Insurance Status and Socioeconomic Factors Affect Early Mortality After Cardiac Valve Surgery.

OBJECTIVE: To characterize the effects markers of socioeconomic status (SES), including race and ethnicity, health insurance status, and median household income by zip code on in-patient mortality after cardiac valve surgery. DESIGN: Retrospective cohort study of adult valve surgery patients included in the State Inpatient Databases and Healthcare Cost and Utilization Project. The primary outcome was mortality during the index admission. Bivariate analyses and multivariate regression models were used to assess the independent effects of race and ethnicity, payer status, and median income by patient zip code on in-hospital mortality. DESIGN: Multistate database of hospitalizations from 2007 to 2014 from New York, Florida, Kentucky, California, and Maryland. PARTICIPANTS: In total, 181,305 patients ≥18 years old underwent mitral or aortic valve repair or replacement and met the inclusion criteria. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Mortality rates were higher among black (5.59%) than white patients (4.28%, p < 0.001) and among Medicaid (4.66%), Medicare (5.22%), and uninsured (4.58%) patients compared with private insurance (2.45%, p < 0.001). After controlling for age, sex, presenting comorbidities, urgent or emergent operative status, and hospital case volume, mortality odds remained significantly elevated for black (odds ratio [OR] 1.127, confidence interval [CI] 1.038-1.223), uninsured (OR 1.213, CI 1.020-1.444), Medicaid (OR 1.270, 95% CI 1.116-1.449) and Medicare (OR 1.316, 95% CI 1.216-1.415) patients. CONCLUSIONS: Markers of low SES, including race/ethnicity, insurance status, and household income, are associated with increased risk of in-hospital mortality following cardiac valve surgery. Further research is warranted to understand and help decrease mortality risk in underinsured, less-wealthy and non-white patients undergoing cardiac valve surgery.

Insurance Status and Socioeconomic Markers Affect Readmission Rates After Cardiac Valve Surgery.

OBJECTIVE: To characterize the effect of insurance status and other socioeconomic markers on readmission rates after cardiac valve surgery. DESIGN: Retrospective cohort study using data from the State Inpatient Databases and Healthcare Cost and Utilization Project. SETTING: Multistate database of all hospitalizations from 2007-2014 from New York, Florida, California, and Maryland. PARTICIPANTS: A total of 147,752 patients ≥18 years old who underwent valve repair and/or replacement were included in the study. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Primary outcomes were unadjusted rates and adjusted odds of 30- and 90-day readmissions. The overall 30-day readmission rate was 19.4%, with the highest rates in the Medicaid (22.9%) and Medicare (21.3%) groups and lowest rates in the private insurance group (14.3%; p < 0.001). Similarly, the overall 90-day readmission rate was 27.6%, with Medicaid (32.7%) and Medicare (30.3%) again demonstrating the highest rates and private insurance (20.0%; p < 0.001) demonstrating the lowest. Compared with private insurance, Medicaid conferred the highest odds of 30-day readmission (odds ratio [OR] 1.30, 95% confidence interval [CI] 1.23-1.39) followed by Medicare (OR 1.27, 95% CI 1.21-1.33). Similarly, increased odds were seen for 90-day readmission for Medicaid (OR 1.36, 95% CI 1.28-1.43) and Medicare (OR 1.32, 95% CI 1.26-1.37). Other readmission risk factors included black or Hispanic race and low household income. CONCLUSIONS: Markers of low socioeconomic status, including insurance status, race, and household income, are associated with an increased odds of readmission after cardiac valve surgery. Such findings may point to inequalities in health care; additional investigation is necessary to understand the causal link.

The effect of obstructive sleep apnea on readmissions and atrial fibrillation after cardiac surgery.

