMO maintains a membership information processing system that records eligibility for services based on monthly premium payments. Administrative personnel attempt to contact individuals whose premiums are unpaid. For purposes of this study, disenrollment was defined to have occurred at the beginning of a 90-day or longer period of ineligibility. The project was reviewed and approved by the Kaiser Permanente Northwest Region Committee for the Protection of Human Subjects on February 16, 1995.

Selection of Subjects

The years 1986 and 1987 were chosen as a baseline period so that this project could be compared with earlier work.2, 12, 13, 14, 15, 16 Because the HMO's outpatient charts were not computerized at the time, severely mentally ill subjects were selected from the 2334 persons who received an antipsychotic drug (excluding prochlorperazine and thiethylperazine, which are used in the HMO only for treatment of nausea and vomiting) or lithium from an HMO pharmacy during 1986 or 1987; individuals in the original group who also received anticancer drugs or drugs used in the treatment of acquired immunodeficiency syndrome were excluded. To minimize the numbers of subjects who might have conditions such as Alzheimer disease, the study focused on the 733 potential subjects who were between ages 10 and 46 years in 1986. Of this group, 526 had mental health department charts (indicating they had had at least 1 contact with an HMO mental health specialist at some time). Individuals were then randomly selected from these 526 persons for mental health chart abstraction. Subjects who carried chart diagnoses of bipolar disorder (including mania, manic-depression, and hypomania) or schizophrenia (including schizophreniform disorder and schizoaffective disorder) in the mental health record were retained in the study. Mental health chart abstraction proceeded through 440 charts until 250 subjects meeting these inclusion criteria were located. Persons who were excluded at this stage typically had diagnoses of substance abuse (primarily amphetamines, cocaine, and/or alcohol) or psychotic depression. Since this study was designed to be descriptive in nature, the sample size of 250 was selected so that the SEs of the mean of annualized utilization estimates (measured in office visits per person per year) would be less than 10% of the estimated mean value. As in other record review projects, diagnoses were assigned based on the majority of those found in the subjects' mental health charts.19, 20 This group of subjects was labeled "cohort 1."

Control Members With and Without Diabetes Mellitus

The severely mentally ill subjects in cohort 1 were then matched with other HMO members. The "pharmacy" controls were taken from the population of HMO members who used the system's outpatient pharmacies during 1986 or 1987 (and had not received an antipsychotic drug or lithium). This group included some two-thirds of the HMO's membership. The "membership" controls were selected from the HMO's enrolled population during 1986 and 1987, which averaged about 290000 persons on any given day at that time. Subjects were matched for sex, year of birth, and "coverage status" (i.e., whether the subject was a subscriber or a dependent of the subscriber). For studies of the enrollment duration of cohort 1, the subjects were also matched for sex and year of birth (within 5 years) with 234 people selected from the 2140 individuals who were HMO members during 1986 or 1987 and who had been discharged by a general medical-surgical unit (in 1986 or 1987) with a diagnosis of diabetes mellitus.

Service Utilization

Cohort 1 subjects' HMO service utilization data were obtained from 1986 through 1990 record reviews and computerized databases. In addition, the names and dates of birth for all subjects without diabetes mellitus in cohort 1 were matched against state mental health agency computerized utilization data. The state agency provided information about subjects' use of community mental health programs and the state mental hospitals from 1986 through 1990. While there were extensive data on state hospital usage (including dates of admission and discharge, diagnoses, and so forth) the community mental health data were limited to enrolled vs not enrolled during particular time periods. The Chronic Disease Score21, 22 (based on nonpsychotropic drug dispensing) was used to gauge the severity of physical illnesses in subjects from cohort 1 without diabetes mellitus.

Costs

The HMO's accounting data and Medicare cost reports became available in 1987 and were used to calculate cost coefficients for each unit of service (e.g., outpatient visit to a provider, day in a medical-surgical unit, and so on). The cost coefficients were then multiplied by units of service for cohort 1 to determine the cost (in 1990 dollars) for each type of care.23, 24 Billing records were used to determine the costs (in 1990 dollars) of services purchased by the HMO (e.g., general hospital inpatient psychiatric care) for members of cohort 1. Public sector costs were not available.

Secular Trends in Enrollment Duration

To address possible secular trends in enrollment duration, a second group of severely mentally ill subjects (labeled "cohort 2") was chosen from the HMO members discharged from a general hospital during 1990 through 1992 with diagnoses of schizophrenia or bipolar disorder. These people were matched for age and sex with HMO controls with and without diabetes mellitus as described for cohort 1. The enrollment duration study focused on the 165 female and 116 male (average age, 31 years in 1990) severely mentally ill subjects in cohort 2 who were between the ages of 10 and 46 years at the time of the index hospital discharge, of whom there were 139 with a diagnosis of schizophrenia and 5 who also had a diagnosis of diabetes mellitus. Follow-up for cohort 2 started with the index hospital discharge and ended December 31, 1995.

Statistical Analysis

Service utilization and cost data for cohort 1 are reported on a per member per month of enrollment basis. In 2-way analyses of variance (ANOVA), data were transformed as needed so that the residuals were roughly normally distributed. For example, the total cost per person per month was transformed by adding 1 to the cost numerator, dividing by the months of enrollment denominator, and then taking the logarithm of that ratio. To account for multiple comparisons, the studentized range test was used to compare the cohort 1 severely mentally ill subjects' utilization and costs with those of the controls.25 Enrollment duration comparisons used the log-rank test and the Cox proportional hazards model stratified to account for the matching.26 Changes in coverage status (subscriber vs dependent) were examined using the Miettinen method.27

Cox proportional hazards models were used to examine factors associated with retention of cohort 1 severely mentally ill subjects in the HMO during the follow-up period from 1986 through 1990.26 Blocks of potential predictors were planned for stepwise inclusion in the proportional hazards models. These potential predictor variables were demographics (age, sex, schizophrenia vs bipolar disorder); enrollment status at the start of the study (subscriber vs dependent, Medicare vs no Medicare, Medicaid vs no Medicaid, years of HMO enrollment prior to the start of the study); and utilization (state hospital admission at any time while an HMO member during the study period, use of community mental health services while an HMO member at any time during the study period, total HMO costs of care per member per month, and HMO mental health costs of care per member per month).


RESULTS

Demographics

In cohort 1 there were equal numbers of males and females. Subjects in cohort 1 were (on average) 32 years old in 1986, with an age range from 13 to 45 years and an SD of 8 years. The ethnicity distribution was 80% white, 5% African American, 2% Asian American, 2% Hispanic, and 12% unknown. There were no differences in the distributions of know ethnicity between the severely mentally ill subjects and the controls. Some 30% of the 250 severely mentally ill persons in cohort 1 (for whom data were available) had never married. In contrast only 12% of the controls (for whom data were available) had never married. At the beginning of the study about half (53%) of the 750 subjects without diabetes in cohort 1 were subscribers, while 44% were dependents and the remaining few were nonmembers. Only 12% of the cohort 1 severely mentally ill subjects changed coverage status from dependent to subscriber during the 4-year follow-up period, compared with 22% of the controls without diabetes mellitus (relative risk, 0.53; 95% confidence interval, 0.30-0.92). The severely mentally ill subjects in cohort 1 were much more likely to have Medicare coverage than the controls without diabetes mellitus (10% vs 0.2%, P<.001 by Fisher exact test). There was no difference in the prevalence of Medicaid coverage (5% vs 4%).

