County-Level Contributors to Geographic Variation in Medicare Fee-for-Service Stroke Hospitalization Rates: A Cross-Sectional Study.

BACKGROUND

Stroke hospitalization represents underlying stroke incidence and hospital utilization. We sought to identify factors associated with county-level hospitalization rates (HRs) and counties with HRs above or below expectation using publicly available data.

METHODS

This cross-sectional study is based on the analysis of county-level 3-year average stroke HRs (principal International Classification of Diseases, Tenth Revision [ICD-10], codes I60.X-I69.X) among Medicare fee-for-service beneficiaries from 2018 to 2020. Linear mixed models were fitted to investigate 6 sets of factors associated with HRs in a serial additive stepwise fashion (ie, demographics, overall population vascular risk factors, risk factor treatment, health delivery and access, environmental features, and socioeconomic status). We reported on marginal R2, the most impactful factors, and characterized proportional difference between crude and predicted HRs.

RESULTS

The cohort of 3198 (98.6%) counties and county-equivalents had a mean stroke HR of 11.2 per 100 000 (SD=2.6). The mean characteristics of the included counties were as follows: 19.4% age ≥65 years, 73% White race, 7.6% coronary heart disease prevalence, 38% hyperlipidemia prevalence, and 5.7 primary care physicians per 10 000. In the fully adjusted model, between-county unexplained variation remained moderately high (R2=0.57). The most impactful factors associated with stroke HRs were prevalence of coronary heart disease, hypertension, smoking, nonadherence to antihypertensive medication, and elevation above sea level. Counties in the northwest United States generally had lower-than-expected HRs.

CONCLUSIONS

Considerable unexplained county-level variance in stroke HRs exists after accounting for a wide variety of known and potential predictors. Future work to clarify the mechanism of known predictors and explain variance may inform interventions to improve systems of care.