I am going to present the NHANES I Epidemiological Follow-up Study, which is a jointly funded and truly collaborative study between the National Center for Health Statistics (NCHS) and various agencies in the National Institutes of Health (NIH) and the Alcohol, Drug Abuse and Mental Health Administration.
As the name implies, this is a longitudinal study that uses as its baseline cohort those persons who are examined as part of the first National Health and Nutrition Examination Survey (NHANES).
We had three major objectives in designing this survey, with the major aim being trying to make the most of a longitudinal nature of this data base.
The first was to relate morbidity, mortality and institutionalization to risk factors measured at baseline.
Second, we wanted to look at changes in individual characteristics between baseline and the follow-up. Here we are basically talking about risk factors. In some cases, we have measurements at time one and a measurement at time two. In other cases, there was some retrospective history collected at the time of the follow-up.
Third, to the extent possible, we wanted to look at the natural history of chronic disease and also functional impairments.
First, let me say something about the NHANES program.
You heard earlier about two of the other data systems in NCHS, the National Health Interview Survey (NHIS) and the National Nursing Home Survey (NNHS). One of the other major data collection systems is the National Health Examination Survey (NHES).
These started in the 1960's. The first three were called Cycles I, II and III.
NHANES I is really the fourth in the cycle, but in the early 1970's the survey was expanded to take into account an interest at that time in poverty, the effects of poverty on nutritional status and then the effects of nutrition on health. There was a major nutritional component added to the NHES, and, hence, the name NHANES.
The second NHANES was done in the late 1970's. An Hispanic NHANES was done in the early 1980's. We are currently planning the third in the series and that should be fielded in about 2 years.
These surveys are unique in that they contain objective measures of health as opposed to the interview surveys which are based on self-reports or the surveys that are based on records.
We do a multi-stage probability sample down to the household level, an interviewer visits the household and takes some history information, does a series of interviews there and then the sample person is asked to come to a trailer where a standardized exam is administered. There is a lot of data collected at this point.
The first NHANES was done between 1971 and 1975. It has a very complicated sample design. There was a nutrition component and then a detailed component and sub-sampling within that. It is somewhat difficult to do longitudinal analysis on this kind of data base.
We have decided to follow the 14,407 people who were 25+ and over at the time of that survey.
The initial follow, which is what I will be talking to you about today, was conducted between 1982 and 1984. Based on earlier presentations, these sound like some very good years for data collection.
There were multiple parts of this design, which I will go through in some detail. This is an ongoing survey. In 1986, we did a telephone re-contact of survivors who were 55+, and over at the time of the baseline. That data collection is completed and is now being processed and cleaned, and hopefully we will have data tapes for that in 1988-1989.
We are currently in the field with the third wave of follow-up, which is another phone re-contact of the entire surviving cohort.
We will be following this cohort through the National Death Index (NDI) until they are all deceased. We may have a series of other interview contacts over the next 10 years, depending on need and funding.
Let me say that the tapes for the initial follow-up will be released through National Technical Information Service (NTIS) in July. If you have any questions prior to that, we do have some materials in the office and would be happy to send those to you.
The kind of data collected at the time of NHANES I includes medical histories, a health care needs and the nutrition component, the standardized examination, and a series of laboratory tests and X-rays.
To give you some idea of the magnitude of this data collection, there are 14 data tapes from NHANES I, all of which are public use and can be ordered from NTIS.
The design for the follow-up did not include an examination, but did have four other kinds of data collection mechanisms. The first activity, of course, was to trace the people in the cohort. This was somewhat problematic because NHANES I was not designed as a longitudinal survey, and there was no tracing information collected. We had no information about these people over the 10 year period of the follow-up.
We used various methods of tracing to determine vital status, which was the first data point, and also to get an address of the subject or of a proxy who could act as a respondent if the subject was deceased.
Once that address was obtained, we conducted personal interviews with surviving subjects and did some physical measurements at the time of the interview. We also did telephone interviews with proxies for decedents.
The other major data collection activity was getting the hospital and nursing home records for the 10 year period of follow-up. We got the names of all the hospitals and nursing homes they had been in, contacted those facilities and got copies of the records.
Finally, we obtained death certificates through state Vital Statistics Offices for all decedents.
We started out with 14,407 in the cohort and managed to trace 93 percent of them over the 10 year period. By "traced," I mean we could determine their vital status, either because we contacted subjects who were surviving and could respond to our validation questions, if we could get a proxy to do the proxy interview, or if we got a death certificate.
In terms of the results of the interview component, we have broken that out to show the difference between the surviving subjects and the decedents.
The response rate for surviving subjects is 93 percent.
However, for deceased subjects, we could only get proxy interviews for about 84 percent. A lot of the tracing was done through mortality records. We would get a death certificate, but there was no way to contact a proxy. There were no leads that we could pick up on to find someone who would do the interview.
We have death certificates for about 96 percent of all known decedents.
Blood pressure, weight and pulse measurements are the three physical measurements that we conducted; that also was quite successful with 96 percent response rate there.
The longitudinal data is wonderful. That seems to be the wave of the future. You have to have good follow-up, otherwise you can not really generalize about your findings. The first thing we tried to do is evaluate how good the tracing was, particularly because there was no built-in tracing mechanism in the baseline.
Here you have the results of tracing by sex and age, and there is clearly some differences. The older people were much easier to trace and there is a race/sex interaction. White males tend to be the easiest to find and Black females the hardest to find.
We do have problems in the younger age groups, especially among females because of name changes.
When this survey was designed there was a lot of interest in poverty and the sample was designed to over-sample areas where they thought they would find high levels of malnutrition or health effects of malnutrition. There was over-sampling among women of child-bearing age, the elderly, and of people living in poverty areas.
The sample was designed to maximize the rates that were to be calculated by subgroups. It was not really even designed as an epidemiologic study. You get this very funny age distribution, which is bad for some things, but happens to be very good for studying nursing home utilization.
We did look at how health effects measured at baseline were related to whether or not a person was traced.
If we were having a hard time finding people who were sicker at baseline, that would indicate that probably our mortality follow-up was not as good as it should be. We have looked at a multiple regression with age, sex, race and health characteristics to see if they were significantly related to successful tracking.
The only variable that seems to be related to not being traced is smoking. There is some indication here that either we are missing some deaths, possibly among the younger age group, or smoking is acting as some kind of surrogate for some other characteristic that makes people hard to find, people who move often, for example.
In the course of doing these continued follow-ups, we keep trying to find those lost to follow-up. Eventually, we will find them, if through nothing else, through the mortality records.
As the NDI is expanded backwards in time, I think it starts in 1977 now, we will be able to fill in that gap where we have not been able to do adequate death tracing. We are finding people at each stage. You lose some; you find some. I think that especially in the elderly our response rate is up close, I think, to 96-97 percent. We are always looking for new and interesting tracing mechanisms.
