T Robert Feng1, Marguerite M Hoyler2, Xiaoyue Ma3, Lisa Q Rong4, Robert S White4. 1. Department of Anesthesiology, New York-Presbyterian/Weill Cornell Medical Center, New York, NY. Electronic address: trf9013@nyp.org. 2. Department of Anesthesiology, New York-Presbyterian/Weill Cornell Medical Center, New York, NY. 3. Department of Healthcare Policy and Research, Weill Cornell Medicine, New York, NY. 4. Department of Anesthesiology, Weill Cornell Medicine, New York, NY.
Abstract
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.
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.
Authors: Kaitlyn I Zurek; Christopher L Boswell; Nathanial E Miller; Jennifer L Pecina; Matthew D Decker; Chung I Wi; Gregory M Garrison Journal: Health Serv Res Manag Epidemiol Date: 2022-06-22
Authors: Wilson M Alobuia; Tong Meng; Robin M Cisco; Dana T Lin; Insoo Suh; Manjula Kurella Tamura; Amber W Trickey; Electron Kebebew; Carolyn D Seib Journal: Surgery Date: 2021-07-03 Impact factor: 3.982