Measuring hospital‐specific disparities by dual eligibility and race to reduce health inequities

Lloren, Anouk; Liu, Shilin; Herrin, Jeph; Lin, Zhenqiu; Zhou, Guohai; Wang, Yongfei; Kuang, Meng; Zhou, Sheng; Farietta, Thalia; McCole, Kerry; Charania, Sana; Sheares, Karen Dorsey; Bernheim, Susannah M.

doi:10.1111/1475-6773.13108

Cited by 26 publications

(47 citation statements)

References 23 publications

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“…Patient social determinants of health also offer insights into assessing risk for rehospitalization. Furthermore, our results align with earlier findings that Black Medicare patients have higher hospital readmissions rates even after controlling for multiple patient-level factors [ 19 , 20 , 21 ]. Previous indicators of healthcare access in these studies, such as insurance status and income, did not play a significant role in predicting readmissions in the current study.…”

Section: Discussionsupporting

confidence: 91%

Effect Modification by Social Determinants of Pharmacogenetic Medication Interactions on 90-Day Hospital Readmissions within an Integrated U.S. Healthcare System

Saulsberry

Singh

Pruitt

et al. 2022

JPM

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The present study builds on our prior work that demonstrated an association between pharmacogenetic interactions and 90-day readmission. In a substantially larger, more diverse study population of 19,999 adults tracked from 2010 through 2020 who underwent testing with a 13-gene pharmacogenetic panel, we included additional covariates to evaluate aggregate contribution of social determinants and medical comorbidity with the presence of identified gene-x-drug interactions to moderate 90-day hospital readmission (primary outcome). Univariate logistic regression analyses demonstrated that strongest associations with 90 day hospital readmissions were the number of medications prescribed within 30 days of a first hospital admission that had Clinical Pharmacogenomics Implementation Consortium (CPIC) guidance (CPIC medications) (5+ CPIC medications, odds ratio (OR) = 7.66, 95% confidence interval 5.45–10.77) (p < 0.0001), major comorbidities (5+ comorbidities, OR 3.36, 2.61–4.32) (p < 0.0001), age (65 + years, OR = 2.35, 1.77–3.12) (p < 0.0001), unemployment (OR = 2.19, 1.88–2.64) (p < 0.0001), Black/African-American race (OR 2.12, 1.47–3.07) (p < 0.0001), median household income (OR = 1.63, 1.03–2.58) (p = 0.035), male gender (OR = 1.47, 1.21–1.80) (p = 0.0001), and one or more gene-x-drug interaction (defined as a prescribed CPIC medication for a patient with a corresponding actionable pharmacogenetic variant) (OR = 1.41, 1.18–1.70). Health insurance was not associated with risk of 90-day readmission. Race, income, employment status, and gene-x-drug interactions were robust in a multivariable logistic regression model. The odds of 90-day readmission for patients with one or more identified gene-x-drug interactions after adjustment for these covariates was attenuated by 10% (OR = 1.31, 1.08–1.59) (p = 0.006). Although the interaction between race and gene-x-drug interactions was not statistically significant, White patients were more likely to have a gene-x-drug interaction (35.2%) than Black/African-American patients (25.9%) who were not readmitted (p < 0.0001). These results highlight the major contribution of social determinants and medical complexity to risk for hospital readmission, and that these determinants may modify the effect of gene-x-drug interactions on rehospitalization risk.

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Section: Discussionsupporting

confidence: 91%

Effect Modification by Social Determinants of Pharmacogenetic Medication Interactions on 90-Day Hospital Readmissions within an Integrated U.S. Healthcare System

Saulsberry

Singh

Pruitt

et al. 2022

JPM

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“…This is because, unlike risk adjustment using patient factors, stratification by peer group is based on a single hospital-level factor (proportions of dually eligible patients) that may reflect only part of the risk associated with readmissions. 9,10 If so, the stratification approach may still unfairly penalize hospitals with high proportions of at-risk patients, including safety net hospitals.…”

Section: Introductionmentioning

confidence: 99%

Are Improvements Still Needed to the Modified Hospital Readmissions Reduction Program: a Health and Retirement Study (2000–2014)?

et al. 2020

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BACKGROUND:To address concerns that the Hospital Readmissions Reduction Program (HRRP) unfairly penalized safety net hospitals treating patients with high social and functional risks, Medicare recently modified HRRP to compare hospitals with similar proportions of high-risk, dual-eligible patients ("peer group hospitals"). Whether the change fully accounts for patients' social and functional risks is unknown. OBJECTIVE: Examine risk-standardized readmission rates (RSRRs) and hospital penalties after adding patient-level social and functional and community-level risk factors. DESIGN: Using 2000-2014 Medicare hospital discharge, Health and Retirement Study, and community-level data, latent factors for patient social and functional factors and community factors were identified. We estimated RSRRs for peer groups and by safety net status using four hierarchical logistic regression models: "base" (HRRP model); "patient" (base plus patient factors); "community" (base plus community factors); and "full" (all factors). The proportion of hospitals penalized was calculated by safety net status. PATIENTS: 20,255 fee-for-service Medicare beneficiaries (65+) with eligible index hospitalizations MAIN MEASURES: RSRRs KEY RESULTS: Half of safety net hospitals are in peer group 5. Compared with other hospitals, peer group 5 hospitals (most dual-eligibles) treated sicker, more functionally limited patients from socially disadvantaged groups. RSRRs decreased by 0.7% for peer groups 2 and 4 and 1.3% for peer group 5 under the patient and full (versus base) models. Measured performance improved after adjusting for patient risk factors for hospitals in peer group 4 and 5 hospitals, but worsened for those in peer groups 1, 2, and 3. Under the patient (versus base) model, fewer safety net hospitals (48.7% versus 51.3%) but more non-safety net hospitals (50.0% versus 49.1%) were penalized. CONCLUSIONS: Patient-level risk adjustment decreased RSRRs for hospitals serving more at-risk patients and proportion of safety net hospitals penalized, while modestly increasing RSRRs and proportion of non-safety net hospitals penalized. Results suggest HRRP modifications may not fully account for hospital variation in patientlevel risk.