The 250 severely mentally ill subjects in cohort 1 had lengthy histories of mental illness. At the time of their first HMO mental health department contact, the vast majority (73%) reported having had at least 1 previous psychiatric hospitalization, with 40% of severely mentally ill subjects reporting 3 or more admissions. Many (41%) were known to have been admitted to a state mental hospital in Oregon. The majority (57%) had had contact with the HMO's emergency psychiatric service at some time during their enrollment.

Diagnoses

The diagnostic algorithm showed that 79 (32%) of the 250 severely mentally ill subjects in cohort 1 had chart diagnoses of schizophrenia, 98 (39%) had bipolar disorder, and the remaining subjects had multiple diagnoses. As expected, 92% of the 98 persons with bipolar disorder had received prescriptions for lithium, while 93% of the 79 subjects with schizophrenia had been dispensed antipsychotic drugs. Some 30% of the bipolar subjects had received antipsychotic drugs as well as lithium.

Service Use

Health care utilization data for the 1986 through 1990 study period are presented in Table 1. Not surprisingly, the severely mentally ill HMO members utilized greater amounts of services than did the controls without diabetes mellitus. As expected, the severely mentally ill subjects had greater per member per month use of mental health [F(2498)=120.1, P<.001] and substance abuse outpatient services [F(2498)=6.5, P<.003] as well as greater use of general hospital psychiatric inpatient services [F(2498)=86.3, P<.001]. During the study period, 88 (35%) of the severely mentally ill subjects in cohort 1 had 274 general hospital psychiatric admissions while the pharmacy controls had none and the membership controls had 1.

Interestingly, there were no statistically significant differences among the 3 groups without diabetes mellitus in the per member per month use of general medical outpatient services. However, differences were observed with respect to use of general medical-surgical inpatient care [F(2498)=4.5, P=.01]. The studentized range test indicated that the severely mentally ill subjects' use of general medical-surgical inpatient care was equivalent to that of the pharmacy controls.

The Chronic Disease Score (based on pharmacy data other than psychotropic drugs for the 665 subjects without diabetes mellitus enrolled in 1986) showed that the severely mentally ill subjects had the highest score (mean=0.48, SD=1.18), followed by the pharmacy controls (mean=0.31, SD=0.92), who were in turn followed by the membership controls (mean=0.15, SD=0.65). These differences are highly statistically significant (2-way ANOVA F[2498]=7.9, P<.001). Because the Chronic Disease Score was not normally distributed, we also examined the percentage of each group with a nonzero score (47 [20%] of 231 severely mentally ill subjects, 34 [15%] of 225 pharmacy controls, and 16 [8%] of 209 membership controls). These frequency differences were also highly statistically significant (X2=14.3, df=2, P<.001).

During their HMO enrollment in the follow-up period, 30 (12%) of the severely mentally ill subjects in cohort 1 were admitted to a state mental hospital compared with 3 (1%) of the pharmacy controls and 1 (0.4%) of the membership controls (X2=48.5, df=2, P<.001). Similarly, 101 (41%) of the severely mentally ill subjects in cohort 1 used community mental health services during the follow-up period compared with 12 each (5%) among the pharmacy and membership controls (X2=152.7, df=2, P<.001).

Costs

Table 2 and Table 3 show the HMO costs of care per member per month for the subjects without diabetes mellitus in cohort 1. The vast majority (98% of the severely mentally ill subjects, 95% of the pharmacy controls, and 87% of the membership controls) incurred HMO costs. The severely mentally ill subjects had substantially higher HMO costs of care per member per month of enrollment than did the controls without diabetes mellitus. The average cost for the subjects with severe mental illness was $380 (median of $203) per member per month vs an average of $149 (median of $33) for the pharmacy controls and $90 (median of $23) for the membership control subjects [2-way ANOVA on the transformed total cost F(2419)=81.4, P<.001]. The studentized range test showed that the 3 groups were all statistically significantly different from one another at the P=.05 level.

Looking in more detail at costs per member per month for the severely mentally ill subjects showed that the median combined mental health cost (inpatient, outpatient, and pharmaceutical) was $99 with the median, excluding psychotropic pharmaceuticals, at $74. Median outpatient mental health cost was $48. The 90th percentile figures were $798 per member per month for total costs, $544 for all mental health costs, $492 for mental health costs excepting psychotropic medications, $284 for inpatient care, and $214 for outpatient mental health costs.

Enrollment Duration

The Kaplan-Meier product-limit estimates in the Figure show the retention of cohort 1 subjects in the HMO from the start of time under observation (in 1986 and 1987) until disenrollment or the end of follow-up on December 31, 1990. Mean enrollment duration for cohort 1 is shown in Table 4. The enrollment durations of the cohort 1 groups differ significantly (log-rank X2=40.7, df=3, P<.001). The stratified Cox model showed that the most powerful predictor of enrollment duration was not being in the membership control group (X2=25.1, df=1, P<.001), with the next most powerful predictor being years of HMO enrollment prior to entering the study (X2=17.8, df=1, P<.001). Once prior years of HMO enrollment had been taken into account, there were no statistically significant enrollment differences among those subjects with diabetes mellitus, severe mental illness, and pharmacy controls in cohort 1. Table 4 also shows that the enrollment duration of cohort 2 subjects was similar to that of cohort 1.

Retention

Among the severely mentally ill cohort 1 subjects, stepwise Cox proportional hazards modeling showed that the factors related to longer duration of enrollment in the HMO were years of HMO enrollment prior to the start of the study period (X2=7.6, df=1, P<.006); age (X2=5.6, df=1, P<.02); and community mental health service use (X2=3.9, df=1, P<.05).

Costs of care (total costs per member per month or mental health costs per member per month) for cohort 1 were not significantly related to retention based on the Cox proportional hazards modeling. Other factors not significantly related to cohort 1 enrollment duration in the proportional hazards models included sex, schizophrenia vs bipolar disorder, subscriber status, or use of the state hospital.


COMMENT

Results from this study need to be interpreted in light of its design. The project was not a randomized trial nor did it include a comparison group of subjects outside the HMO. Since the study was designed to take advantage of existing data, subjects were not interviewed and clinical outcomes were not measured. Consequently, there could well have been important but unrecorded differences among the groups. Furthermore, subjects' reasons for disenrollment and for use of public mental health services were not available.

The project examined "prevalent" cases of people with severe mental illness who were using HMO services. At the time of this study it was not possible to identify HMO members with newly emerging (i.e., "incident") psychosis. Certainly, the "careers" of severely mentally ill persons who do not receive treatment may well be different from those of the subjects described here. For example, persons who become psychotic and refuse HMO mental health services might be unable to maintain enrollment and quickly leave the organization. Indeed, earlier work has shown that the treated prevalence of schizophrenia within this HMO is less than what would be expected from Epidemiologic Catchment Area data, although the treated prevalence of bipolar disorder is comparable to the national estimate.18 Very recent improvements in the HMO's automated data systems may provide an opportunity to conduct an incidence study focusing on people with newly emerging psychosis.