Finally, we compared the mortality experience of our cohorts with what would be expected given the national mortality rates occurring at that time. What you find are proportions surviving for White males and White females 65-69. We do have a representative population and that we are not missing any significant portion of that population or a particular kind of person.
You would expect in the early years for our cohort to have lower mortality (because they had to be healthy enough to make it to the van) and, therefore, would have a lower death rate.
On the other hand, we over-sampled in poverty areas and in other groups where we thought we would have higher mortality. The poverty areas do have higher mortality. The non-poverty areas have lower mortality.
When you put those two together, they just kind of converge on the center. In the final analysis, the data is behaving as one would expect it should.
The next aspect of the data collection was the interview procedure and this consisted of a very lengthy questionnaire--it took about 2 hours--and also the physical measurements.
I said this was a collaborative study. It is truly a collaborative study. There are about 12 institutes that participated all with their own agendas. If you look at the questionnaire topics, you can identify who participated in this study.
It was an extremely complicated interview. I would say that the majority of it was taken up by determining whether someone had some chronic condition or acute condition in the 10 year follow-up. If they did have it, when was the onset and were they hospitalized.
If they were hospitalized, the name of the hospital was obtained. All that information was taken down and used for the next kind of data collection.
There was also some more risk factor information collected, some psychosocial variables, some mental health variables, smoking history and that kind of thing.
Most of the subject interviews were done in-person, the proxies were done by telephone.
Again, the physical measurements were pulse, blood pressure and weight. The interviewers actually carried around a little scale and blood pressure equipment, and took three blood pressure measurements.
The non-response goes up with age. These were people who, for some reason, we felt should not take part in the physical measurement section because of a health condition. In some cases, we had an interview with someone using a proxy respondent because the subject was incapacitated; for example, they were in a nursing home where they were too ill to participate. In those cases, of course, we could not get physical measurements.
Finally, the health care facility data collection included the names of all of the institutions that someone had been in; all the hospitals, nursing homes, any other kind of overnight stay the person had. We asked people to sign a release form, sent those to the hospitals, got all the records back and so have, in essence, a 10 year history of utilization for 14,000 people.
The continued waves of follow-up also get this information and we are continuing to go back to hospitals to get these records.
We asked them to fill out an abstract form, but also to send us a Xerox of the face sheet and the discharge summary.
It is a little difficult to give you response rates on this kind of data collection, because we were not quite sure what we should have. We were asking people to recall dates and reasons for hospitalization over a 10 year period. People are not very good at remembering dates.
We do have information from about 2,500 facilities and 400 nursing homes. Some did refuse to participate, and, in some cases, the respondent refused to sign the release form.
We are dealing with about 17,000 hospital records and about 400 nursing home records.
We feel this is a very important data base and can be used for a lot of different activities, including health services utilization, but also used to verify certain diagnoses.
We have objective measures of health at baseline. We do not have objective measures at follow-up, but if someone reports that they had cancer, an MI or something like that, we can look at the hospital record and try to get a verification of that.
We do have some hospitals that refused plus some people that refused. We have an additional contract to do an evaluation of these records to try to merge what the person told us and on a case-by-case basis match that with what the hospital sent. We try to make up dummy records where we are pretty sure we should have a record, but the hospital refused to participate. The entire file will also be matched to the Medicare file to evaluate completeness. We also will do some methodological work on how far back people can remember and do they remember certain kinds of conditions better than others, etc.
That is currently underway. The hospital records will be released with the entire file, but we will then do another release of this evaluation tape in about a year and a half.
Finally, the collection of death certificates. There are a few cases where we do not have the death certificate and keep going back to the states trying to obtain them.
That pretty well describes the data collection. I guess the next question is what can it do for issues of long term care. I think the first thing you should be aware of is this funny age distribution and that we do have a lot of people in the older age groups.
The epidemiologic follow-up is a representative sample it is a large sample, and it is multipurpose. It was not specifically designed to look at nursing home care, and was not designed to look at institutionalization; it was not designed to look at any one particular thing.
Because of that, it has a lot of different kinds of information and you can start to look at things like the interrelationship between health and sociodemographic or socioeconomic factors and the use of nursing homes.
We have a couple of little scenarios about how people can get into a nursing home. In this case you have a health effect that leads to an income change. Then there is some outside factor, some home support not being available and the person goes into a nursing home.
Alternatively, you have some problem with income, then you have the health effect and that leads to a nursing home. You have various payment strategies once you are in the home.
You can have a scenario where a person had much better higher level of income and through some outside factors like the death of a spouse, also ends up in a nursing home at some later date with a different kinds of payment.
The epidemiologic follow-up clearly cannot differentiate between these patterns of health and utilization. It can start to look at some of the components in trying to understand these very complicated interrelationships between health and social factors and utilization.
What we are trying to do now is look at something fairly simple.
We are looking at some of the socioeconomic variables measured at baseline in relation to outcome. This is the kind of table that we are planning on running, using survival techniques. We can look at the percent institutionalized at any point in the follow-up period, the percent not institutionalized, but functionally dependent, and then the percent not functionally dependent. Family income is measured in the dollars in 1970-1975. About 15 percent of this sample had been in a nursing home at some time during the follow-up. About 9 percent were in a home at the time of the interview or had been in a home prior to their death, and then about 3 percent who had been in and out again.
The data base includes these hospital and nursing home records. You can look at how the hospital experience relates to the nursing home stay, over a 10 year period, which is a fairly long period of observation. That is just for the initial follow-up, and now we are adding about another 3 years to that.
The Inventory of Long Term Care Places (ILTCP), is a comprehensive listing of nursing and personal care homes and facilities for the mentally retarded or developmentally disabled.
It was created primarily to serve as a sampling frame for the institutionalized population component portion of the 1987 National Medical Expenditure Survey (NMES).
The institutionalized population component is currently in the field and data is being collected which describes medical care use and expenditures by persons in nursing homes and facilities for the mentally retarded.
The sample of facilities of the NMES were selected from the universe of places as depicted by the inventory.
The inventory data that was collected were used to stratify the sampling frame prior to the sample drawn.
The inventory is of interest from a research standpoint because it is an up-to-date census of these kinds of facilities.
Inventory development and fieldwork were cosponsored by NCHS, the Health Care Financing Administration (HCFA), and the National Center for Health Services Research (NCHSR).
Inventory data were collected by the Bureau of the Census using a mail questionnaire. Three rounds of mail questionnaires were distributed, the first in February 1986.
After the first mail out, up to two additional questionnaires were sent to non-responding facilities. Those facilities which did not respond or which responded in a way which did not give us certain key data items were subject to certain kinds of follow-ups, primarily telephone, but some personal follow-ups were attempted as well.
Census attempted to contact some 56,700 places identified by NCHS. Those 56,700 places were on mailing lists that personnel at NCHS compiled.
