SMALL-AREA VARIATIONS IN HOSPITALIZATION RATES - HOW MUCH YOU SEE DEPENDS ON HOW YOU LOOK

This research investigates the degree that estimates of the magnitude of small area variations in hospitalization rates depend on both the e stimation method and the number of years of data used. Hospital discha rge abstracts for patients 65 and older from acute care hospitals in M assachusetts from 1982 to 1987 were analyzed. The SCV statistic, the a pproach used in many current small area variation studies, and empiric al Bayes (EB), an approach that adjusts more fully for the effect of r andom variation, were compared. EB estimates based on 3 years of data were best able to predict future area-specific hospitalization rates. Compared to EB estimates using 3 years of data, the SCV statistic with 1 year of data overestimated the median amount of systematic variatio n by over 70% for the 68 conditions studied; with 3 years of data, the SCV overestimated the median by 55%. Regardless of method, the same c onditions were identified as relatively more variable and the same geo graphic areas were found to have higher than expected hospitalization rates. The magnitude of differences in hospitalization rates depends o n how the data are analyzed and how many years of data are used. Hospi talization rates across small geographic. areas may vary substantially less than reported previously.