Estimating hospital admission patterns using Medicare data.
It is often necessary in health services research and strategic planning to simultaneously describe the geographic pattern of admissions to multiple hospitals. Obtaining the data necessary to accomplish this can often be problematic. In some states discharge abstract data on all admissions to all hospitals in the state are compiled and maintained by a government agency, but in 23 states these data are not available. Furthermore, problems arise when a substantial fraction of admissions cross state borders, such that data from more than one state is required for description of 'patient flows'. Individual hospitals typically maintain data on the geographic source of their own admissions, but are not likely to have access to such data regarding other hospitals in their area. Patient flow data on Medicare admissions are available for all states and are readily accessible, but heretofore it has not been known how closely the admission patterns of Medicare patients approximate those of other types of patients. We examine the accuracy of using data on Medicare admissions to estimate, at the hospital level, the admission patterns of other types of patients. Using zip code-to-hospital patient flow data for all non-federal hospitals in California, we calculated the correlation between Medicare admission patterns and those of three other groups of patients (other adults, pediatrics and obstetrics) for each hospital. For the majority of hospitals, Medicare data predict the admissions of other adults quite well, and the admissions of pediatric and obstetric admissions moderately well.(ABSTRACT TRUNCATED AT 250 WORDS)
Radany
M H
MH
Institute for Health Policy Studies, University of California at San Francisco 94109.
Luft
H S
HS
D000328:Adult; D002140:California; D002391:Catchment Area, Health / Q000706:statistics & numerical data*; D002648:Child; D005843:Geography; D006761:Hospitals / Q000706:statistics & numerical data*; D006780:Hospitals, Rural / Q000706:statistics & numerical data; D006786:Hospitals, Urban / Q000706:statistics & numerical data; D006801:Humans; D006278:Medicare / Q000706:statistics & numerical data*; D010343:Patient Admission / Q000706:statistics & numerical data*; D011177:Postal Service; D014481:United States