STUDY OBJECTIVE: To understand the effect of obstructive sleep apnea on readmission rates and post-operative atrial fibrillation in the cardiac surgical population. DESIGN: Retrospective cohort study. SETTING: Administrative database consisting of 2007-2014 data from California, Florida, New York, Kentucky, and Maryland from the State Inpatient Databases, Healthcare Cost and Utilization Project. PATIENTS: A total of 506,604 patients ≥18 years old who underwent coronary artery bypass grafting surgery (CABG) and/or valve surgery were included in the study. After excluding for death during the index hospitalization and missing data, 396,657 patients remained for 30-day readmission analysis. INTERVENTIONS: None. MEASUREMENTS: Primary outcomes were unadjusted rates and adjusted odds of 30-day readmission. Secondary outcomes included post-operative atrial fibrillation and readmission diagnoses. Bivariate associations were assessed between OSA status, covariates and potential confounders, and outcomes. Odds ratios (OR) with 95% confidence intervals (CI) were estimated. Statistical significance was assessed at p < 0.05. MAIN RESULTS: The overall 30-day readmission rate was 17.2%, with a rate of 19.6% vs. 17.1% in the OSA vs. non-OSA group (p < 0.001). Patients with OSA had higher odds of 30-day readmission (OR = 1.08, 95% CI 1.06-1.11) and higher odds of developing post-operative atrial fibrillation (OR = 1.04, 95% CI 1.01-1.08) compared to non-OSA patients. The most common reason for readmission was atrial fibrillation (38.6%), with OSA patients presenting with atrial fibrillation more frequently than their counterparts (41.7% vs. 38.4%, p < 0.001). CONCLUSIONS: Patients with OSA are at increased risk of 30-day readmission and post-operative atrial fibrillation following cardiac surgery compared to those without OSA. Although the importance of OSA is increasingly recognized, it remains a significant risk factor for post-operative readmissions and morbidity. Further research is needed to optimize perioperative management of patients with OSA, but these results highlight the importance of this disease on patient outcomes and healthcare costs.

Coronary artery bypass graft readmission rates and risk factors - A retrospective cohort study.

BACKGROUND: Hospital readmissions contribute substantially to the overall healthcare cost. Coronary artery bypass graft (CABG) is of particular interest due to its relatively high short-term readmission rates and mean hospital charges. METHODS: A retrospective review was performed on 2007-2011 data from California, Florida, and New York from the State Inpatient Databases, Healthcare Cost and Utilization Project. All patients ≥18 years of age who underwent isolated CABG and met inclusion/exclusion criteria were included. Insurance status was categorized by Medicaid, Medicare, Private Insurance, Uninsured, and Other. Primary outcomes were unadjusted rates and adjusted odds of readmission at 30- and 90-days. Secondary outcomes included diagnosis at readmission. RESULTS: A total of 177,229 were included in the analyses after assessing for exclusion criteria. Overall 30-day readmission rate was 16.1%; rates were highest within Medicare (18.4%) and Medicaid (20.2%) groups and lowest in the private insurance group (11.7%; p < 0.0001). Similarly, 90-day rates were highest in Medicare (27.3%) and Medicaid (29.8%) groups and lowest in the private insurance group (17.6%), with an overall 90-day rate of 24.0% (p < 0.0001). The most common 30-day readmission diagnoses were atrial fibrillation (26.7%), pleural effusion (22.5%), and wound infection (17.7%). Medicare patients had the highest proportion of readmissions with atrial fibrillation (31.7%) and pleural effusions (23.3%), while Medicaid patients had the highest proportion of readmissions with wound infections (21.8%). Similar results were found at 90 days. Risk factors for readmission included non-private insurance, age, female sex, non-white race, low median household income, non-routine discharge, length of stay, and certain comorbidities and complications. CONCLUSIONS: CABG readmission rates remain high and are associated with insurance status and racial and socioeconomic markers. Further investigation is necessary to better delineate the underlying factors that relate racial and socioeconomic disparities to CABG readmissions. Understanding these factors will be key to improving healthcare outcomes and expenditure.