1. Geographic variation in Medicare and the military healthcare system.
- Author
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Adesoye T, Kimsey LG, Lipsitz SR, Nguyen LL, Goodney P, Olaiya S, and Weissman JS
- Subjects
- Age Factors, Humans, Military Personnel, Racial Groups, Retrospective Studies, Sex Factors, United States, Health Expenditures statistics & numerical data, Health Services statistics & numerical data, Medicare statistics & numerical data, Military Medicine statistics & numerical data, Residence Characteristics statistics & numerical data
- Abstract
Objectives: To compare geographic variation in healthcare spending and utilization between the Military Health System (MHS) and Medicare across hospital referral regions (HRRs)., Study Design: Retrospective analysis., Methods: Data on age-, sex-, and race-adjusted Medicare per capita expenditure and utilization measures by HRR were obtained from the Dartmouth Atlas for 2007 to 2010. Similarly, adjusted data from 2007 and 2010 were obtained from the MHS Data Repository and patients assigned to HRRs. We compared high- and low-spending regions, and computed coefficient of variation (CoV) and correlation coefficients for healthcare spending, hospital inpatient days, hip surgery, and back surgery between MHS and Medicare patients., Results: We found significant variation in spending and utilization across HRRs in both the MHS and Medicare. CoV for spending was higher in the MHS compared with Medicare, (0.24 vs 0.15, respectively) and CoV for inpatient days was 0.36 in the MHS versus 0.19 in Medicare. The CoV for back surgery was also greater in the MHS compared with Medicare (0.47 vs 0.29, respectively). Per capita Medicare spending per HRR was significantly correlated to adjusted MHS spending (r = 0.3; P <.0001). Correlation in inpatient days (r = 0.29; P <.0001) and back surgery (r = 0.52; P <.0001) was also significant. Higher spending markets in both systems were not comparable; lower spending markets were located mostly in the Midwest., Conclusions: In comparing 2 systems with similar pricing schemes, differences in spending likely reflect variation in utilization and the influence of local provider culture.
- Published
- 2017