• Jodi B Segal, Najlla Nassery, Hsien-Yen Chang, Eva Chang, Kitty Chan, and John F P Bridges.
• *Johns Hopkins School of Medicine †Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.
• Med Care. 2015 Mar 1;53(3):230-6.

BackgroundOveruse can be defined as use of a service when the risk of harm exceeds its likely benefit. Yet, there has been little work with composite measures of overuse.ObjectiveOur goal was to create a composite measure of overuse with claims data.DesignObservational study using 5% of Medicare claims from 2008.SettingAll inpatient and outpatient settings of care, excluding nursing homes.ParticipantsOlder Americans receiving health care services in hospitals or outpatient settings.MeasuresWe applied algorithms to identify specific cases of overuse across 20 previously identified procedures and used multilevel modeling techniques to examine variation in overuse across all procedures. Included in the model were patient-level factors and both procedure and regional fixed effects for the 306 hospital referral regions (HRR). These estimated regional fixed effects, representing the systematic, region variation in overuse across all measures, was then normalized compared with the overall average to generate a Z score for each HRR. The resulting "Overuse Index" was then compared with total costs, 30-day postdischarge mortality, and total mortality at the HRR level, graphically, and associations were tested using Spearman ρ.ResultsThe Overuse Index varied markedly across regions, but 23 were higher than the average (P<0.05). The Index was positively associated with total costs (ρ=0.28, P<0.0001). It was positively correlated with 30-day postdischarge mortality (ρ=0.18 P≤0.005), and neither positively or negatively correlated with total mortality.ConclusionsThis study confirms previous research hypothesizing that systematic regional variation in overuse exists and is measurable. Addition research is needed to validate index and to test its predictive and concurrent validity in panel data.

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