The nursing home list was obtained by updating the list of places appearing in the 1982 National Master Facility Inventory (NMFI).
That process involved contacting states and relevant associations for their most current listings and these were then compared to the NMFI listings. What appeared to be new places were added to the list.
The list of places appearing in the 1982 National Census of Residential Facilities (NCRF) was updated to serve as the mailing list for facilities for the mentally retarded and developmentally disabled.
This list was compiled by the Center for Residential and Community Services at the University of Minnesota in 1982.
The updating procedures used to compile this list were similar to those used to update the list of nursing homes. States and relevant associations were contacted for their listings and facilities not appearing on the earlier list were added to the mailing list.
This updating process, of course, is not exact and consequently was a source of some error. One problem is that the mailing lists did contain some facilities which were represented more than once.
This often happens because of minor differences in facility names and addresses and it is difficult to say, "Well, yes, this is the same facility," or, "No, it is a completely different facility."
Some of these duplicates were identified in the field by Census. On the public use tape, which is soon to be released, these places are identified as such.
Another problem with the updating process is that it is only as good as the sources of lists that you have. At the time the lists were compiled, a complete unduplicated listing of skilled nursing facilities (SNF), that are hospital-based was not available. It is probably true that the ILTCP undercounts these places.
The inventory data of some 56,000 places will be released in two parts. The first part contains some 45,000 facility level records representing these homes or facilities, which had complete or partial responses to the mail questionnaire and follow-ups.
The remaining 11,500 or so are on a separate file. This file, again, is facility level records, but they are records of facilities for which data was not available for a variety of reasons, the facility may have gone out of business, some just could not be located, a small number of refusals and so on. There is a list of the different kinds of field status codes which comes as part of the public use tape.
I would like to briefly concentrate on the data items which are available for either the complete or the partial respondents, that is the 45,000 some places.
Each facility was asked to characterize itself from a list of different facility types. There were approximately seven different kinds of places you might regard as a nursing home or a personal care home in the list.
The list includes such types of facilities as the SNF's, approximately 20 percent of the 45,000 indicated that they were skilled nursing facilities SNF's.
Intermediate care facilities (ICF's), and as I said earlier, long term care units of hospitals, licensed personal care homes, but homes which were not certified and so on.
There were also five or six different kinds of facilities for the mentally retarded identified on the questionnaire. These include ICF's for the mentally retarded, foster homes for the mentally retarded or developmentally disabled, state institutions, semi-independent living quarters and so on.
This characterization can be used, and in the public use data, is a crucial part of identifying which places should be defined as nursing homes and which places would be facilities for the mentally retarded.
I might add at this point that the definition that the institutionalized population component of NMES us
Most of the remainder appear to be facilities for the mentally retarded on the public use tape. Although, there are some other facilities which managed to slip on the mailing lists, such as homes for unwed mothers.
The ILTCP provides various measures of facility size. I guess the most important one is the total number of beds set up and staffed for use.
In addition to the total number of beds, you can identify the number of beds certified under the various public programs, Medicare SNF beds, Medicaid SNF beds, Medicaid ICF beds and ICF/MR beds as well.
Other measures of size available include the number of residents in the facility the previous night and the number of admissions occurring during the calendar year of 1985.
As part of the inventory there are questions which refer to the type of ownership of the facility, whether it is for profit, nonprofit, or some sort of government owned facility, federal, state, or local.
For a large number of the facilities, the county can be identified and for most facilities, you certainly know the state of the facility.
Finally, there is a set of variables which I like to call administrative variables. These mainly describe the facilities response to the various mail questionnaires. When, for example, the first mail questionnaire was received, if the first mail questionnaire was returned and so on. There are variables which can be used for certain kinds of methodological studies.
A couple of final notes. The public use file is soon to be released. For the most part, the data appear as reported. There has been very little editing done in attempts to get the data in public use form as quickly as possible.
MARY HARAHAN: Our next two speakers will be discussing the data base that is a little bit different. It is certainly not strictly a health care or long term care data base. But we think it has tremendous possibilities for those of you who are interested in looking at the income and asset characteristics of the population.
DANIEL KASPRZYK: This survey actually began about 10-15 years ago in the Office of the Assistant Secretary for Planning and Evaluation (ASPE) in the Department of Health and Human Services (DHHS). It was a combined effort of Census at that time, ASPE, and the Social Security Administration (SSA).
ASPE was extremely instrumental in the design and content of the survey. In fact, I am quite certain that left to our own designs the survey would look quite different now without the kind of broad governmental information we have received from various agencies.
I would like to just make it clear that this survey is not a long term care data base. It is a household survey principally designed to provide information about income and program participation. It does, however, have some questions designed by working groups of employees from government agencies which had an interest in long term care.
The Survey of Income and Program Participation (SIPP) is a nationally-representative household survey program. It was intended primarily to provide information on cash and noncash income, eligibility and participation in various government transfer programs, disability, labor force status, assets and liabilities and many more items.
SIPP arose in recognition that the best source of information on the distribution of household and personal income in the United States, the March Income Supplement to the Current Population Survey (CPS), had limitations that could only be rectified by a total redesign or a change in the instrument and procedures.
These deficiencies in the March income supplement in the CPS became especially apparent in the early 1970's when many public assistance programs were expanded and reorganized.
It was in response to these deficiencies that a development program arose. This development program was called the Income Survey Development Program. It was funded, principally, by ASPE and DHHS.
The purpose of this survey was to develop methods to overcome some of the shortcomings of the CPS, namely the under-reporting of property income and other irregular sources of income, the under-reporting and misclassif ication of various participation in federal programs and to provide information to assist at the analysis of program participation and eligibility.
During the period 1977-1981, this development program was in operation. Various tests, including a feasibility test that was essentially a survey of 8,000 households, was conducted in 1979. All these tests led to the design of the SIPP.
The kinds of data that SIPP provides are personal, household, and family income data for each month of the calendar year.
The monthly income data are based on a wide variety of cash and noncash sources, monthly data on most government income transfer programs and detailed data on assets, liabilities, and a number of special topics which I will describe later.
SIPP began in October 1983. It is an ongoing survey program for Census. That sample, which began in October 1983, consisted of approximately 21,000 households in 174 areas around the country. It is designed to represent the noninstitutional population of the U.S.
Each household is interviewed once every 4 months for 2 1/2 years to produce sufficient data for short term longitudinal analyses, while attempting to provide a relatively short recall period for reporting monthly income.
The reference period for the principal survey items, namely the income and program participation data, is the 4 months preceding the interview.
We have started a panel in October 1983. We began a new sample in February 1985, the same characteristics, namely a national household sample in about the same number of areas in the country, extending for 2 1/2 years, with interviews every 4 months. Similarly, in 1986 and 1987.
Several panels run concurrently. By looking at the timing of these data collections, you can combine samples to produce estimates from a larger sample.