Another issue is the degree of severity of the subjects' mental disorders. For example, some 67% of the cohort 1 severely mentally ill subjects were self-reported to be employed at the time of their first HMO mental health clinic visit. Interestingly, the Epidemiological Catchment Area project found that 43% of the persons identified in that study as having schizophrenia were employed.28 The severely mentally ill HMO members may be that subset of persons with conditions like schizophrenia, who have a relatively good prognosis.29, 30, 31, 32, 33, 34, 35, 36, 37

Nonetheless, the frequent use of emergency and inpatient psychiatric services for this population suggests that many of these individuals were, indeed, severely disabled. Furthermore, the Chronic Disease Score indicated that the severely mentally ill persons appeared to have had physical as well as mental health problems. These individuals were also much more likely to have Medicare coverage than the controls without diabetes mellitus. Presumably, the severely mentally ill subjects became eligible for Medicare coverage by virtue of qualifying for Social Security Disability Insurance due to their mental illness.38 The relatively low rate of Medicaid participation by the severely mentally ill subjects in cohort 1 may well have been due to state policies at the time of the study, which, in effect, deemed persons receiving Social Security Disability Insurance to be "too wealthy" for Medicaid.

Relatively few of the severely mentally ill subjects in cohort 1 (compared with the controls without diabetes mellitus) changed coverage status from dependent to subscriber during the 4-year follow-up period. One explanation for these findings is that the severely mentally ill subjects who entered the study as dependents were not as likely as their matched controls to obtain competitive employment (and thereby become subscribers in their own right). Indeed, naturalistic follow-up studies of patients with mania suggest that significant disability would be expected for at least some of those severely mentally ill HMO subjects who had bipolar disorder.39, 40

Its limitations notwithstanding, this study showed that HMO members with severe mental illness had enrollment duration longer than that of controls without diabetes mellitus but somewhat shorter than that of members with diabetes mellitus. Furthermore, costs to the HMO were unrelated to duration of enrollment. To the authors' knowledge, cohort 1 has been followed up longer than any group of mainstream managed care beneficiaries with severe mental illness. This study is also one of the few that measured both private and public mental health service use.13 In contrast to the Medical Outcomes Study,15, 16, 17 this project involved a variety of HMO control subjects.

It is worthwhile examining the factors that did and did not explain the severely mentally ill subjects' retention within the HMO. There was no support for the contention that HMO members were "disenrolled" due to severe mental illness.9 Of course, as expected in a "prevalence" study, subjects with very brief periods of enrollment were unlikely to be included in the sample. Consequently, length of HMO eligibility prior to the study was a good predictor of enrollment duration during follow-up. Indeed, when length of enrollment before the study period was included in the Cox proportional hazards analysis, the severely mentally ill subjects had retention times longer than the membership controls but equivalent to that of the diabetic subjects and the pharmacy controls.

We were also unable to find evidence that this HMO "routinely excluded any coverage of chronic mental illness."10 Indeed, the severely mentally ill subjects in cohort 1 were provided amounts of service that generated costs to the HMO several times that of the membership controls. This cost difference was accounted for chiefly by mental health care. Based on the HMO's cost data, it appears that 36% of the severely mentally ill subjects in cohort 1 exceeded the state-mandated outpatient mental health benefit of $2000 per 24 months. Psychiatric inpatient costs were generally less than the state-mandated $8500 per 24 months, but 9% of severely mentally ill cohort 1 subjects did exceed the benefit limit. Looking at combined inpatient and outpatient mental health costs showed that 12% of severely mentally ill cohort 1 subjects exceeded the $10500 per 24 months limit. Of course, one could challenge the accuracy of the cost data. However, it should be noted that some of the costs (e.g., general hospital inpatient psychiatric services) represent payments from the HMO to its vendors. In any event, it seems clear that coverage was provided to HMO members who were severely mentally ill. Furthermore, HMO costs were not related to enrollment duration.

An important issue is the HMO's policies toward serving persons with severe mental illness. As with many HMOs, this organization's mental health services were theoretically limited to treatment of conditions that, in the judgment of the attending physician, were subject to significant improvement through relatively short-term therapy.41 In practice, as demonstrated by these results, mental health services were provided to persons with chronic conditions. Since this approach to persons with severe mental illness may not be found in other HMOs, these results may have limited generalizability.42, 43, 44

Indeed, the distinctions among HMOs44 may explain the apparent discrepancy between the retention data from this project and the implication from the Medical Outcomes Study15 that severely mentally ill subjects would have a shorter enrollment than healthier members. It should be noted that the Medical Outcomes Study was conducted in several prepaid settings (including a traditional staff model HMO), with the poorest outcomes for depressed psychiatric patients observed in independent practice associations.17 Differences between the independent practice association approach to severe mental illness and that provided by traditional HMOs could be responsible for the disparate outcomes observed in the 2 studies. As Judith L. Feldman, MD, remarked: "When you've seen one HMO you've seen one HMO" (oral communication, 1988).

The integrated service delivery system provided by traditional HMOs may be of particular value for severely mentally ill members who have physical as well as mental health problems, as suggested by our data. It is interesting to note that the costs of general medical-surgical care for severely mentally ill subjects were similar to those of the pharmacy controls even though the Chronic Disease Score suggested that the former had more physical illness than the latter. An integrated system might be more efficient than a mental health "carve-out" for people with both physical and severe mental health problems. On the other hand, while the data from cohort 2 suggest that this HMO is continuing to serve severely mentally ill members, the now fiercely competitive health care environment45 makes one wonder if any HMO will be able to provide the level of mental health service described here.

It should be pointed out that the HMO was by no means the sole provider of mental health care to these individuals. Nearly half of the severely mentally ill subjects in cohort 1 also used community mental health services. Furthermore, the use of community mental health care was associated with longer duration of HMO enrollment. While this observational study cannot determine causality, it is conceivable that the subjects who maintained their HMO membership were also to optimize use of both private and public services. One might imagine that the HMO's expertise in areas such as psychopharmacology, emergency psychiatric services, and inpatient psychiatric care could complement the public mental health sector's capabilities in fields such as rehabilitation and vocational training. Unfortunately, shrinkage of public sector mental health funds combined with private sector competition may leave persons with severe mental illness struggling to find appropriate care.46 Nonetheless, there may be considerable value in studying ways HMOs and community mental health agencies can work together to offer an efficiently integrated package of services that will benefit people with severe mental illness.6


NOTES

From the Kaiser Permanente Center for Health Research (Drs McFarland, Johnson, and Hornbrook) and Oregon Health Sciences University (Dr. McFarland), Portland.

Accepted for publication June 21, 1996.

Supported in part by grants P50 MH43458, R01 MH45015, and K02 MH01238 from the National Institute of Mental Health, Bethesda, MD.

Presented in part at the 147th Annual Meeting of the American Psychiatric Association, Philadelphia, PA, May 25, 1994, and at the 123rd Annual Meeting of the American Public Health Association, San Diego, CA, November 1, 1995.

