Utility of Socioeconomic Status in Predicting 30-Day Outcomes After Heart Failure Hospitalization

Abstract

Background An individual's socioeconomic status (SES) is associated with health outcomes and mortality, yet it is unknown whether accounting for SES can improve risk-adjustment models for 30-day outcomes among Centers for Medicare & Medicaid Services (CMS) beneficiaries hospitalized with heart failure (HF). Methods and Results We linked clinical data on hospitalized HF patients in the Get With The Guidelines®-HF™ database (01/2005–12/2011) with CMS claims and county-level SES data from the 2012 Area Health Resources Files. We compared the discriminatory capabilities of multivariable models that adjusted for SES, patient, and/or hospital characteristics to determine whether county-level SES data improved prediction or changed hospital rankings for 30-day all-cause mortality and rehospitalization. After adjusting for patient and hospital characteristics, median household income (per $5,000 increase) was inversely associated with odds of 30-day mortality (OR 0.97, 95% CI 0.95–1.00, p=0.032), and the percentage of persons with at least a high school diploma (per 5 unit increase) was associated with lower odds of 30-day rehospitalization (OR 0.95, 95% CI 0.91–0.99).After adjustment for county-level SES data, relative to whites, Hispanic ethnicity (OR 0.70, 95% CI 0.58, 0.83) and black race (OR 0.57, 95% CI: 0.50–0.65) remained significantly associated with lower 30-day mortality, but had similar 30-day rehospitalization. County-level SES did not improve risk adjustment or change hospital rankings for 30-day mortality or rehospitalization. Conclusions County-level SES data are modestly associated with 30-day outcomes for CMS beneficiaries hospitalized with HF, but do not improve risk adjustment models based on patient characteristics alone.

Thinking Outside the Box: Treating Acute Heart Failure Outside the Hospital to Improve Care and Reduce Admissions

“…43 However, a similar study using data from GWTG-HF linked to Medicare claims and more aggregate county-level data on socioeconomic status found more modest associations between county-level socioeconomic status and 30-day outcomes. 44 Taken together, these 2 studies suggest that the local environment probably plays a role in readmissions, but a more detailed understanding of the community may be important.…”

Prevalence of Alzheimer Disease in Hospitalized Patients with Congestive Heart Failure

“…HCUP includes acute care hospital data in the United States, with all-payer (source of payment for the hospital length of stay). This database has all-payer data on hospital inpatient stays from selected states, however only few studies have focused on CHF and AD, hospital characteristics and reported studies are mainly on cost effectiveness [12][13][14] with few in longitudinal and population based studies [15].…”

“…Asians had similar rates with whites. However, when SES is included in the model, Hispanics and African Americans had modestly lower 30-day and 1-year mortality rates than Whites, but there were similar 30-day re-hospitalization rates among these ethnic groups [12,13]. A recent randomized trial of 2331 patients, with CHF and an ejection fraction (EF) ≤ 35 showed that compared to Whites, African-Americans patients (N=749) tended to be younger, had lower SES, higher rates of hypertension and diabetes with less ischemic etiology [8].…”

“…Median household income was inversely associated with a 30-day mortality risk. When SES is not included in the model, Hispanics and African Americans had higher 30-day re-admission rates than Whites [12,13]. Asians had similar rates with whites.…”

Capturing Complexity

“…6 An additional recommendation is particularly relevant to this discussion: "NQF and others … should develop strategies to identify a standard set of sociodemographic variables (patient and community-level) to be collected and made available for performance measurement and identifying disparities." 6 In this issue of Circulation: Heart Failure, Eapen et al 7 add to the body of literature on the relationship between socioeconomic variables and heart failure outcomes in a way that helps us understand how a standard set of socioeconomic variables should be collected. They used patient and hospital characteristics obtained from the well-known Get With The Guidelines-Heart Failure program to develop prediction models for 30-day readmission and mortality rates obtained from Medicare claims, compared predictions from the models with actual rates, then used Census data to assess the value of adding socioeconomic variables to the prediction models.…”