Modern Methods of Clinical Investigation (1990) / Chapter Skim
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5. Strengths and Weaknesses of Health Insurance Data Systems for Assessing Outcomes
5. Strengths and Weaknesses of Health Insurance Data Systems for Assessing Outcomes
Pages 47-67
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From page 47... ...
Of particular interest are the data generated by health insurance systems in Norm America, Europe, Australia, and New Zealand. Because health care data collected for administrative purposes are evermore available and less expensive to analyze, it is not surprising that such data bases are increasingly used in technology assessment and health policy research (1,2,3~.
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From page 48... ...
This data base should record all contacts with the health care system for each individual, with the unique identifier available to facilitate tracing. Ideally, the data base would record all hospital care, both inpatient and outpatient, services in free-standing surgery centers, activities in physician offices, entry to nursing or personal care home, health care received at home, and prescription drug use.
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From page 49... ...
At the intermediate level, Level 2 data require consistent individual identifiers on hospital discharge abstracts. Hospital claims can be sorted by date and identifying number to generate hospitalization histories for each individual.
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From page 50... ...
ROOS ET AL. TABLE 5.1 Data requirements and types of studies using hospital data Data Requirements Types of Studies Simple—Level 3 Need hospital discharge abstracts Intermediate Level 2 Need hospital discharge abstracts and consistent individual identifiers Comprehensive—Level 1 Need hospital discharge abstracts, consistent individual identifiers, and enrollment file In-hospital Mortality Volume-outcome comparisons, monitoring of individual hospitals Length of Stay Small-Area Analyses Changes over Time Timely Longitudinal Research Short-Term Readmissions Volume-Outcome Comparisons Monitoring of Individual Hospitals Quality Assurance and Cost Control Highest Quality Longitudinal Research Shortest-Term and Long-Term Outcome Studies Identification of Incident Cases Volume-Outcome Comparisons Monitoring of Individual Hospitals Choice of Treatment Small-Area Analysis by Person SOURCE: Rutkow IM (ed)
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From page 51... ...
In other words, if the mortality rate is too low to permit a statistically strong analysis, we can study additional poor outcomes, including complications reflected in hospital readmissions and patterns of physician visits. If there are insufficient cases in a given year, additional years can be examined.
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From page 52... ...
note that a primary "strength of Medicaid data for pharmacoepidemiology is the availability of detailed pharmacy records from which drug exposure history can be constructed." Most evidence suggests that events such as hospitalizations and physician visits are well recorded in health insurance systems. As discussed later, diagnoses recorded in the administrative data have limitations, which are often related to characteristics of medical practice; two physicians seeing the same patient will sometimes diagnose different entities.
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From page 53... ...
Similar design flexibility should be possible using the Medicare data. Potential for Multiple Projects Because administrative data systems are not designed for specific studies, they can be valuable for multiple projects.
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From page 54... ...
The decision tree for modeling treatment of infective endocarditis highlights the usefulness of claims data. The data base provided estimates of the probabilities of a number of events after two strategies: early surgery or attempted medical cure.
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From page 55... ...
Examples include transurethral prostatectomy and carotid endarterectomy. Studying these conditions or treatments through He claims data is relatively straightforward.
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From page 56... ...
The accuracy of procedural and diagnostic data depends upon both the physicians and the clerks involved. American Medicare data appear to record procedures performed with fair accuracy, particularly if the "order of procedure" is ignored.
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From page 57... ...
A comparison of diagnoses recorded on hospital records with those reported in the claims showed 95 percent correspondence in gallbladder disease, and 89 to 92 percent correspondence in a study of acute myocardial infarction (28,29~. Although Medicare does not include ambulatory care diagnoses with the physician claims, other data systems may contain this diagnostic information.
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From page 58... ...
Researchers have assumed that the optimal approach would incorporate primary data collection, possibly combining clinical judgment with physiologic information and diagnostic testing (18,19,231. On the other hand, the ability of researchers and clinicians to predict the morbidity and mortality following medical and surgical treatment is clearly limited.
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From page 59... ...
Computerized hospital admission/separation abstracts can be used to generate covariates, such as the Charlson comorbidity index, for risk adjustment. In assessments done in Manitoba, the addition of other sorts of information (claims from physician visits, health status indices from surveys, and even some prospectively collected clinical data)
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From page 60... ...
We need research to compare the power of additional chart review with claims-based work. Direct comparisons of predictive power and biases would define whether widespread additional data gathering is cost effective in risk adjustment.
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From page 61... ...
Linking specialized data bases with multipurpose claims data presents many research options, greatly increasing the amount and quality of data on individuals. Such capabilities are important because, no matter how much is recorded in any data base, specific items desired for a given study may not be available.
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From page 62... ...
Some relevant applications of record linkage are listed; the previously mentioned prostatectomy research used the first four linkages to help the Manitoba data base reach its potential (21: 1. Linkage of enrollment files or registries with Vital Statistics files to verify deaths and provide cause-of-death information.
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From page 63... ...
Thus, the monitoring of hospital mortality, as done by HCFA, can help select hospitals for primary data collection. Primary data collection within the hospital can be facilitated by claims data which identify individuals, by name or number, whose charts should be pulled (18~.
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From page 64... ...
This information can be obtained from clinical data base. Several valuable data bases obtained by extensive chart review are available for exploring what can and cannot be done using Medicare data.
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From page 65... ...
Use of claims data systems to evaluate health care outcomes: Mortality and reoperation following prostatectomy. Journal of the American Medical Association 1987;257:933-936.
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From page 66... ...
Using insurance claims to measure health status: The illness scale. Journal of Chronic Diseases (Suppl 1)
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From page 67... ...
Using administrative data to predict important health outcomes: Entry to hospital, nursing home, and death. Medical Care 1988;26:221-239.
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