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Biomedical subjects

E Keeler

Publications and source records attributed to E Keeler.

6 recordsLinked to original sources
PubMed1990

Explaining variations in hospital death rates. Randomness, severity of illness, quality of care.

We used administrative (Part A Medicare) data to identify a representative sample of 1126 patients with congestive heart failure and 1150 with acute myocardial infarction in hospitals with significant unexpectedly high inpatient, age-sex-race-disease-specific death rates ("targeted") vs all other ("untargeted") hospitals in four states. Although death rates in targeted hospitals were 5.0 to 10.9 higher per 100 admissions than in untargeted hospitals, 56% to 82% of the excess could result from purely random variation. Differences in the quality of the process of care (based on a medical record review) could not explain the remaining statistically significant differences in mortality. Comparing targeted hospitals with subsets of untargeted ones, eg, those with lower than expected death rates, did not affect this conclusion. Severity of illness explained up to 2.8 excess deaths per 100 admissions for patients with myocardial infarction. Identifying hospitals that provide poor-quality care based on administrative data and single-year death rates is unlikely; targeting based on time periods greater than 1 year may be better.

Aged↗
PubMed1990

Patterns of outpatient mental health care over time: some implications for estimates of demand and for benefit design.

The article examines patterns of starting and continuing outpatient mental health care as a function of time, and the implications of these patterns for estimates of the response of demand to generosity of fee-for-service insurance coverage. The data are from the RAND Health Insurance Experiment (HIE), which acquired a random sample of the nonelderly general population in six U.S. sites. People rarely had more than one episode of use of outpatient mental health services in a year. Persons who used in the prior year had high rates of continuing in treatment, while those without prior use entered treatment at a low, steady rate. Similar patterns of use by former users and nonusers were observed across insurance plans that varied widely in generosity, but the absolute probabilities of use were significantly lower in less generous plans. The probability of use of mental health services expanded significantly over time in the HIE; thus, estimates of demand in a steady state would be higher than those based on the HIE study years.

Community Mental Health Services↗
PubMed1978

A new planning methodology to assess the impact of the health care system on health status.

This article summarizes a new methodology recently developed by the Rand Corporation which permits health planners to assess the impact of the local health care system on the health status of the population. The methodology, in algorithm form, should assist health planners in developing objectives and actions related to the occurrence of selected health status indicators and should be amenable to health care interventions. Emphasis has been placed on developing a simplified, approximate analysis that health planners will find both feasible and effective. No detailed mathematic analyses are called for. The data required are, in most instances, readily obtainable. The algorithm is a methodology by which HSAs can investigate determinants of health status, identify breakdowns in the health care system, and specify needed improvements in the system. The goal of these algorithms is to assist HSAs to obtain valid and sufficiently detailed data that will provide a basis for monitoring breakdowns in the health care system and to improve planning decisions aimed at preventing such breakdowns. This should, in turn, affect population health status in the planning area.

Breast Neoplasms↗
PubMed1977

Decision analysis.

Explore the source record for details and available documents.

Bayes Theorem↗
PubMed1976

Effects of pooled samples.

Pooling of specimens before testing may reduce the costs of expensive tests for rare conditions. This paper presents models of how test performance is degraded by such pools, and of the financial savings that pooling allows. The method of computing optimal pool size is demonstrated on a screening test and on the test for gastrin. Test characteristics that make pooling especially effective are listed.

Clinical Laboratory Techniques↗