Toward a Health Statistics System for the 21st Century Summary of a Workshop (2001) / Chapter Skim
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3. Workshop Discussion
3. Workshop Discussion
Pages 31-60
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From page 31... ...
The current health statistics system, in particular, has evolved to meet many needs, but perhaps, with minimal vision to the evolution. One of the goals of the workshop was to identify current and future data gaps with respect to the health and policy questions the future health statistics system should be able to answer.
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From page 32... ...
Black stated that it is incumbent upon a national health information system to provide information on both the impact of health care on the health status of patients and the effects of other factors on this health status (see Figure 3-11. She labeled this approach a "population health perspective." Black suggested that it will be necessary to provide data to respond to a change in the policy discussions from a focus on what health care services are being provided to a focus on what is being done to improve health.
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From page 34... ...
For example, mortality data do not really help us figure out how healthy children are; hospitalization data are not sufficient because hospitalization of children is relatively rare, and individual diseases are relatively infrequent. She noted that several national surveys that contain questions on children's health, such as the National Hospital Discharge Survey, the National Ambulatory Medical Care Survey, and the National Hospital Ambulatory Medical Care Survey, are not able to distinguish child health from child ill-health.
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From page 35... ...
At the microsystem level is the informal social support network. Intersecting through that is the individual human life cycle, and what we understand about differences in health status between populations in other countries.
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From page 36... ...
The concept of what it is we should measure the definition of health and the measures of health that are appropriate to employ is an important first consideration in the development of the components of a health information system. With the idea that a proposed goal of a health statistics system is to improve health status, there was much discussion at the workshop on the definition of health and measures of health.
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From page 37... ...
Government officials at the federal, state, and community levels all need health information to guide them in their public policy decision making. In general, there was a recognition that health data are frequently not given as important a role in public policy decision making as they often merit and that there is a need to interest legislators and elected officials in the value of data collection and evaluation.
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From page 38... ...
A similar lack of appropriate data was evident in the process of developing the Health Security Act, proposed by President Clinton in 1993. Although there were data contributing to the estimates of how many people would be covered by the Health Security Act, how much it would cost the government, whether the cost of health care would increase or decrease, and whether the proposal would affect employment; there were few, if any, data contributing to the question of whether or not the HSA would actually improve the health status of Americans.
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From page 39... ...
Several workshop participants stated that regardless of the level at which health data are collected, if the information is not gathered and disseminated in a timely manner, it will cease to be relevant to decision makersnot only the government decision makers but also insurers, health care providers, and consumers. The completeness and coverage of the data are also important factors
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From page 40... ...
. mealcatlons - Quan1 - Popul; quality Enhanced Administrative data + - Longitudinal administrative - Answer Administrative Data lab results data question - Linkage of key laboratory of who values to patients' diagnoses specifi and services (e.g., hemoglobin, hemp WBC, liver/renal function)
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From page 41... ...
. certain services patients receive - No capture of OTC medication use Answer more clinically sophisticated - Difficult to create (payers do not have questions requiring understanding lab data, providers do not have data of where drug or disease impacts from the full "episode" - hospital, ER, specific lab values (relationship of specialists, pharmacy)
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From page 42... ...
For example, as many workshop participants suggested, data about subpopulations, including children with special problems and ethnic minority groups, are needed to give an accurate depiction of the health status and health care needs of all Americans. Furthermore, the lack of longitudinal data can call into question the validity of health care usage and expenditure decisions.
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From page 43... ...
. Llcatlon small sample size, and based on "ad hoc data collection." In addition, participants suggested that the quality of insurance coverage and health care can vary greatly, so that simple utilization rates of health care do not necessarily provide a good indicator of health status.
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From page 44... ...
For example, the National Immunization Survey provides data on the immunization rates of children 19-35 months of age; the Medical Expenditure Panel Survey provides data on health status; the National Household Survey on Drug Abuse provides data on the incidence and prevalence of drug use; the National Health Interview Survey provides national data on noninstitutional samples for acute illness, accidental injury, illness prevalence, health utilization; and the National Health and Nutrition Examination Survey provides national data obtained from physical examinations and physiologic and biomedical measurements. When you take into account all of the available sources that provide health data, you have an imposing collection of health data at the federal level (see Table 3-21.
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From page 45... ...
An example would be data that incorporate lab results with administrative data and allow for longitudinal analyses and linkages of key lab data to patients' diagnoses and services, as a means of attaining more efficient information collection and the ability to answer more clinically sophisticated questions. For instance, can using lab results from diabetics answer such questions as whether the diabetic is healthier in a capitated plan, or healthier when treated by a diabetologist versus a family physician, or whether the age of the physician impacts care, or whether female diabetics do better with female physicians?
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From page 46... ...
