Development and Implementation of a Maryland State Program Providing Hospital Payment Incentives for Reduction in Readmission Disparities.

BACKGROUND: Social factors are a key determinant of hospital readmission. We describe the development of the country's first statewide policy providing hospitals with financial incentives to reduce readmission disparities. OBJECTIVE: To describe the development and evaluation of a novel program that measures hospital-level disparity in readmission and rewards hospitals for improvement. RESEARCH DESIGN: Observational study using inpatient claims. PARTICIPANTS: Baseline data included 454,372 all-cause inpatient discharges in 2018 and 2019. Of the included discharges, 34.01% involved Black patients, 40.44% involved female patients, 33.1% involved patients covered by Medicaid, and 11.76% involved patients who were readmitted. Mean age was 55.18. MEASURES: The key measure was the percentage change over time within the hospital in readmission disparity. Readmission disparity was measured using a multilevel model that gauged the association between social factors and readmission risk at a given hospital. Three social factors (Race, Medicaid coverage, and Area Deprivation Index) were combined into an index reflecting exposure to social adversity. RESULTS: Of the State's 45 acute-care hospitals, 26 exhibited improved disparity performance in 2019. LIMITATIONS: The program is limited to inpatients within a single state; the analysis does not provide evidence on the causal relationship between the intervention and readmission disparities. CONCLUSION: This represents the first large-scale effort in the US to link disparities to hospital payment. Because the methodology relies on claims data, it could easily be adopted elsewhere. The incentives are directed to within-hospital disparities, thus mitigating concerns about penalizing hospitals with patients with greater social exposure. This methodology could be used to measure disparity in other outcomes.

Safety-Net Hospitals, Neighborhood Disadvantage, and Readmissions Under Maryland's All-Payer Program: An Observational Study.

Background: Safety-net hospitals have higher-than-expected readmission rates. The relative roles of the mean disadvantage of neighborhoods the hospitals serve and the disadvantage of individual patients in predicting a patient's readmission are unclear. Objective: To examine the independent contributions of the patient's neighborhood and the hospital's service area to risk for 30-day readmission. Design: Retrospective observational study. Setting: Maryland. Participants: All Maryland residents discharged from a Maryland hospital in 2015. Measurements: Predictors included the disadvantage of neighborhoods for each Maryland resident (area disadvantage index) and the mean disadvantage of each hospital's discharged patients (safety-net index). The primary outcome was unplanned 30-day hospital readmission. Generalized estimating equations and marginal modeling were used to estimate readmission rates. Results were adjusted for clinical readmission risk. Results: 13.4% of discharged patients were readmitted within 30 days. Patients living in neighborhoods at the 90th percentile of disadvantage had a readmission rate of 14.1% (95% CI, 13.6% to 14.5%) compared with 12.5% (CI, 11.8% to 13.2%) for similar patients living in neighborhoods at the 10th percentile. Patients discharged from hospitals at the 90th percentile of safety-net status had a readmission rate of 14.8% (CI, 13.4% to 16.1%) compared with 11.6% (CI, 10.5% to 12.7%) for similar patients discharged from hospitals at the 10th percentile of safety-net status. The association of readmission risk with the hospital's safety-net index was approximately twice the observed association with the patient's neighborhood disadvantage status. Limitations: Generalizability outside Maryland is unknown. Confounding may be present. Conclusion: In Maryland, residing in a disadvantaged neighborhood and being discharged from a hospital serving a large proportion of disadvantaged neighborhoods are independently associated with increased risk for readmission. Primary Funding Source: National Institute on Minority Health and Health Disparities and Maryland Health Services Cost Review Commission.

Beta-Blocker Use in Hypertension and Heart Failure (A Secondary Analysis of the Systolic Blood Pressure Intervention Trial).

Given the concern that beta-blocker use may be associated with an increased risk for heart failure (HF) in populations with normal left ventricular systolic function, we evaluated the association between beta-blocker use and incident HF events, as well as loop diuretic initiation in the Systolic Blood Pressure Intervention Trial (SPRINT). SPRINT demonstrated that a blood pressure target of <120 mm Hg reduced cardiovascular outcomes compared with <140 mm Hg in adults with at least one cardiovascular risk factor and without HF. The lower rate of the composite primary outcome in the 120 mm Hg group was primarily driven by a reduction in HF events. Subjects on a beta blocker for the entire trial duration were compared with subjects who never received a beta blocker after 1:1 propensity score matching. A competing risk survival analysis by beta-blocker status was performed to estimate the effect of the drug on incident HF and was then repeated for a secondary end point of cardiovascular disease death. Among the 3,284 propensity score-matched subjects, beta-blocker exposure was associated with an increased HF risk (hazard ratio 5.86; 95% confidence interval 2.73 to 13.04; p <0.001). A sensitivity analysis of propensity score-matched cohorts with a history of coronary artery disease or atrial fibrillation revealed the same association (hazard ratio 3.49; 95% confidence interval 1.15 to 10.06; p = 0.028). In conclusion, beta-blocker exposure in this secondary analysis was associated with increased incident HF in subjects with hypertension without HF at baseline.