Reprints: Bentson H. McFarland, MD, PhD, Center for Health Research, Kaiser Permanente, Northwest Region, 3800 North Kaiser Center Drive, Portland, OR 97227.

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  46. McFarland, B.H. "Ending the Millennium: Commentary on HMOs and the Seriously Mentally Ill: A View from the Trenches." Community Mental Health Journal, in press.
TABLE 1. Service Utilization*
Number (Percent)
Service Severely Mentally Ill Subjects
(n=250)
Pharmacy Controls
(n=250)
Membership Controls
(n=250)
Inpatient Admissions
- Medical-surgical
- Psychiatry
- State hospital
 
11 (27)
31 (66)
6.1 (32)
 
15 (48)
0
0.88 (11)
 
5.9 (18)
0.096 (1.5)
0.068 (1.1)
Outpatient Visits
- General medical
- Mental health
- Substance abuse
 
770 (1010)
460 (560)
27 (110)
 
770 (1130)
8.7 (46)
7.3 (64)
 
610 (920)
18 (140)
4.9 (32)
Used Community Mental Health Program 101 (40) 12 (5) 12 (5)
* Services per 1000 member-months of health maintenance organization enrollment. All data are presented as mean (SD) unless otherwise indicated. Data were collected from 1986 through 1990.


TABLE 2. Costs of Care, 1987 Through 1990
Number (Percent)
Service Mean (SD) Cost Per Member Per Month, 1990 $
Severely Mentally Ill Subjects
(n=225)
Pharmacy Controls
(n=223)
Membership Controls
(n=218)
Inpatient
- Medical-surgical
- Psychiatry
- Substance abuse
 
59 (182)
118 (317)
2 (12)
 
77 (531)
0
0.1 (1)
 
35 (147)
0.4 (6)
0
Outpatient
- General medical
- Mental health
- Substance abuse
 
59 (69)
94 (138)
7 (32)
 
55 (83)
4 (24)
2 (16)
 
43 (67)
3 (19)
1 (8)
Pharmaceutical
- General medical
- Psychiatric
- Substance abuse
 
14 (25)
28 (39)
0.0004 (0.005)
 
9 (19)
0.4 (2)
0.03 (0.4)
 
6 (11)
1 (5)
0
Total 380 (473) 149 (592) 90 (194)


TABLE 3. Subjects With Nonzero Costs*
Number (Percent)
Service Severely Mentally Ill Subjects
(n=225)
Pharmacy Controls
(n=223)
Membership Controls
(n=218)
Inpatient
- Medical-surgical
- Psychiatry
- Substance abuse
 
76 (34)
88 (39)
4 (2)
 
49 (22)
0
2 (1)
 
34 (16)
1 (1)
0
Outpatient
- General medical
- Mental health
- Substance abuse
 
212 (94)
192 (85)
36 (16)
 
208 (93)
13 (6)
7 (3)
 
183 (84)
17 (8)
8 (4)
Pharmaceutical
- General medical
- Psychiatric
- Substance abuse
 
205 (91)
205 (91)
1 (1)
 
198 (89)
44 (20)
1 (1)
 
159 (73)
35 (16)
0
Total 220 (98) 212 (95) 189 (87)


TABLE 4. Duration of Enrollment in Days*
  Cohort 1
(1986-1990)
Cohort 2
(1990-1995)
Subjects with diabetes mellitus
Severely mentally ill subjects
Pharmacy controls
Membership controls
1424 (39)
1263 (45)
1236 (45)
1023 (47)
1437 (40)
1298 (48)
---
---
* Data from Kaplan-Meier survival distribution function. Data are given as mean (SE); ellipses indicate not applicable.


[Table of Contents]


Managing the Care of Schizophrenia: Lessons From a 4-Year Massachusetts Medicaid Study

Barbara Dickey, Ph.D.; Sharon-Lise T. Normand, Ph.D.; Edward C. Norton, Ph.D.; Hocine Azeni, M.A.; William Fisher, Ph.D.; and Frederic Altaffer, Ph.D.
Archives of General Psychiatry 53:945-952 (October 1996)

Background: In 1992, Massachusetts launched a statewide managed care plan for all Medicaid beneficiaries.

Methods: This retrospective, multiyear, cross-sectional study used administrative data from the Massachusetts Division of Medical Assistance and Department of Mental Health, consisting of claims for 16400 disabled adult patients insured by Medicaid in Massachusetts between July 1, 1990, and Jun 30, 1994. The main outcome measures include annual rates of hospitalization, emergency department utilization, and follow-up care 30 days after discharge; length of inpatient stay; and per-person inpatient and outpatient expenditures.

Results: Between 1991 and 1994, the likelihood of an inpatient admission decreased from 29% to 24% and was accompanied by a slight reduction in length of stay (median number of bed-days per admission dropped by 3.3 days). There was a slight decrease in the number of patients who sought care in general hospital emergency department utilization. However, there was a small increase in the fraction of patients readmitted within 30 days of discharge. Medicaid and Department of Mental Health expenditures for mental health per treated beneficiary decreased slightly, from $11060 to $10640, during the 4-year study period.

Conclusions: Although per-person expenditures dropped and most patient patterns of care remained the same, longer-term study is recommended to assess whether the trends can be maintained.

The treatment of schizophrenia remains a major clinical challenge to health care providers.1 The behavioral problems and thought disorders that are characteristic of schizophrenia make management complex and expensive. For example, in the United States, even though slightly more than 1% of adults have the disorder, treatment expenditures account for more than 2.5% of all health care expenditures.2, 3 It is not unusual for those with schizophrenia to have disabilities that lead to loss of employment and private health insurance. When this occurs, government becomes the primary health care insurer. Almost two-thirds of all the expenditures for schizophrenia treatment come from federal, state, and local government sources.2

With so much government money at stake, it is not surprising that reforms are rapidly changing the provision of government services to the mentally ill. All but 6 states are pursuing managed care for Medicaid beneficiaries, including those with severe mental illness, such as schizophrenia. In some states, Medicaid managed care plans tap into existing health maintenance organization networks.4 In other states, Medicaid contracts with mental health managed behavioral care companies to provide administrative functions and direct beneficiaries to a local provider network.

There are 2 fundamental issues in the evaluation of managed care for the severely mentally ill. First, can managed care succeed in providing quality care to psychiatrically disabled patients, especially those diagnosed as having schizophrenia?5, 6, 7, 8 These individuals are at high risk for catastrophic psychiatric and medical care but seldom are able to navigate effectively within the health care system and often lack advocates on their behalf. Even though providers surveyed in Massachusetts have reported that quality has not been compromised,9 both critics and advocates would like to have more evidence before accepting this conclusion.

The second issue is whether managed care actually reduces costs of shifts costs onto families, other state agencies, or medical care providers. When there are strong financial incentives to reduce acute hospital admissions, managed care plans will be financially motivated to divert beneficiaries to the long-term care system run by the state mental health agency. Individuals with schizophrenia are likely to be eligible for both Medicaid benefits and a state-funded long-term care system of community and hospital-based services. Shifting costs to the state mental health agency may result in greater profits for managed care plans but may not improve continuity of care; moreover, the societal costs may be higher. To date, there are no studies of how the reduction in mental health expenditures for acute care might shift costs to long-term care.