Each sample is divided into four approximately equal sub-samples. We call these the "rotation groups." One rotation group is interviewed in each month. When I say the interviews were conducted between October 1983 and January 1984, one-fourth of the sample was interviewed in October 1983. The next fourth was interviewed in November, the next fourth December and then finally in January. Then we repeat again.
The purpose is that this design creates manageable interviewing workloads, hand processing workloads each month, instead of one large workload every 4 months. The real problem with that design is that it results in each rotation group or each sub-sample getting a slightly difference period, by one month.
If you are interviewing in January, you ask questions about labor force participation, hours, earnings that you have received over the 4 month period for that 4 month period. It would be September, October, November and December.
Then the next rotation group comes in in February and they have their reference period for the principal survey items is the 4 months preceding the interview month. The reference period is October, November, December and January and so on. In order to get monthly data for the full sample, you have to understand that each rotation group has a slightly different reference period.
For this survey, the important feature of panels, these are basically new samples, and they are initiated each year. There are waves of interviews and each wave of an interview is every 4 months. A wave is an interview.
Each panel consisted of eight interviews, except for the first one, which consists of nine. It got started a little earlier than we anticipated. Then within each wave of interviewing are rotation groups. That is just the sub-samples.
The data collection for the survey is handled through the Census Regional Office. The interviewers that are assigned to these offices conduct personal interviews with each sample household every 4 months.
At the time of the interviewer's visit, each person who is 15 years of age and older, who is present is asked to provide information about himself or herself. We do take proxies. We have not done much telephone interviewing at this point. Telephone interviewing is only used as a stopgap measure to get information if it was otherwise not able to be obtained in a personal interview.
For the interview, the median interview time was about 43 minutes overall. For a one person household, it was about 29 minutes.
We had planned on 30, so I guess we did all right there. It is a rather burdensome interview, or so most people think.
We do try to get mostly self-interview. We do try give instructions for self-interviews. However, the rate is not all that terrific, in my opinion.
One feature of SIPP is that at the time the sample is drawn, we have an address. We go to the address at the time of the first interview and we enumerate everyone who lives at that address.
From that point on, the sample is no longer an address sample, but rather a person-based sample. We follow those individuals whom we identify at the first interview for the next 2 1/2 years. It actually becomes the cohort of people identified at the time of the first interview.
For cost and operational reasons, these personal visit interviews are only conducted at the new addresses when people move, if that new address is within 100 miles of one of our sampling areas.
I am told that the interviewers have taken it upon themselves to ignore our advice and follow-up when they move beyond the hash marks. They follow-up through telephone interviews.
When you are designing the survey you try to think about how you get the best data and how not to burden our interviewers. I must have spent I do not know how many meetings talking about how far we should follow people. We really did not know whether we ought to have the interview or just make these phone calls and track them down. When we finally make the momentous decision, say yes, the interviewers should do this, we found out that, in fact, they had been doing it. Our interviewers are quite flexible.
It is a person-based sample after the time of the first interview, so you can get some rates on how the respondents change over time. That may or may not effect the quality of the data.
There are four components to the SIPP data collection, first is a control card, then the core set of questions that are repeated in every interview. Then there are modules which we call fixed modules that are assigned to specific ways of interviewing. Then, finally, variable modules that are added from time to time.
The control card, the first method of collecting data, is used to obtain and maintain information on the basic characteristics associated with households and persons, and to record some information for operational control purposes.
The characteristics on this control card are recorded by the interviewer and includes the basic demographics: age, race, sex, ethnic origin, marital status, educational level for each member of the household, some information on the housing unit, and relationships to the householder.
A household respondent, typically, provides this information. The control card is also used as a way of keeping track of the employment and income information that are reported in each interview.
Although the data are recorded on a questionnaire, the methodology is such that the interviewer refers to previously reported income types in each succeeding wave. This control card is a vehicle for writing down after the interview what exactly was reported and then the interviewer at the next interview refers to that.
Finally, the last reason for the control card is that it provides us as a way of keeping track of information for following people, the basic method that we use is just to ask at the time of the first interview whether there is one or more people within the household or outside the household who will always know where you will be at. That turns out to be fairly good in terms of being able to use that data for tracking people.
The other way we track people, of course, is through the ingenuity of the field staff. They can find more ways of nosing around the neighborhood to find out where our sample respondents move.
In the core section of the questionnaire is the principal reason for the survey. I mean, the content of SIPP was developed around these core data. It was designed to measure the economic situation of persons in the U.S.
These questions, as I said, are repeated at each interview. The core data built, basically, an income profile for everyone who is 15 years of age and older in the sample household.
The profile is developed by asking a series of questions about labor force participation over the 4 month period. Essentially, a calendar is developed, so you have weekly labor force participation.
Then asking specific questions about the types and amounts of various sources of income, and, particularly a number of detailed questions on program participation and asset ownership. There are a few questions that deal with health insurance, also.
There are several different questions on income types that are asked about during the interview. It pretty much runs the range of all the major federal income security programs. Then there is the asset listing; the usual listing of assets, savings, CD's, NOW accounts, IRA's, mortgages, royalties. There are a lot of questions and a lot of details.
In addition to these questions that we repeat each interview, we also ask a series of questions depending on the interview that we call "fixed topical modules."
The data from these modules should allow an analysis of well-being, which go beyond strictly the income and demographic area.
The idea behind SIPP was to provide a broader context for analyzing by adding questions on topics not covered at the core section.
The administration of these modules is made possible by the fact that when we go back in the second and subsequent interviews less time is required to update the income data and some time in the interview is freed up. Topics covered in these modules take up about 10 minutes, actually, for each module, each interview.
Typically, the data collected in a module does not have the same reference period that we have in the core data. It can be the last two jobs held. It could be over the last year. The reference period varies depending on the topic.
We have an information handout which you can request. It shows the breadth of data collected in this survey. It is called "Topical Modules for the 1984 Panel," and then goes on to 1985, 1986 and 1987 panels.
The kinds of questions that we ask deal with topics of health and disability, and our third interview of the 1984 panel, education and work history. A detailed series of questions on assets and liabilities, assets held and liabilities owned, and the values of those assets. Pension plan coverage, retirement plan shelter costs are in another interview. Child care arrangements and expenses in yet another interview.
Support for non-household members, marital history, fertility history, and migration history--all of these topics get asked in one module or another.
In the 1986 panel, and toward the end of the 1985 panel, there were a series of questions on health status and utilization of health care services, and another series of questions on long term care.
These tend to be questions about health conditions that last 3 months or longer. Then they ask if they need any help in looking after personal needs and who helped them, if they need help doing certain activities and, again, who helped.
These questions, and all questions that have to do with the topical content of SIPP, are not developed independently by Census.
