Showing papers by "Lee A. Green published in 1994"

Physician decision making and variation in hospital admission rates for suspected acute cardiac ischemia. A tale of two towns.

Abstract: The authors tested the "uncertainty hypothesis," which holds that variations in rates of hospitalization or surgeries across small geographic areas reflect differences in physicians' decision making when confronting uncertainty. A small-areas variation analysis of suspected acute cardiac ischemia (ACI) admissions in northern Michigan was performed, and two demographically nearly identical towns differing by a factor of 3 in ACI admission rates were selected. Medical records of all patients evaluated in the emergency departments of these hospitals for suspected ACI in 1988 were abstracted retrospectively. Probabilities of ACI were objectively estimated using the Acute Cardiac Ischemia Time-Insensitive Predictive Instrument. Logistic regression of admission on patient characteristics, other illnesses, probability of ACI, and community revealed no difference in admission decisions between the two hospitals (odds ratio for community = 0.766, 95% confidence interval, 0.542-1.08, n = 787, P > .1). Nearly twice as many patients with ACI presented to the emergency department of the high-admitting hospital as to the low-admitting hospital. The authors conclude that, at least for ACI, population-based area discharge rates do not necessarily reflect case-based decision rates. Drawing inferences regarding physician decision making from discharge or claims datasets may lead to error.

Diagnosing and managing unstable angina

Abstract: This Quick Reference Guide for Clinicians contains recommendations on the care of patients with unstable angina based on a combination of evidence obtained through extensive literature reviews and consensus among members of an expert panel. Principal conclusions include the following. (1) Many patients suspected of having unstable angina can be discharged home after adequate initial evaluation. (2) Further outpatient evaluation may be scheduled for up to 72 hours after initial presentation for patients with clinical symptoms of unstable angina judged at initial evaluation to be at low risk for complications. (3) Patients with acute ischemic heart disease judged to be at intermediate or high risk of complications should be hospitalized for careful monitoring of their clinical course. (4) Intravenous thrombolytic therapy should not be

A closer examination of sex bias in the treatment of ischemic cardiac disease

Abstract: BACKGROUND: Past studies have conflicted regarding the existence of sex bias in the treatment of women with ischemic cardiac disease. This study explored the effect of different analytic models on conclusions about sex bias. METHODS: A retrospective analysis of medical records was performed on 787 patients evaluated for potential acute cardiac ischemia in the emergency departments of two nonteaching community hospitals. The Acute Coronary Ischemia Time Insensitive Predictive Instrument (ACI-TIPI) was used to estimate the likelihood of ischemic disease. The decisions to admit to hospital, not to admit to hospital, and to discharge with diagnosis of myocardial infarction were the outcome variables. RESULTS: Logistic regression models of increasing levels of detail were applied and evaluated. Analysis using summary data (similar to discharge abstracts or claims data) revealed that patient sex affected admission decisions, but an analysis of clinically detailed data by hospital was required to reveal the nature of the effect. There was disparity in admission decisions by sex at one hospital but not at the other. The odds ratio for admission (women vs men) was 0.546 (95% CI, 0.33 to 0.91) at Hospital A, and 1.22 (95% CI, 0.72 to 2.05) at Hospital B. This disparity appeared to be related to a high rate of admission (67%) among men with low (< 10%) probability of acute ischemia. CONCLUSIONS: Differences in treatment of suspected acute cardiac ischemia by sex may be a practice variation phenomenon rather than a uniform bias. When these differences occur, they may represent overtreatment of men rather than inadequate treatment of women. Because summary or billing datasets lack clinical detail, they are inadequate for the study of physician decision-making.