Abstract WP147: County Level Geographic Variation in Stroke Hospitalization Rates Among Medicare Fee-For-Service Beneficiaries

Introduction: Granular regional stroke incidence data in the US is lacking. Thus, we sought to identify factors associated with county-level hospitalization rates and counties with hospitalization rates above or below expectation among Medicare fee-for-service (FFS) beneficiaries using publicly available data. Methods: Cross-sectional study based on the analysis of county-level three-year average ischemic and hemorrhagic stroke hospitalization rates (principal ICD-10 I63, I65-I66) per 100,000 population among Medicare FFS beneficiaries from 2018-2020 using publicly available data from the CDC’s Interactive Atlas of Heart Disease and Stroke (ATLAS) and other sources. Linear mixed models were fitted to investigate six sets of factors (n Total = 61) associated with county-level hospitalization rates in a serial additive stepwise fashion (i.e., demographics, overall population vascular risk factors, risk factor treatment, health delivery and access, environmental features, and socioeconomic status). We reported on the predicted hospitalization rates, fixed effects marginal R 2 , the most impactful factors using average marginal effects, and characterized proportional difference between observed and predicted hospitalization rates of the fully adjusted model. Results: The cohort of 3,198 counties and county-equivalents had a mean stroke hospitalization rate of 11.2 per 100,000 (SD= 2.6). Mean characteristics of included counties:19.4% above age 65y, 73% white, 7.6% coronary heart disease (CHD) prevalence, 38% hyperlipidemia prevalence, and 5.7 primary care physicians per 10,000. In the fully adjusted model, between-county unexplained variation was lower-than-expected but remained moderately high (Model 6 R 2 = 0.57) (Figure 1). The five most impactful factors included having a history of hypertension (a county at the 10th percentile of hypertension prevalence had a higher expected stroke hospitalization rate of 5.47 versus 7.90 at the 90th percentile), CHD, smoking, nonadherence to antihypertensive medication, and the elevation of the county above sea level (Table 1). Counties in the northwest and New England regions generally had lower-than-expected hospitalization rates (Figure 2). Conclusions: Considerable unexplained county-level variance in stroke hospitalization rates exists after accounting for a wide variety of known and potential predictors. Future work to explain unexplained variance may inform stroke mechanisms and interventions to improve systems of care.