When Census acquired funding for the survey in 1981, after the yearly budget cuts of the Reagan Administration, and DHHS had to bow out of the enterprise, a SIPP Advisory Committee was formed by the Office of Management and Budget (OMB). This Advisory Committee advises and recommends to Census changes in the SIPP content, particularly changes that relate to data required for policy analysis. The OMB Advisory Committee has representatives from over 20 federal agencies and it is through this Committee that we sort out the difficult task of deciding what goes on a survey of this nature.
It is a multipurpose survey and so you have got the problems of rule by committee. Everybody that comes to these meetings has their own agenda for action and for analysis, and it is through a process of working through committees and working groups that the content of SIPP is finally determined with regard to these topical modules.
The survey itself, because of the way we approach the modules, is viewed as government data resource and every effort is made by Census to maintain open lines of communication with this Advisory Committee with regard to the content.
In fact, we are now going through an exercise to develop the content for the 1988 panel of the survey. We have solicited information from various agencies on the Advisory Committee, asked whether there is any changes they require, demonstrated by data with regard to the core section of the questionnaire and sometime this summer we probably will start the process with regard to the topical module.
There is at this point one topical module open sometime in the 1988 panel, late part of the 1987 panel. I am sure that it is a varying policy. The government will have lively debates as to what ought to be considered in that module.
A little bit about non-response. SIPP, at the first interview, it was a household address sample and then it becomes a person-based survey. So the kinds of non-response rates you can devise vary.
Household rates, of a fashion, are a little complicated algorithm to create that because we do follow people and splits in household take place. It is not a one time concept, it is not a cross-sectional concept.
You can see that in the 1984 panel our non-response rate for the first interview was 4.9 percent, about 60-75 percent of that were refusals. That rate is pretty comparable to the rates that they see in the CPS in the March supplement.
As you go down there from wave one through wave nine, you will see that obviously the non-response accumulates. You will also notice that from wave to wave we lose fewer households over time, so that it averages probably about 2 percent a wave. We lose most of the people in the first three interviews. It is similar with the 1985 panel.
Another way of looking at non-response in this survey is to look at it from a person-based point of view. That is probably a better way. Looking at it from a person point of view, you are interested, usually, in the cohort of people that were there at the time of the first interview.
We have got about 79 percent who were there for five interviews straight. The dominant pattern of missing this is the attrition pattern. Once they drop out, they are gone. It is very difficult to convert them.
The way we treat our follow-up for non-response goes something like this. If you are out for two interviews in a row, just drop them from the sample, and we never go back. Otherwise, our interviewers try their best to convert the respondents, and they try hard.
Another form of non-response is the item non-response. Obviously, the interest in the survey is on income and program participation, whether we are getting better measurements of it.
We are getting lower item non-response rates for many income types that we are concerned with, compared to the March CPS.
Because it is a multi-interview design, you want to be able to link the people across time. An identifier is used to match data across time.
By and large, it works. The matching using the ID is very effective. We can match over time. Problems arise and you should try to understand why something does not match, it becomes very complicated, because people drop out of the survey for a variety of reasons, only one of which is non-response. Another could be they have moved, another they could have been institutionalized, or they could have died. There is a variety of reasons why you might not make a match, but, by and large, this identifier does work and people have been successful in matching over time.
The final thing I would like to mention are data products. The SIPP has several data products. One report series is the Series P-70, Household Economic Studies, which was originally providing average monthly data for calendar quarter; now looking more like a Series that provides information on special topics. The last three reports have dealt with assets and liabilities or wealth in the country, functional limitations and disability, and child care arrangements. Like any Census report, it is available through the Government Printing Office (GPO).
There are also working papers. These are papers developed by staff, and they are principally evaluation papers to deal with survey methodology and in some cases may even provide some substantive analyses, but only preliminary. That is, you have done a study and you do not quite feel that it is final, but you want to get it out to a broader community, the working papers vehicle is the way we do it.
The most important data product coming out of SIPP is the micro-data files. By nature, as I have mentioned, the content of SIPP is so diverse it is virtually impossible for Census or anyone to analyze all that data.
At this time, there are several kinds of micro-data files. We release data for the core portion, that is, the income and program participation data. We release it in two structures. One a complex structure that has a series of record types, household, family, person, and income. All these record types are related to each other through a series of pointers.
Another product is the same data just in a different format. That is a rectangular format. For every person in the sample there is one record and so it is a rectangular file. We have got what we call a complex file and a rectangular file--same data, just a different structure.
Then we release the topical module data. The topical module data is always in a rectangular format and it has all the core data collected at the time the module data were collected.
These are the files that are currently available. We have released the waves one-nine core data for the 1984 panel; all nine interviews are now available. We have released the wave three, four and five of the topical module data for the 1984 panel. The release of wave seven, which is another asset/liability module, is imminent within the next month or so. The release of some core data from the 1985 panel will take place within the next several months.
Finally, we have a multi-wave data collection, but all the files I have just mentioned to you are cross-sectional. They are just for the interviews that we have conducted. One of the problems we have had difficulty dealing with is how to create the multi-wave file in such a way, that it links data, edits and imputes it over time so that it all makes sense. The project is difficult. An initial stab has been made of it, and that is what we call the "multi-wave research file." It is not, strictly speaking, a Census public use file. It is a research file that is not available through the normal means of going to our Data Users Services Division. It is available by writing to me or David McMillan at Census.
It is a file that puts together three interviews of income and program data, edits and imputes for missing data in a way that attempts to be more logically consistent than what you would find by linking the individual wave files.
The wave files, as we release them, are processed independently so that if you match them together there may be cases of change in status which are solely a function of the processing system, not a function of any reporting by the respondent.
Those are the basic data products. The public use cross-sectional files are available through our Data Users Services Division.
Another way of accessing SIPP, by not going through Census is through a data base at the University of Wisconsin. The National Science Foundation has funded what is called SIPP Access. It is a data base system that is up at the University of Wisconsin. The contact there is Martin David, who is a Professor of Economics.
We have coming out shortly a users guide for SIPP that attempts to help people merge their way through these files; and a quality profile for SIPP, which talks a little bit about the non-sampling error aspects of the survey, and the other things you might run into.
MARY HARAHAN: We have a second speaker who will be talking about SIPP. By now you all know how very complicated it is.
ROBERT FRIEDLAND: The Employee Benefit Research Institute (EBRI) is a nonprofit, nonpartisan public policy research institute located in Washington, whose primary objective is to facilitate responsible public and private health and welfare retirement policies.
We are at the moment conducting two studies that explicitly examine the ability of retirees to finance health care for themselves and their dependents.
Both of these studies are using a number of public data bases, many of the data bases that we are discussing in these two days. One of the data bases that the two studies share in common is SIPP. SIPP is just one of the many data bases we are using for these two studies.
The first study, which should be out by this fall, is directed by my colleague Deborah Challet, and it examines the elderly's ability to finance their health care in general. I am conducting a companion study which examines financing of long term care, and I expect that to be complete a year hence.