Evaluations of managed care plans are in an early stage of development, and little descriptive information is available to provide benchmarks against which to compare different approaches to cost containment.10 Earlier reports 9, 11 of the Massachusetts plan studied only the first year after implementation. In addition, these studies were limited to claims for mental health treatment.

We developed a database on adult Medicaid beneficiaries with schizophrenia to examine access to care, use of services, and treatment costs associated with schizophrenia before and after the introduction of managed care. Because care for our disabled population is not limited to services reimbursed by Medicaid alone, the data are drawn from 2 state agencies: the Division of Medical Assistance (Medicaid) and the Department of Mental Health (DMH). Data cover 2 years of the plan after implementation and include nonpsychiatric medical care, pharmacy, transportation, and dental care. These additional data are important to include because they account for roughly 40% of the total expenditures. We also examined incident patients, those not treated for schizophrenia before managed care was introduced.


PATIENTS AND METHODS

The Massachusetts Managed Mental Health Program

In 1992, Massachusetts received a 1915b waiver from the Health Care Financing Administration. Under this plan, all beneficiaries were asked either to enroll in a local health maintenance organization or to select a Medicaid-approved primary care clinician. Virtually all psychiatrically disabled beneficiaries chose a primary care clinician. Medicaid contracted with a single proprietary vendor, Mental Health Management of America, a division of First Mental Health, Boston, MA, to management the provision of mental health benefits. The vendor had 4 specific cost-containment strategies: (1) negotiation of reimbursement rates with a network of providers who would be paid on a fee-for-service basis, (2) implementation of an aggressive utilization management plan, (3) development of community-based alternatives to hospitalization, and (4) collaboration with the DMH to fund emergency service teams to screen patients for appropriateness of inpatient admission, with a view toward diverting many of them to alternative treatment sites.

Under the terms of the contract with Medicaid, the vendor was required to make available to recipients all the mental health and substance abuse benefits: acute inpatient treatment, crisis stabilization, outpatient evaluation and treatment, psychiatric day treatment, residential detoxification, and methadone treatment. The vendor was directed to add diversionary services, including acute residential treatment programs, family stabilization teams, and partial hospitalization programs. The contract further specified that the vendor would be responsible for the centralized functions of utilization review, claims processing, systems support, and provider relations, and for decentralized regionally based case management and network management. The contract with the vendor excluded payment for long-term nursing home care, mental health services provided by the DMH, and any medical treatment or outpatient pharmacy. In addition, it did not include members of health maintenance organizations and those who had Medicaid as a second payer. Disabled beneficiaries were covered at a higher rate than other beneficiaries, and providers were reimbursed by the vendor on a fee-for-service basis.

Data Sources

We used administrative data obtained from Medicaid and the DMH. Together, these files provided information regarding patient sociodemographic status, reimbursed inpatient and outpatient care, discharge diagnoses, and timing of services.

Definition of Cross-Sectional Cohorts

We created 4 separate cohorts, 1 for each fiscal year of the study, that together described treatment spanning the period from July 1, 1990 (the start of fiscal year 1991) through June 30, 1994 (the end of fiscal year 1994). The members of each cohort consisted of all adult Massachusetts Medicaid beneficiaries, aged 18 to 64 years, who were disabled and treated, either as inpatients or outpatients, for schizophrenia (International Classification of Diseases, Ninth Revision, Clinical Modification, primary diagnostic code of 295) at least once during the fiscal year. The cross-sectional cohorts were created by assigning patients with a schizophrenia claim to the fiscal year in which the claim was submitted; for this reason, it was possible for patients to appear in more than 1 cohort.

With the use of the patient's unique Medicaid identification number, patient-level files for each fiscal year were constructed by identifying paid claims for all psychiatric and substance abuse care (claims with a primary diagnostic code of 290-315), medical care (claims with any primary diagnostic code excluding V codes and 290-315 or any claim with a mental health Current Procedure Terminology procedure code), and other services, such as pharmacy, transportation, and dental care. Finally, to ensure that we had a complete record of service use for each patient, we merged state hospital admissions from the DMH inpatient files with the administrative Medicaid information by means of unique patient identification numbers.

Sociodemographic and Comorbidity Data

We used Medicaid membership files to identify the date of birth, sex, race, and residence ZIP code for each patient in our study cohort. To measure the degree of substance abuse in our sample, we assumed that if a patient was ever diagnosed as a substance abuser (primary or secondary diagnostic International Classification of Diseases, Ninth Revision, Clinical Modification code of 291, 292, 303.00, 303.90, 304, or 305) in a given year, then the patient had a drug or other alcohol abuse problem in the given year.

Admission Type

During the study, the DMH had contracted with a few general hospitals for inpatient beds to replace some of the beds in state hospitals closed as part of a larger deinstitutionalization plan. Thus, DMH-funded admissions occurred in both state and general hospitals. To differentiate between beds funded by Medicaid and those funded by the DMH, we classified each mental health inpatient admission as either a DMH admission or a Medicaid admission. The admission policy for Medicaid recipients to a DMH bed required that beds be available to forensic patients and to patients with behavioral management requirements that could not be met in general hospital psychiatric units or in freestanding psychiatric facilities otherwise reimbursed by Medicaid.

Evaluation of Access to Care

We defined access to care in each year as the number of Medicaid beneficiaries with a primary diagnosis of schizophrenia who had at least 1 Medicaid-paid claim. We also examined the number of incident patients in each year. We classified a patient as incident if there was no mental health claim with a primary diagnosis of schizophrenia for the patient in the previous year(s). Because we did not have Medicaid data before 1991, we were unable to identify new patients in 1991 and consequently may also have overestimated the number of incident patients in the remaining years.

Mental Health Inpatient Utilization

We defined mental health inpatient utilization as hospital admissions with primary mental health discharge diagnoses corresponding to schizophrenia, or any other psychiatric and substance abuse disorder. Because we hypothesized that hospital admissions would drop as a result of the screening and diversion programs of the managed care plan, we examined the distribution of mental health inpatient admissions in each year. We also estimated the likelihood of having any mental health inpatient admission by the percentage of patients who had at least 1 such admission in a given year. Finally, for those patients who had at least 1 mental health inpatient admission in a given year, we examined the number of bed-days per admission.

Continuity of Care

To describe follow-up care after discharge, we first defined inpatient transfers as admissions to another hospital within 24 hours after a discharge and then linked information from the transfers to form a complete inpatient episode of care for each patient in our cohorts. We then categorized each discharge into 1 of 4 mutually exclusive categories: discharges for which there was no outpatient or inpatient contact within 30 days, discharges for which there was outpatient contact within 30 days, discharges resulting in rehospitalization within 30 days, and discharges for which both an outpatient contact and a rehospitalization within 30 days resulted. Outpatient contact included a visit to any hospital outpatient department or to a clinic; a visit to a physician office; or the provision of any 1 of a set of mental health services, such as psychological testing, case management, or day treatment.