46 TOWARD A HEALTH STATISTICS SYSTEM FOR THE 215T CENTURY TABLE 3-2 Data Sources for Health Indicators Included in the Candidate Sets Health Indicator Data Source Level of Availability Mortality Infant Maternal Motor vehicle crash Alcohol-related motor vehicle crash Work injury Suicide Homicide Firearm fatality Lung cancer Breast cancer Cardiovascular disease Stroke Diabetes Unintentional injury Residential fire Morbidity HIV AIDS TB Measles Syphilis Gonorrhea Hypertension Hypercholesterolemia End-stage renal disease Asthma hospitalization Cumulative trauma disorders Depression Reported disability Hospital days/100,000 Years potential life lost ~ · · r · 1nmerglng Infectious ulseases Food/water-borne diseases Hospital admissions Vital Statistics Vital Statistics Vital Statistics, EARS EARS CFOI Vital Statistics Vital Statistics Vital Statistics Vital Statistics Vital Statistics Vital Statistics Vital Statistics Vital Statistics Vital Statistics Vital Statistics NNDSS NNDSS NNDSS NNDSS NNDSS NNDSS BRFSS, NHANES, NHIS BRFSS, NHANES, NHIS HCFA NHDS ASOII NCS, ECAS BRFSS, NHIS NHIS Vital Statistics NNDSS NNDSS NHDS Local, State, National Local, State, National Local, State, National State, National State, National Local, State, National Local, State, National Local, State, National Local, State, National Local, State, National Local, State, National Local, State, National Local, State, National Local, State, National Local, State, National Local, State, National Local, State, National Local, State, National Local, State, National Local, State, National Local, State, National State, National State, National State, National Some State, National Some State, National National State, National Some State, National Local, State, National State, National State, National Local, State, National
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From page 47... ...
. room VlSltS Seatbelt use Firearm storage Overweight Sedentary pattern Untreated dental caries Air quality exposure Health insurance/loss High school graduation rate Childhood poverty MSA, State, National State, National State, National State, National National National Vital Statistics NSFG,YRBS Vital Statistics, NSFG Vital Statistics NSFG,YRBS Vital Statistics Local, State, National National Local, State, National Local, State, National National Local, State, National Ross Labs, NSFG State, National NHSDA/NHIS/YRBS/MFS National NHSDA/NHIS/YRBS/MFS National NHSDA/NHIS/YRBS/MFS National NHSDA/NHIS/YRBS/MFS National NHIS BRFSS, NHIS BRFSS, NHANES BRFSS, NHANES, NHIS NHANES AIRS NHIS, Census, MEPS NCES Census State, National State, National State, National State, National National (Non-attainment areas)
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From page 48... ...
the workshop encouraged the development of a greater connection between federal agencies and the private sector, so that each sector could have additional, useful information that it would be unable to collect on its own, and so that costly overlap among the public and private sectors could be reduced. Discussion of linkage of government and private sector resources highlights an interesting question: At what level or levels should linkages of health data take place?
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From page 49... ...
Dorothy Rice provided a brief overview of the changes that have occurred over the years in regard to data collection. From in-home interviews to random-digit telephone dialing, computer-assisted telephone surveys, and computer-assisted interviews, the progress of technology in general has had positive effects on health statistics.
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From page 50... ...
When there is a distrust among survey participants concerning how their information will be used by federal, state, and local governments or by private organizations, the data collection process will inevitably become more difficult and incomplete. Dorothy Rice summarized these difficulties by stating that "both individuals and businesses are questioning how the information is used and who has access to it.
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From page 51... ...
, reported to the workshop attendees that the DHHS has been developing privacy regulations in connection with the Health Insurance Portability and Accountability Act (HIPAA) legislation.]
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From page 52... ...
Furthermore, Jacqueline Kosecoff suggested that in many circumstances health plans need to submit data that are scrambled and "scrambled data are really hard to link with previously scrambled data." John Eisenberg commented that he considered the proposed regulations to be "a terrific document. It really does bring together control and assurance to the public that their data is being held confidential, and yet a recognition that there are certain goods that we have to keep .
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From page 53... ...
Matrix masking involves transforming the data by recoding or releasing only subsets of the data, but leaving the essence of the data in tact. One of the difficulties with this approach is that anonymity is not always assured by simply removing identifiers or variables from the data sets.
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From page 54... ...
Another important feature of using a population-based system is that it "enables the user to simultaneously relate characteristics that affect a population's need for health care to that population's use of health care, to that area's supply of health care resources, and finally, to the health status of a population." Black suggested that a prerequisite of a strong health information system is a strong health data system. The data system used by POPULIS is a population-based research registry that captures data provided by the Manitoba provincial health insurance administration system.
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From page 55... ...
Black emphasized that when designing population-based health surveys, the possibility for linking data and conducting validity studies using administrative data should be foreseen and incorporated into study design. In Manitoba, with the expansion of national, longitudinal, population health services, there has been explicit consideration given to the potential to link detailed data from surveys to the population-based study that comes from the administrative registry information.
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From page 56... ...
Other collaborations include the European and international standardization committees, joint health statistics meetings between the World Health Organization and the European Economic Community (EEC) , and several initiatives that fall under the Global Healthcare Applications Project.
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From page 57... ...
Dorothy Rice echoed this sentiment when she said that the private sector should be an important contributor to future health information systems. Jacqueline Kosecoff stated that it is not necessarily optimal to have all the data that a particular hospital or health care provider has collected.
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From page 58... ...
Jacqueline Kosecoff suggested that whichever organization could make data available cheaply and efficiently should take the lead regardless of whether it is a public- or private-sector organization. She continued by saying that researchers should stop arguing over who will house the data sources and worry more about getting a system in place.
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From page 59... ...
Kenneth Thorpe, for example, noted that the federal government is spending hundreds of millions of dollars on health data and that private foundations are doing the same thing, but with much overlap among disparate surveys. Consolidation and integration might be a way to defragment the data collection process.
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From page 60... ...
National Research Council 2000 Improving Access to and Confidentiality of Research Data: Report of a Workshop. Committee on National Statistics, Christopher Mackie and Norman Bradburn, eds.
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