The starting point for both studies is the economic status of the elderly, and, in particular, the degree to which the elderly are vulnerable to change, change from the loss of a spouse, illness, or inflation.
Long term care, in large part, is an issue related to retirement income adequacy. In a sense, this is why we turn to a data base like SIPP.
I was invited to talk about our views of SIPP. In particular, I would like to tell you why we chose this particular data base and how we ended up modifying SIPP to meet our purposes. In doing so, I would like to convey both the strengths and the weaknesses of this data base.
The primary reason we chose SIPP is that we felt this data could provide us with the most comprehensive picture of economic status of the elderly.
As we have just heard, it is quite a rich data base. Most of the first panel is now available. We can examine employment, earnings, sources and amount of retirement income, assets, liabilities, housing conditions, sources of health insurance including post-retirement employer provided health insurance, characteristics about current or past employers and occupations, the health and disability for any age, sex or marital group, or living arrangement that you want to put together.
SIPP will enable us to get a sense of the extent of limitations in activities of daily living (ADL), and instrumental activities of daily living (IADL).
We are able to get a sense of the degree of assistance needed, who provides that assistance, and whether or not this assistance is paid for.
In addition, some of the conditions address what health conditions were considered the primary reason for that limitation. This is for the entire population.
We can get a sense of how many days an individual spent in bed in a year. There are a few questions that ask about health care use. However, it really is limited to hospital use and ambulatory care. Unfortunately, nursing home care, in the data that is now available, is not asked. Also unfortunate is when there is exit from the survey, then there is reentry, and it is because of institutionalization, we do not know what kind of institution has been entered.
The scope in this area is wide, but it is certainly not as deep as the 1982 National Long Term Care Survey (NLTCS). The assessment for disability is somewhat limited. It is limited to hearing, vision, speaking, mobility, transferring, some light housework, meal preparation, and a broad category called "personal needs."
Cognitive disfunction and continence are not assessed, nor is there any attention paid to technological aids, such that you find in the 1982 NLTCS.
A secondary reason why we chose to use SIPP is that the data base offers potential for addressing so many different social, economic and public policy questions. Its richness is enhanced because the longitudinal nature of the core questions that we have just heard about that are asked every 4 months.
There is also a list of topical modules. There is a wide range of topical modules over the next 6 years.
The designers of SIPP I have to commend. They were ingenious in their way of minimizing the cost of collecting the data and getting the data out quickly without sacrificing, it appears, the integrity of the data.
As soon as each of the four rotation groups is interviewed, the data is prepared for release as a wave.
Each of the 4 months of data is labeled as month one through four. Corresponding month one, for example, of each of the four rotation groups of the weight is not the same as calendar month for each person in the rotation group.
Because each rotation group is interviewed one after the other, there is partial overlap.
To illustrate, when you get a wave of data, you are getting information about January in July on one quarter of the panel, and information on April is available for everybody.
It is not bad to use this approach for just one wave. But I think there are some limitations in just using one wave of data. The cost of using two waves of data increases tremendously when you try to put them together.
This is the biggest disadvantage of using SIPP. The cost of producing SIPP has been shifted to us who use the data base and minimized by Census. On one hand, as a taxpayer, I applaud this and as a researcher I get a little older trying to sort this through.
You practically need a commercial pilot's license to navigate through the relationship between rotation groups and waves. The data base is very complicated and can be very expensive to run.
We were not particularly happy with the wave format and we decided early on that we, for our purposes, needed to combine waves. We combined waves two through five to create a 12 month longitudinal file corresponding to 1984.
We started this process before Census announced that they would create a longitudinal file. I understand the longitudinal file that is available from Census is a 12 month file, but not necessarily a calendar year file.
We felt, for purposes of public policy discussion and in particular, those who deal with public policy, the ability to compare numbers from different data bases. In particular we had to worry about, after using the CPS for all these years, numbers that come out in one data base versus the numbers in the CPS.
We put together, for that reason, among other reasons, a calendar year file. That was not an easy trick.
We have just completed this process and we are now attaching to our calendar year file of core data, data from two topical modules. Topical modules from waves three and four provide us information at a point in time on assets. I am glad to hear that the second asset module is coming. We will have two point of time of assets, liabilities, health, and disability.
We have really just begun to look at the data and I am glad that we put the many waves together because one finding, not terribly surprising, was the propensity for inconsistency on the part of the respondents. The data seems to be relatively very clean on the part of the coding and the Census edits are beautiful, but they can not control for inconsistency on the part of the respondents. The inconsistency, if you are looking at the elderly, appears to increase dramatically with age, particularly when you hit around age 75.
If we had not put the waves together, we would not have seen this, and we would not have been able to come up with an algorithm to try and adjust for that.
I would like to close with a thank you to ASPE and the Office of the Assistant Secretary for Health (OASH) and all those who participated in the development of this Conference.
In some ways, finding out about data, especially forthcoming data, can be at times as frustrating as trying to find out about available community-based services for our loved ones.
In taking the analogy one step further, very often the answer depends on where you begin the process.
Having some personal experience in both of these matters, I know that the consequences cannot be compared. This forum will help a great deal as research is conducted, as markets develop, and as public policy is formulated using information, availability of these data bases will be critical in that process. If you have questions about how we put together our SIPP data base, I would be happy to answer those questions.
MARY HARAHAN: We thought it would be useful to have some discussion about other data bases which may not be so large or so complicated in-scope, but which do have relevance for long term care policy.
AURORA ZAPPOLO: The data bases that are being discussed or at least the three primary national ones, are specifically designed to address long term care issues from a national perspective.
They are of special interest because they provide current information on functionally impaired elderly people living in nursing homes and in the community.
A number of important questions can be answered by these data bases, especially relating to the magnitude of the populations that we are looking at.
However, with recent policy debates on various aspects of long term care, I am increasingly hearing that these surveys do not answer all of the questions. In particular, the kinds of topics that people say they can not find answers to are duration of nursing home stays, outcomes of such stays, the likelihood that people living in the community will need nursing home care at some point in the future, and the point in a nursing home stay at which a person depletes his or her assets and becomes a Medicaid recipient.
I have two basic points to make in answer to these concerns. The first is that some questions are better addressed at state and local levels, and can never be answered adequately by a national survey. The second is that there are studies that are already done that we just need to become more aware of. The gap is often in our knowledge about data bases, rather than in the data bases themselves.
Some of what I am going to refer to are data bases that are in progress right now and are not available for that reason.
There are a wide range of what I am calling "sub-national studies" that have been conducted at various levels, whether state or local. There are also studies in other countries that we should be looking at.
I do not in any way intend to give anything more than examples of some of these data bases that you should be aware of. I do not know where to look for a complete inventory.
Let me start with national studies. My talk originally was going to be only about sub-national studies, but it became clear as we developed the agenda that there were just some studies that should be mentioned. Those that you have heard this morning are important examples of other national studies to be aware of.