Because we believed that, ideally, continuous patient care should be rendered from 1 provider, we also calculated the number of unique hospitals to which patients with more than 1 hospitalization were admitted. Finally, we estimated the distribution in each year of general hospital emergency department visits. We did not calculate the distribution for state hospitals because they do not have emergency departments.

Assessment of Expenditures

We derived costs for Medicaid services from the paid claims that indicated the amount reimbursed. Although we could not determine whether paid claims overestimated or underestimated the true cost of treatment, these costs represented public expenditures through this entitlement program. Because the DMH operates on a fixed budget and records only use of services, we estimated costs for inpatient care by means of the per diem for state hospitals calculated by the DMH. These estimated per diem costs are based on accounting costs, calculated by dividing total annual inpatient expenditures, including capital costs, by the number of actual patient bed-days in each facility annually. Hospital-specific per diem costs were used to estimate the episode costs for each person admitted to a DMH facility by multiplying the calculated per diem by the number of days in the episode.

Inpatient mental health expenditures (psychiatric or substance abuse care) were dichotomized into Medicaid and DMH admissions to examine the extent of cost shifting between these 2 government agencies. All inpatient expenses are clustered together so that room and board, ancillaries, and physician fees are included.

Outpatient mental health expenditures included hospital outpatient department or clinic services, physician services, and other mental health services provided in free-standing mental health agencies.

Non-mental health expenditures were composed of medical care, pharmacy, transportation, and dental care. Claims for the last 3 categories did not report diagnoses, and consequently we were unable to distinguish mental health--related from non-mental health--related expenditures.

We aggregated the inpatient and outpatient mental health expenditures and then added all categories for total expenditures. Within each category of expenditures we report the number and percentage of persons with any expenditures, the average expenditure per person with any expenditure, and the total expenditure. For inpatient care we also report expenditure per admission.

Statistical Analyses

We computed simple univariate summary statistics by year. For continuous-valued variables, we calculated sample means and SDs; we also constructed box plots12 to display the center and spread of the distributions of the observations. Inpatient utilization was stratified by admission type (DMH or Medicaid). All expenditure figures are reported in 1994 dollars by adjusting expenditures in 1991, 1992, and 1993 for inflation by means of the gross domestic product deflator.13


RESULTS

Description of the Cross-Sectional Cohorts

Between July 1, 1990, and June 30, 1994, we observed 16400 disabled adults who contributed a total of 32135 annual observations. Despite changes in the number of treated beneficiaries during the 4-year period, we found that the sociodemographic characteristics remained virtually unchanged (Table 1): approximately half the beneficiaries were female and the majority were white, with a mean age of 41 years. Eleven percent were ethnic or racial minorities. Comorbid substance abuse increased as a proportion of the total study population. This increase might be a coding artifact resulting from changes in diagnostic practice or an increased awareness of substance abuse. Reimbursement of the treatment of substance abuse received much attention from providers because of the emphasis placed by the managed care vendor on outpatient rather than inpatient detoxification. It is also possible, given increases in the level of alcohol and other drug dependence in the general population, that there is increasing substance abuse among many of these patients, and the increase is being documented by providers.

Access to Care

The number of Medicaid beneficiaries with schizophrenia being treated increased from 6614 in 1991 to 7541 in 1994 (Table 1). However, in 1993, the year managed care was introduced in Massachusetts, the number of treated beneficiaries increased by more than 3000 from the previous year. This 1993 increase occurred despite a decrease in the number of providers. The increase might be an epidemiological phenomenon, but the stable demographic characteristics suggest that is not the source of the increase. More likely, the increase can be attributed to the advocacy work of the mental health provider community and family members who wanted to ensure that those who met the eligibility criteria were actually enrolled in Medicaid. In fact, the incident patients in 1993 were more likely to be older, white, female, and substance abusers than new patients in the remaining years (Table 1). The most striking demographic change for new schizophrenia patients was the higher percentage, in all years, of substance abusers.

Mental Health Inpatient Utilization

The percentage of patients who had at least 1 inpatient admission dropped by 4 percentage points during the study period, from 29.8% in 1991 to 25.4% in 1994 (Table 2). The decrease in the likelihood of a mental health admission during the study period was larger for DMH admissions than for Medicaid admissions (Table 2). Even though the probability of an admission decreased, the total number of DMH admissions remained almost the same in all 4 years. Medicaid admissions dropped 65% in 1993 but returned to the pre-managed care level by 1994. For those admitted, the median number of bed-days per admission decreased by about 3.3 days; there was a drop of 2.5 days for Medicaid admissions and of 3 days for DMH admissions (Figure 1).

Continuity of Care

We found little evidence of change in continuity of care. Rapid readmissions were up slightly, from 22.1% in 1991 to 24.2% in 1994 (Table 3), but there was essentially no change in the absence of outpatient follow-up contact, with the proportion of discharges without any follow-up contact remaining at 29%. (We were unable to identify in these data follow-up that may have occurred through DMH-funded community support services.) For patients with multiple admissions, there was an increase in the percentage who were admitted to more than 1 hospital (Table 3) but no increase in the percentage of patients who used emergency departments.

Mental Health Expenditures

Inpatient

Medicaid inpatient expenditures dropped dramatically in 1993, in the first year of managed care, but rose the following year (Table 4). The savings in Medicaid inpatient expenditures were largely offset, however, by increased expenditures on DMH hospital admissions. The annual Medicaid per-inpatient costs dropped below pre-managed care levels, while DMH per-inpatient costs were higher after implementation of the managed care program.

Outpatient

Both total expenditures and pre-treated beneficiary expenditures rose from their pre-managed care levels. The large increase in the number of beneficiaries in 1993 led to a dip in per-treated outpatient expenditures, but by 1994 this effect had disappeared. Given the large reductions in inpatient treatment, it was expected that outpatient treatment would expand, although these increases suggest only a modest cost shifting from inpatient to out-patient treatment.

Non-Mental Health Expenditures

Total expenditures of inpatient and outpatient medical and surgical care rose with the influx of new beneficiaries in 1993 (and then dropped as the number declined in 1994), but the per-person treated costs were about the same across all 4 study years. These data do not provide evidence that mental health treatment was shifted to the non-mental health sector. Other non-mental health expenditures include transportation and dental costs, which remained essentially the same during the study period. Pharmacy costs doubled both in total expenditures and per person treated.

Total Expenditures

The total Medicaid and DMH expenditures for mental health per treated beneficiary fell slightly from $11090 to $10600 during the 4-year study period. When all other Medicaid reimbursed care is added to mental health care, there is a slight increase in the total per-person expenditures (Table 4). The total dollar expenditures fluctuated with the number of treated beneficiaries across the study years, but it was decreasing, not increasing, at the end of the study period. The total Medicaid and DMH dollar expenditure for mental health care after managed care reversed the upward trend and stabilized at about $80 million in 1993 and 1994 (Figure 2).


COMMENT

Using a unique database of patient-level mental health treatments constructed from 2 sources, Medicaid and the DMH, we found that managed care was associated with some gains in continuity of care but a slight increase in rapid readmissions. Furthermore, there were reductions in mental health expenditures at the per-person level, primarily because fewer inpatient bed-days were reimbursed by Medicaid. The use of DMH inpatient beds for these beneficiaries remained about the same. Total mental health expenditures during the 4-year study period were contained, despite a growth in the number of treated beneficiaries.