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“…The first model used the standard CMS disparities method (model 1). 1,4 Briefly, this is a mixed effects logistic regression model with patient clinical risk factors, an indicator for DE status, a random intercept and a…”

Section: Discussionmentioning

confidence: 99%

“…Cohort selection criteria followed publicly reported measure specifications used by CMS; we further divided the cohort by DE status, defined as eligibility for full state Medicaid benefits. 1,21 We included multiple admissions per patient if they were separated by at least 30 days. To ensure adequate data for clinical risk adjustment, we included only admissions for which patients were continuously enrolled in Medicare for at least 12 months prior to the index admission.…”

Section: Study Design and Populationmentioning

confidence: 99%

“…Low-income older US adults who are dually eligible (DE) for both Medicare and Medicaid insurance often experience worse outcomes and higher rates of readmission following hospitalization. 1 In recent years, numerous government programs and policies have aimed to mitigate these inequities, including by enhancing integration of medical and social resources aimed to improve outcomes for DE adults. 2,3 Starting in 2018, the Centers for Medicare & Medicaid Services (CMS) began reporting disparities in readmission rates for DE patients, with all US hospitals now receiving confidential reports of their hospital-specific disparities in condition-specific 30-day risk-adjusted readmission rates for DE patients.…”

Section: Introductionmentioning

confidence: 99%

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Factors Associated With Disparities in Hospital Readmission Rates Among US Adults Dually Eligible for Medicare and Medicaid

et al. 2022

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IMPORTANCE Low-income older adults who are dually eligible (DE) for Medicare and Medicaid often experience worse outcomes following hospitalization. Among other federal policies aimed at improving health for DE patients, Medicare has recently begun reporting disparities in withinhospital readmissions. The degree to which disparities for DE patients are owing to differences in community-level factors or, conversely, are amenable to hospital quality improvement, remains heavily debated. OBJECTIVE To examine the extent to which within-hospital disparities in 30-day readmission rates for DE patients are ameliorated by state-and community-level factors. DESIGN, SETTING, AND PARTICIPANTS In this retrospective cohort study, Centers for Medicare & Medicaid Services (CMS) Disparity Methods were used to calculate within-hospital disparities in 30-day risk-adjusted readmission rates for DE vs non-DE patients in US hospitals participating in Medicare. All analyses were performed in February and March 2019. The study included Medicare patients (aged Ն65 years) hospitalized for acute myocardial infarction (AMI), heart failure (HF), or pneumonia in 2014 to 2017. MAIN OUTCOMES AND MEASURES Within-hospital disparities, as measured by the rate difference (RD) in 30-day readmission between DE vs non-DE patients following admission for AMI, HF, or pneumonia; variance across hospitals; and correlation of hospital RDs with and without adjustment for state Medicaid eligibility policies and community-level factors. RESULTSThe final sample included 475 444 patients admitted for AMI, 898 395 for HF, and 1 214 282 for pneumonia, of whom 13.2%, 17.4%, and 23.0% were DE patients, respectively. Dually eligible patients had higher 30-day readmission rates relative to non-DE patients (RD >0) in 99.0% (AMI), 99.4% (HF), and 97.5% (pneumonia) of US hospitals. Across hospitals, the mean (IQR) RD between DE vs non-DE was 1.00% (0.87%-1.10%) for AMI, 0.82% (0.73%-0.96%) for HF, and 0.53% (0.37%-0.71%) for pneumonia. The mean (IQR) RD after adjustment for community-level factors was 0.87% (0.73%-0.97%) for AMI, 0.67% (0.57%-0.80%) for HF, and 0.42% (0.29%-0.57%) for pneumonia. Relative hospital rankings of corresponding within-hospital disparities before and after community-level adjustment were highly correlated (Pearson coefficient, 0.98). CONCLUSIONS AND RELEVANCEIn this cohort study, within-hospital disparities in 30-day readmission for DE patients were modestly associated with differences in state Medicaid policies and community-level factors. This suggests that remaining variation in these disparities should be the focus of hospital efforts to improve the quality of care transitions at discharge for DE patients in efforts to advance equity.

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Measuring hospital‐specific disparities by dual eligibility and race to reduce health inequities

Cited by 26 publications

References 23 publications

Effect Modification by Social Determinants of Pharmacogenetic Medication Interactions on 90-Day Hospital Readmissions within an Integrated U.S. Healthcare System

Effect Modification by Social Determinants of Pharmacogenetic Medication Interactions on 90-Day Hospital Readmissions within an Integrated U.S. Healthcare System

Are Improvements Still Needed to the Modified Hospital Readmissions Reduction Program: a Health and Retirement Study (2000–2014)?

Factors Associated With Disparities in Hospital Readmission Rates Among US Adults Dually Eligible for Medicare and Medicaid

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