In particular, there are questions of duration, outcome, likelihood of institutionalization, Medicaid spend-down, and utilization of health resources.
We have talked at various times about the need to model long term care insurance options, for example, and measuring the magnitude of federal responsibility for nursing home coverage.
The common characteristic of many of the questions is that we need repeated measures of the same individual over time. Jennifer Madans made reference to the increasing attention being given to longitudinal surveys.
One of the major efforts going on right now that you should be aware of is NMES. NMES is collecting a full year's data on the functional status, health services utilization and expenditures not only for persons living in households, but for those living in nursing homes and in facilities for the mentally retarded.
Repeated observations of the same individuals over time will give us measures of change in functional status, admission to nursing homes and hospitals, discharge from those places and the length of time in a nursing home before someone spends down to Medicaid. Another unique aspect of NMES is in its collection of data simultaneously from persons in households and in institutions, which allows comparisons based on the same time period and using identical or similar questions.
NMES is going to be a rich data base, and although it will not be available for a few years, I think that most or all of the current questions will still be with us at that time.
The ILTCP, which Curt Mueller referred to, is the sampling frame for the institutional part of NMES, and it is important as a data base in itself. It broadens the universe of long term care facilities that we are looking at one point in that it includes facilities for the mentally retarded, as well as nursing and personal care homes.
It does not include all long term care facilities, however. Facilities for the mentally ill and the chronically physically impaired are not included. Nevertheless, it provides valuable information on the supply of services that are available according to standardized characteristics. An important point to keep in mind with the inventory is that it is a census, and because it is a census we can look at state and local level data without the limitations that come from sample surveys.
The importance of data bases on facilities used for long term care is in the analysis of supply issues. Studies which examine utilization of health resources, for example, without regard to the availability of those resources, the kind of picture you get on a national scale, can be misleading. This is especially true for those studies that are conducted in areas in which the population in that area has few alternatives for the services that they need.
Another national survey that is being developed which you might want to know about is the National Mortality Follow-Back Survey (NMFBS).
This survey, which is being done by the NCHS, includes information on utilization of nursing homes during the last year of life.
We also should become more aware of those studies that are done by the Veterans Administration (VA), because they have done a great deal of work, especially in terms of projections of the elderly.
In addition to surveys there are two special categories of national data that I just want to mention. They are relevant to long term care, even through they are not designed to be long term care data bases.
The first of these is the Decennial Census. Although the census is not designed as a long term care data base, every census has data on people living in institutions. Just as NMES on a sample survey basis will allow us to compare those in institutions with those in households, every census lets us do that.
In addition, Census is considering or has decided, I am not sure where we are at the moment in this, that in the 1990 census there will be a pair of questions that will collect the functional status of the population.
The two questions being considered are global. The first is like ADL, asking whether a person needs help in bathing, dressing or getting around inside the house. The other is an approximation of IADL, asking whether he need help in shopping, housework or getting around outside the house.
Although these items are general and they do not differentiate the kind of impairment, they are going to be the first data available on such a large scale on functional dependencies. They will provide bench-mark data from which we can access changes in the proportion of functionally impaired in different settings.
The final category of national data that I want to mention are the various administrative data systems at HCFA.
These are not available in the form of data tapes. But they are disseminated in statistical reports for the agency.
The Medicare statistical system is composed of three administrative record systems: the Health Insurance Master File (HIMF), the Provider of Service File (PSF) and the Utilization File (UF).
The HIMF contains a record on each person enrolled in Medicare, showing age and other basic information. The NLTCS was designed based on that file, or it was sampled from that file. The PSF describes hospitals, nursing homes, home health agencies and other providers who are approved to give care to Medicare beneficiaries. The UF is based on the billing records, which includes dates of service and amount billed. Since the advent of the Prospective Payment System (PPS), we also have diagnostic detail on 100 percent of the hospital bills. The combination of these three files allows both population-based and provider-based analyses. Like the Decennial Census, these data are important as overall measures of the population.
In the case of the Medicare files, they represent most of the elderly in the country and their use of covered health services.
I would like to move into the area of state data sets. Although we have national data on the Medicare population from administrative records, there is no similar data set on the Medicaid population. Consequently, the project known as Tape-to-Tape was developed at HCFA.
This project is a major effort to produce person level data on the Medicaid population; and it is in five states, California, Georgia, Michigan, New York and Tennessee. The data will eventually cover 8 years of enrollment claims and provider information which can be compared from one state to another.
One of the projects that is currently underway is directed specifically at the spend-down question, the point at which someone becomes a Medicaid recipient. SysteMetrics is developing tapes which will be used for a series of papers comparing the date of admission and the date of coverage on Medicaid. Data from the spend-down study will be available this year. The data tapes will not be available generally, in this case, because the agreements with the States require prior approval. Another part of the Tape-to-Tape analysis, in fact, that came out this week in the American Journal of Public Health, focuses on the oldest old and you might want to take a look at that article.
The development of the Tape-to-Tape project is important in health services research not only for the data it produces but for its methods, which brings me to the next part of the talk.
One of the difficulties in using most national surveys for studies of the Medicaid population is that the sample designs do not permit making specific estimates for specific states.
The cost of data collection on a national basis simply precludes the inclusion of the number of cases which would be necessary. Often, the fact that state differences are smoothed over is overlooked in analyses. In studies which focus on Medicaid recipients, the use of national estimates is actually less meaningful than the use of state estimates. Since Medicaid is a state-administered program and, in fact, varies by state in the services that are provided, it is important to recognize these differences.
Such studies should be based on the smallest geographic unit on which the data are available. Of course, even state level data can smooth over differences between urban and rural areas.
In recognition of the need for state level data another agency is emphasizing this--NCHSR.
Currently, they are assisting selected states in the development of data bases to examine spend-down. It is part of an overall project to encourage a public/private partnership in the development of financing option for long term care.
Many states have already collected and analyzed data on their long term care populations either through administrative mechanisms or occasionally through survey mechanisms.
Connecticut is one that I became aware of that has a very interesting data set. The Department of Health Services has a comprehensive longitudinal data base showing the characteristics of nursing home residents. Data are available at admission and on a fixed report date, which is the discharge date, when that is appropriate.
Additional data on prior nursing home stays and whether discharged to another health facility for each individual allows more accurate analyses of length of stay, outcomes and episodes of institutionalization than is possible with any national data base that is currently available.
Furthermore, the identification of source of payment at admission and discharge data allows analysis of Medicaid spend-down in the context of Connecticut's Medicaid program.
There is a directory of agency heads and contact persons for designated state statistical agencies. The directory was put together by NCHS as pan of its ongoing efforts to exchange information with state governments. You might want to contact the state government that you are working with, or that you are interested in collecting data on, to explore the availability of data bases.