There are several general conclusions from this study. First, because our measures of access and continuity of care are based on administrative data, they are limited in their scope and sensitivity. Furthermore, we have no way of knowing whether the pre-managed care levels were appropriate. Finally, for those with chronic illnesses, examination of short-term results is not an adequate indicator of the value of managed care. Information regarding the appropriateness of processes of care, such as the adequacy of discharge planning, or knowledge regarding patient well-being is crucial in judging the adequacy of quality. Because there is no clear evidence about the effectiveness of managed care plans to provide services needed by the most seriously mentally ill, we believe that continued research is essential to document the benefits or risks to clients.

Second, although we established that there were cost savings under managed care, we cannot be certain of the actual magnitude of the savings. Our assessment before and after managed care allows only 2 types of comparisons. The first type simply focuses on levels and directions of trends observed before and after implementation. The second approach compares observed postintervention levels with the levels that would have been expected in the absence of the intervention.14 From the perspective of the first approach, the vendor appears to have achieved a net reduction in expenditures and service use. The reduction in Medicaid inpatient expenditures was a function of 3 factors: the negotiated rates with the network hospitals, the reduced number of admissions, and the reduction in the total number of bed-days.

Third, the introduction of this managed care plan resulted in an unanticipated increase in the number of beneficiaries treated for schizophrenia. In this study we observed an increase in additional patients in 1993 who had a profound effect on the system, at least in the first year. The increase in treated patients in 1993, which shrank in 1994, tells us less about access to care and more about diagnostic variability in mental health. Rather than roughly 3000 members losing their coverage, as it appears, we found that they remained enrolled and were being treated for other mental illnesses. The marked increase in the number of beneficiaries in 1993 is real, regardless of diagnostic category. However, it creates a denominator problem: comparing percentages across years may be misleading, and per-person mean costs may be lower because individuals who need less intensive treatment are added to the membership. For example, the proportion of treated beneficiaries who had 1 or more admissions to a DMH inpatient bed during a year appears to drop from 15% to 10%, but the actual number of admissions did not change. This suggests that many of the new patients were among those less seriously ill. Trends such as these have been exhibited in a range of evaluations in a number of divergent fields.15, 16 Their ubiquitous character suggests the need for caution on the part of administrators and providers who would attempt to learn in the first few months after implementation what the ultimate effects of managed care will be on savings or service use.

Our final conclusion relates to cost shifting. We did find some evidence of cost shifting in this study. For example, one striking finding is the doubling of pharmacy costs. The increases in pharmacy costs observed might raise concern that psychosocial treatments are too often replaced by pharmacological interventions, but what seems more likely is that pharmaceutical costs have risen, especially for patients who are taking newer antipsychotic medications. Additionally, the growth in medical expenditures might signal cost shifting to that sector, and the fact that per-person medical care costs increase slightly might signal such a shift. The growth in medical expenditures are important because they compose about a third of all the health care dollars spent by Medicaid and the DMH on treatment for those with schizophrenia.

This report must be considered carefully in the light of its limitations. The mental health environment in Massachusetts at the time of this study was in transition. Reforms that are a response to fiscal and social problems are rarely unidimensional. In Massachusetts, prepaid managed care was only 1 aspect of a more global effort to privatize the Massachusetts mental health service system in the early 1990s. This effort entailed the closing of 3 state hospitals and the expansion of community-based services provided by vendors under contract to the DMH. The current study design does not rule out secular trends.

Although this study raises many questions, it also provides preliminary findings about the relationship of managed care with service use and with expenditures for seriously mental ill adults with schizophrenia. Future studies of managed care will need to continue to explore the trade-off between quality of care and costs, cost shifting between government agencies, and the difference between short-term and long-term effects.


From the Departments of Psychiatry (Dr. Dickey) and Health Care Policy (Dr. Normand), Harvard Medical School, Boston, MA; Mental Health Services Research, McLean Hospital, Belmont, MA (Dr. Dickey and Mr. Azeni); Department of Biostatistics, Harvard School of Public Health, Boston (Dr. Normand); Center for Economics Research, Research Triangle Institute, Research Triangle Park, NC (Dr. Norton); Center for Psychosocial and Forensic Services Research, University of Massachusetts Medical School, Worcester (Dr. Fisher); and Mentor, Inc., Boston (Dr. Altaffer).


NOTES

Accepted for publication June 21, 1996.

This research was supported by grant RO1-MH54076 from the National Institute of Mental Health, Rockville, MD.

We thank the Massachusetts Department of Mental Health and the Division of Medical Assistance for providing data and technical support. Thanks also to Richard Lindrooth, Research Triangle Institute, Research Triangle Park, NC, for providing technical assistance.

Reprints: Barbara Dickey, Ph.D., McLean Hospital, Administrative Building, 115 Mill Street, Belmont, MA 02178-9106.


REFERENCES

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  2. Rupp A., and S.J. Keith. "The Costs of Schizophrenia." Psychiatr Clin North Am, 1993; 16:413-423.
  3. Regier, D.A., W.E. Narrow, D.S. Rae, R.W. Manderscheid, B.Z. Locke, and F.K. Goodwin. "The De Facto US Mental and Addictive Disorders Service System." Arch Gen Psychiatry, 1993; 50:85-94.
  4. Hurley, R.E., D.A. Freund, and J.E. Paul. Managed Care in Medicaid: Lessons for Policy and Program Design. Ann Arbor, MI: Health Administration Press; 1993.
  5. Sharfstein, S.S. "Utilization Management: Managed or Mangled Psychiatric Care?" Am J Psychiatry, 1990; 147:965-966.
  6. Tischler, G.L. "Utilization Management of Mental Health Services by Private Third Parties." Am J Psychiatry, 1990; 147:967-973.
  7. Schlesinger, M. "On the Limits of Expanding Health Care Reform: Chronic Care in Prepaid Settings." Milbank Q, 1986; 64:189-215.
  8. Schlesinger, M. "Striking a Balance: Capitation, the Mentally Ill,and Public Policy." In: D. Mechanic and L.H. Aiken, eds. Paying for Services: Promises and Pitfalls of Capitation, New Directions for Mental Health Services. San Francisco, CA: Jossey-Bass, Inc.; 1989; 43:91-115.
  9. Callahan, J.J., D.S. Shepard, R.H. Beinecke, M.J. Larson, and C. Cavanaugh. Evaluation of the Massachusetts Medicaid Mental Health/Substance Abuse Program. Waltham, MA: Brandeis University; January 1994.
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  11. Dickey, B., E.C. Norton, S.L. Normand, H. Azeni, W. Fisher, and F. Altaffer. "Massachusetts Medicaid Managed Health Care Reform: Treatment for the Psychiatrically Disabled." Adv Health Econ, 1995; 15:99-116.
  12. Statistical Sciences Inc. S-PLUS: User's Manual. Seattle: WA:Statistical Sciences, Inc., 1991; 1:5-51.
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  16. McCleary, R., and R.A. Hay. Applied Time Series Analysis for the Social Sciences. Beverly Hills, CA: Sage Publications: 1980.
TABLE 1. Demographic Characteristics of Cross-Sectional Cohorts*
  All Patients, No. (%) Incident Patients, No. (%)
FY 1991
(N=6614)‡
FY 1992
(N=7295)‡
FY 1993†
(N=10685)‡
FY 1994†
(N=7541)‡
FY 1992
(N=2528)§
FY 1993
(N=5484)§
FY 1994
(N=1774)§
Age, y
- 18-21
- 22-39
- 40-64
- Mean±SD
 