Measuring Structural Racism and Its Association With BMI.

INTRODUCTION: Structural racism has attracted increasing interest as an explanation for racial disparities in health, including differences in adiposity. Structural racism has been measured most often with single-indicator proxies (e.g., housing discrimination), which may leave important aspects of structural racism unaccounted for. This paper develops a multi-indicator scale measuring county structural racism in the U.S. and evaluates its association with BMI. METHODS: County structural racism was estimated with a confirmatory factor model including indicators reflecting education, housing, employment, criminal justice, and health care. Using Behavioral Risk Factor Surveillance Survey data (2011-2012) and a mixed-effects model, individual BMI was regressed on county structural racism, controlling for county characteristics (mean age, percentage black, percentage female, percentage rural, median income, and region). Analysis occurred 2017-2019. RESULTS: The study included 324,572 U.S. adults. A 7-indicator county structural racism model demonstrated acceptable fit. County structural racism was associated with lower BMI. Structural racism and black race exhibited a qualitative interaction with BMI, such that racism was associated with lower BMI in whites and higher BMI in blacks. In a further interaction analysis, county structural racism was associated with larger increases in BMI among black men than black women. County structural racism was associated with reduced BMI for white men and no change for white women. CONCLUSIONS: The results confirm structural racism as a latent construct and demonstrate that structural racism can be measured in U.S. counties using publicly available data with methods offering a strong conceptual underpinning and content validity. Further study is necessary to determine whether addressing structural racism may reduce BMI among blacks.

Association of ß-Blocker Use With Heart Failure Hospitalizations and Cardiovascular Disease Mortality Among Patients With Heart Failure With a Preserved Ejection Fraction: A Secondary Analysis of the TOPCAT Trial.

Importance: ß-Blockers are prescribed to most patients with heart failure (HF) with a preserved ejection fraction (HFpEF), but their effect on HFpEF remains unclear. Objective: To determine the association of ß-blocker use with HF hospitalizations and cardiovascular disease (CVD) mortality, overall and in strata of patients with an ejection fraction (EF) of 50% or greater or less than 50%. Design, Setting, and Participants: For 1761 participants from North and South America enrolled in the multicenter, double-blinded Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist randomized clinical trial of spironolactone for patients with HFpEF between August 10, 2006, and January 31, 2012, the association of baseline ß-blocker use with HF hospitalization and CVD mortality was analyzed using unadjusted and adjusted Cox proportional hazards regression models, overall and in strata of patients with an EF of 50% or greater or less than 50%. Participants had symptomatic HF with a left ventricular EF of 45% or greater, with enrollment based on either hospitalization attributed to decompensated HF in the prior year or elevated natriuretic peptide levels. Statistical analysis was performed from January 31 to May 2, 2019. Exposure: Use of ß-blockers. Main Outcomes and Measures: Incident HF hospitalization and CVD mortality. Results: Among 1761 participants included in the analysis (879 women and 882 men; mean [SD] age, 71.5 [9.6] years), 1394 (79.2%) reported ß-blocker use and 1567 (89.0%) had an EF of 50% or greater. Hospitalizations for HF occurred for 399 participants (22.7%), and CVD mortality occurred for 229 participants (13.0%). Use of ß-blockers was associated with a higher risk of HF hospitalization among patients with HFpEF with an EF of 50% or greater (hazard ratio, 1.74 [95% CI, 1.28-2.37]; P < .001) but not among patients with an EF between 45% and 49% (hazard ratio, 0.68 [95% CI, 0.28-1.63]; P = .39). There was a significant interaction between ß-blocker use and EF threshold for incident HF hospitalizations (P = .03). Use of ß-blockers was not associated with a change in CVD mortality. Conclusions and Relevance: For patients with an EF of 50% or greater, ß-blocker use was associated with an increased risk of HF hospitalizations but not CVD mortality. For patients with an EF between 45% and 49%, there was no such association.