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1.
J Am Coll Cardiol ; 78(25): 2599-2611, 2021 12 21.
Artigo em Inglês | MEDLINE | ID: mdl-34887146

RESUMO

This review summarizes racial and ethnic disparities in the quality of cardiovascular care-a challenge given the fragmented nature of the health care delivery system and measurement. Health equity for all racial and ethnic groups will not be achieved without a substantially different approach to quality measurement and improvement. The authors adapt a tool frequently used in quality improvement work-the driver diagram-to chart likely areas for diagnosing root causes of disparities and developing and testing interventions. This approach prioritizes equity in quality improvement. The authors demonstrate how this approach can be used to create interventions that reduce systemic racism within the institutions and professions that deliver health care; attends more aggressively to social factors related to race and ethnicity that affect health outcomes; and examines how hospitals, health systems, and insurers can generate effective partnerships with the communities they serve to achieve equitable cardiovascular outcomes.


Assuntos
Equidade em Saúde , Disparidades em Assistência à Saúde/etnologia , Melhoria de Qualidade , Doenças Cardiovasculares/terapia , Humanos , Racismo Sistêmico
2.
BMC Health Serv Res ; 21(1): 5, 2021 Jan 04.
Artigo em Inglês | MEDLINE | ID: mdl-33397379

RESUMO

BACKGROUND: The HOSPITAL Risk Score (HRS) predicts 30-day hospital readmissions and is internationally validated. Social determinants of health (SDOH) such as low socioeconomic status (SES) affect health outcomes and have been postulated to affect readmission rates. We hypothesized that adding SDOH to the HRS could improve its predictive accuracy. METHODS: Records of 37,105 inpatient admissions at the University of Chicago Medical Center were reviewed. HRS was calculated for each patient. Census tract-level SDOH then were combined with the HRS and the performance of the resultant "Social HRS" was compared against the HRS. Patients then were assigned to 1 of 7 typologies defined by their SDOH and a balanced dataset of 14,235 admissions was sampled from the larger dataset to avoid over-representation by any 1 sociodemographic group. Principal component analysis and multivariable linear regression then were performed to determine the effect of SDOH on the HRS. RESULTS: The c-statistic for the HRS predicting 30-day readmission was 0.74, consistent with published values. However, the addition of SDOH to the HRS did not improve the c-statistic (0.71). Patients with unfavorable SDOH (no high-school, limited English, crowded housing, disabilities, and age > 65 yrs) had significantly higher HRS (p < 0.05 for all). Overall, SDOH explained 0.2% of the HRS. CONCLUSION: At an urban tertiary care center, the addition of census tract-level SDOH to the HRS did not improve its predictive power. Rather, the effects of SDOH are already reflected in the HRS.


Assuntos
Readmissão do Paciente , Determinantes Sociais da Saúde , Idoso , Hospitais , Humanos , Fatores de Risco , Fatores Sociais
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