Another source of state level data is, of course, university research. A study I would like to mention that is going on right now and has been going on for a while is at the University of Maryland. The study represents all licensed nursing homes in the state and it is a project that is funded by the National Institute on Aging (NIA). The data base is stratified to represent nursing homes at all levels of care. Data are collected from patient records within the sample nursing home similar to how the NNHS does it.
Let us look at local areas. A variety of federally-sponsored studies are available on local areas. One that is of particular prominence are the studies at NIA, especially the Established Populations for Epidemiological Studies of the Elderly (EPESE).
Richard Suzman from NIA has a handout describing all their various studies.
Let me just mention what the EPESE study is about. It was begun in 1980. These epidemiological studies were developed in three communities originally, East Boston, Massachusetts, Washington County, Iowa and New Haven, Connecticut. In 1984, a fourth community was added in Durham, North Carolina.
The project is designed to produce estimates of chronic conditions and impairments among the institutionalized elderly and eventually, over a period of time, to develop predictors of mortality, hospitalization and admission to nursing homes.
The project, I think, is going to be an important one in years to come. At this point, the only data that are available are the original cross-sectional data. If you do want to find out what is in that data collection activity, you can get a copy of the baseline data book from NIA.
This is another case in which data tapes are not available, but there is a mass of cross-sectional data that is published already.
At HCFA, the Office of Research and Demonstration is another federal agency that collects or conducts studies in smaller geographic areas.
Currently, there are over 300 studies going on that are research evaluation or demonstration projects related to the federal programs. Many of them relate to long term care, not necessarily under that name.
There are studies of nursing home case mix, home health, hospice services, the impact of prospective payment on nursing home utilization, and beneficiary awareness studies regarding their health insurance options.
The Health Care Financing Status Report, a large red volume, describes all of the extra-mural projects and many of the intramural projects that are currently under way. If you want a copy of that report, you can purchase a copy through the NTIS.
You might also want to look at the Health Care Financing Review. One of the issues, in particular, includes an article by Candace Macken describing the 1982 NLTCS.
The NCHSR is another federal agency that sponsors studies in smaller geographic areas.
They have both extra-mural and intramural research. Some of their intramural research activities have focused on such topics as the cost and economic implications of informal support, the size and sources of long term care expenditures, and the feasibility of alternative financing mechanisms, such as long term care insurance.
Other federal agencies produce data related to long term care. The important thing that I want you to know is that the place to find out about all of them is NTIS. NTIS is an archive of federal statistical information and it includes both data tapes and reports.
I wanted to also mention data bases from other countries.
Data from other countries can fall into one of two categories, and, in a sense, it is how you choose to use it. It can be cross-national, that is, comparative, or it can focus on a particular country.
The concern for the increasing size of the elderly population is not limited to the U.S. It is a worldwide concern and consequently there is a lot of research activity going on in many of the western nations.
Two examples of countries that have produced extensive relevant analyses of these populations are Canada and Sweden.
The Canadian study that I want to mention is a longitudinal study of nursing home admissions in the Province of Manitoba. It was initiated in 1974. There are four levels of nursing home care that are available there. Three of them represent levels that seem to be like our skilled and intermediate care. The lowest level of care, though, provides service that, as I interpret it, is more of a personal care service.
I think that fact alone could make it an interesting comparison for us to look at, suggesting the implications of an additional care level.
Some comparisons that have been noted by the Canadian researchers are that Manitobans enter nursing homes later than their American counterparts and they stay longer after that.
Turning our attention to Sweden, there are a number of important epidemiological studies that have been going on for some time. Most of the research that I am aware of is more in the area of epidemiology rather than health services research. However, they are moving in this direction. As you know, Sweden has a very generous national policy regarding services for the elderly and chronically impaired.
A recent law requires local jurisdictions to reduce the population in long term care institutions and prevent further institutionalizations, all under a very tight timetable. This has resulted in dramatic changes in their delivery system.
Many of these changes are still going on, and a number of studies are focused on looking at those changes. In Sweden, it is interesting to note that there is much less emphasis on national estimates than we have here.
A study which some of you may have heard of is the Longitudinal Study of the Elderly in Gothenberg, which was begun in 1971. The study collected information on personal and health characteristics of a cohort of elderly using personal interviews and physical examinations. A somewhat similar study is being developed in Lund this year.
I was fortunate last year to have the opportunity to visit long term care providers in Sweden and I think that one of the most important and interesting lessons I learned is that international research can tell us a lot about our own system.
I was asked frequently to explain some aspect of the U.S. long term care system, and usually it was something that was either difficult to explain or that gave me an insight into our own system once I thought about it.
We can learn both from other nations' views of our system and from a fresh perspective based on distancing ourselves from old habits and patterns of thinking.
I might add the same kind of fresh perspective can be gained from looking at other aspects of long term care, other than nursing homes and the elderly in the development of the part of NMES that is on the facilities for the mentally retarded.
Again, there were insights into our long term care system for the elderly as we learned about what is going on in the service system for the mentally retarded here in the U.S.
I told you at the outset that the examples I am giving are only examples for illustration. The key point to remember is to look beyond the large national data bases for other sources of information.
I have noted some of the directories. I want to repeat the key ones that you should know about. NTIS, as I said, houses most studies sponsored by the federal government.
There is the Health Care Financing Status Report which describes current research projects. There is no particular vehicle for showing all of the completed ones. That is why I draw your attention to the current one, because then you can track them, You can see when they should be completed and then find out what is available on them.
There are two others. The HHS Data Inventory, which identifies data bases throughout the Department, including a brief description and a contact person.
Again, you might want to look at those that do not particularly focus on long term care or the elderly to see where there is information that we can use in regard to long term care research.
The other collection of studies is the National Archive of Computerized Data on Aging. This is conducted by something called the Inter-University Consortium for Political and Social Research. They are located at the University of Michigan, and they have funding from the NIA to have an ongoing archive of data bases.
Universities that participate in the Consortium get data tapes free from the Consortium. However, anyone can contact them and I do not know what the charges are, but I gather that they are nominal to get information on these studies.
This particular archive includes not only national data bases but sub-national data bases. It also includes not just federally-funded projects but from any funding source.
There is no single entity, as far as I know, that identifies all long term care projects without regard to sponsorship. Clearly, we need a complete inventory of existing data bases, including published research reports and identification of those for which data tapes are available. Until such an inventory is available, it will be up to each of us to discover the less recognized data bases.
I think another important need is to synthesize and integrate the information that we can get from these various data bases.
I would like to close by repeating my theme that the answers to many of our questions are available if we increase our awareness of existing data bases and recognize that national studies are not necessary for all purposes.
With the abundance of long term care studies that have been done, we have a wonderful opportunity for researchers to discover new relationships by integrating the findings from different studies.
CHRISTINE PATTEE: I am the long term care person from Connecticut and I realized after Aurora gave this nice little summary of our data system that we are not listed in the Connecticut Data Center Contact. So if anyone would like to hear about the Connecticut data system, and we would be happy to share information with you.
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