172 (2.6)
3234 (48.9)
3208 (48.5)
41±12
 
184 (2.5)
3503 (48.0)
3608 (49.5)
41±12
 
331 (3.1)
4843 (45.3)
5511 (51.6)
41±12
 
179 (2.4)
3538 (46.9)
3824 (50.7)
41±11
 
118 (4.7)
1302 (51.5)
1108 (43.8)
39±12
 
246 (4.5)
2480 (45.2)
2758 (50.3)
40±12
 
104 (5.9)
934 (52.6)
736 (41.5)
38±11
Female 3182 (48.1) 3486 (47.8) 5808 (54.4) 3470 (46.0) 1201 (47.5) 3291 (60.0) 764 (43.1)
Race
- African American
- American Indian
- Asian American
- Hispanic
- White
- Unknown
 
618 (9.3)
3 (0.0)
19 (0.3)
86 (1.3)
5865 (88.7)
23 (0.3)
 
699 (9.6)
3 (0.0)
25 (0.3)
125 (1.7)
6413 (87.9)
30 (0.4)
 
891 (8.3)
9 (0.1)
28 (0.3)
188 (1.8)
9537 (89.3)
32 (0.3)
 
772 (10.2)
4 (0.1)
22 (0.3)
102 (1.4)
6464 (85.7)
177 (2.3)
 
260 (10.3)
1 (0.0)
14 (0.6)
76 (3.0)
2164 (85.6)
13 (0.5)
 
430 (7.8)
5 (0.1)
15 (0.3)
126 (2.3)
4891 (89.2)
17 (0.3)
 
187 (10.5)
0 (0.0)
12 (0.7)
38 (2.1)
1377 (77.6)
160 (9.0)
Substance Abuse 636 (9.6) 775 (10.6) 3108 (29.1) 1023 (13.6) 355 (14.0) 1875 (34.2) 324 (18.3)
* Patients are disabled Massachusetts Medicaid beneficiaries treated for schizophrenia. FY indicates Fiscal Year.
† Managed care plan years.
‡ Number of treated beneficiaries
§ Number of new treated beneficiaries.


TABLE 2. Mental Health Inpatient Utilization* for Disabled Patients With Schizophrenia
  FY 1991 FY 1992 FY 1993† FY 1994†
No. of treated beneficiaries 6614 7295 10685 7541
Total No. of admissions 3937 4624 2486 3870
Distribution of hospital admissions, No. (%)‡
- 0
- 1
- 2
- 3
- 4
- >5
 
4690 (70.9)
991 (15.0)
459 (6.9)
198 (3.0)
125 (1.9)
151 (2.3)
 
5120 (70.2)
1120 (15.4)
471 (6.5)
252 (3.5)
148 (2.0)
184 (2.5
 
9146 (85.6)
1001 (9.4)
318 (3.0)
114 (1.1)
58 (0.5)
48 (0.4)
 
5623 (74.6)
1085 (14.4)
388 (5.1)
202 (2.7)
108 (1.4)
135 (1.8)
>1 inpatient admission, No. (%)‡
- All admissions
- DMH admissions
- Medicaid admissions
 
1924 (29.1)
1082 (16.4)
1170 (17.1)
 
2175 (29.8)
1098 (15.1)
1466 (20.1)
 
1539 (14.4)
1038 (9.7)
608 (5.7)
 
1918 (25.4)
915 (12.1)
1232 (16.3)
* Hospital admissions for treatment of mental illnesses or substance abuse.
† Managed care plan years.
‡ Percentage was calculated with number of treated beneficiaries used as the denominator. FY indicates fiscal year; DMH, Department of Mental Health.


TABLE 3. Continuity of Care for Disabled Patients With Schizophrenia*
  No. (%)
FY 1991 FY 1992 FY 1993† FY 1994†
Follow-up care within 30 d of a discharge
- None
- Outpatient contact
- Rehospitalization
- Rehospitalization and outpatient contact
- Total No. of Discharges
 
1077 (29.2)
1797 (48.7)
142 (3.8)
677 (18.3)
3693 (100.0)
 
1199 (27.3)
2178 (49.7)
127 (2.9)
880 (20.1)
4384 (100.0)
 
932 (38.0)
1159 (47.2)
124 (5.1)
238 (9.7)
2453 (100.0)
 
1117 (29.7)
1729 (46.0)
215 (5.7)
696 (18.5)
3757 (100.0)
Distribution of unique hospitals‡
- 1 hospital
- 2 hospitals
- 3 hospitals
- 4 hospitals
- >5 hospitals
- Total No. of Patients With 2 Hospitalizations
 
361 (38.7)
364 (39.0)
145 (15.5)
42 (4.5)
21 (2.3)
933 (100.0)
 
342 (32.4)
431 (40.9)
171 (16.2)
71 (6.7)
40 (3.8)
1055 (100.0)
 
227 (42.2)
213 (39.6)
64 (11.9)
24 (4.5)
10 (1.9)
538 (100.0)
 
298 (35.8)
381 (45.7)
113 (13.6)
29 (3.5)
12 (1.4)
833 (100.0)
Emergency department visits
- 0
- 1
- 2
- 3
- 4
- >5
- Total
 
5626 (85.1)
545 (8.2)
192 (2.9)
92 (1.4)
44 (0.7)
115 (1.7)
6614 (100.0)
 
6219 (85.3)
577 (7.9)
221 (3.0)
97 (1.3)
69 (0.9)
112 (1.5)
7295 (100.0)
 
9894 (92.6)
562 (5.3)
140 (1.3)
44 (0.4)
22 (0.2)
23 (0.2)
10585 (100.0)
 
6653 (88.2)
435 (5.8)
210 (2.8)
82 (1.1)
43 (0.6)
118 (1.6)
7541 (100.0)
* FY indicates fiscal year.
† Managed care plan years.
‡ Distribution of patients with 2 or more hospitalizations categorized by the number of unique hospitals to which they were admitted during the fiscal year. In FY 1991, 38.7% of the 933 patients who had at least 2 hospitalizations went to a single hospital, 39.0% were admitted to 2 distinct hospitals, 15.5% were admitted to 3 distinct hospitals, 4.5% were admitted to 4 distinct hospitals, and the remainder (2.3%) were admitted to 5 or more distinct hospitals.


TABLE 4. Annual Expenditures for Disabled Patients With Schizophrenia*
  FY 1991 FY 1992 FY 1993† FY 1994†
Mental Health Expenditures‡
Medicaid mental health inpatient admissions
- No. of inpatients
- Average annual expenditure per inpatient, $
- Total annual expenditure, x$1000
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