Physician Decision Making and Variation in Hospital Admission Rates for Suspected Acute Cardiac Ischemia: A Tale of Two Towns

• Published in: Medical care 1994-11, Vol.32 (11), p.1086-1097
• Main Authors: Green, Lee A., Becker, Mark P.
• Format: Article
• Language: English
• Subjects: Acute Disease; Adolescent; Adult; Aged; Bias; Biological and medical sciences; Chest pain; Child; Child, Preschool; Communities; Confidence Intervals; Coronary care units; Decision Making; Diagnosis-Related Groups; Emergency departments; Female; Health Services Research; Hospital admissions; Humans; Infant; Infant, Newborn; Ischemia; Logistic Models; Male; Medical practice; Medical sciences; Michigan; Middle Aged; Myocardial infarction; Myocardial ischemia; Myocardial Ischemia - classification; Myocardial Ischemia - diagnosis; Myocardial Ischemia - epidemiology; Odds Ratio; Patient Admission - statistics & numerical data; Patient Discharge - statistics & numerical data; Physicians; Practice Patterns, Physicians' - statistics & numerical data; Predictive Value of Tests; Public health. Hygiene; Public health. Hygiene-occupational medicine; Retrospective Studies; Small-Area Analysis
• ISSN: 0025-7079; 1537-1948
• DOI: 10.1097/00005650-199411000-00002

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.