David M Jacobs1, Katia Noyes2, Jiwei Zhao3, Walter Gibson1, Timothy F Murphy4, Sanjay Sethi4, Heather M Ochs-Balcom2. 1. 1 Department of Pharmacy Practice, School of Pharmacy and Pharmaceutical Sciences. 2. 2 Department of Epidemiology and Environmental Health, School of Public Health and Health Professions. 3. 3 Department of Biostatistics, School of Public Health and Health Professions, and. 4. 4 Department of Medicine, Clinical and Translational Research Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, New York.
Abstract
RATIONALE: Understanding the causes and factors related to readmission for an acute exacerbation of chronic obstructive pulmonary disease (AECOPD) within a nationwide database including all payers and ages can provide valuable input for the development of generalizable readmission reduction strategies. OBJECTIVES: To determine the rates, causes, and predictors for early (3-, 7-, and 30-d) readmission in patients hospitalized with AECOPD in the United States using the Nationwide Readmission Database after the initiation of the Hospital Readmissions Reduction Program, but before its expansion to COPD. METHODS: We conducted an analysis of the Nationwide Readmission Database from 2013 to 2014. Index admissions and readmissions for an AECOPD were defined consistent with Hospital Readmissions Reduction Program guidelines. We investigated the percentage of 30-day readmissions occurring each day after discharge and the most common readmission diagnoses at different time periods after hospitalization. The relationship between predictors (categorized as patient, clinical, and hospital factors) and early readmission were evaluated using a hierarchical two-level logistic model. To examine covariate effects on early-day readmission, predictors for 3-, 7-, and 30-day readmissions were modeled separately. RESULTS: There were 202,300 30-day readmissions after 1,055,830 index AECOPD admissions, a rate of 19.2%. The highest readmission rates (4.2-5.5%) were within the first 72 hours of discharge, and 58% of readmissions were within the first 15 days. Respiratory-based diseases were the most common reasons for readmission (52.4%), and COPD was the most common diagnosis (28.4%). Readmission diagnoses were similar at different time periods after discharge. Early readmission was associated with patient (Medicaid payer status, lower household income, and higher comorbidity burden) and clinical factors (longer length of stay and discharge to a skilled nursing facility). Predictors did not vary substantially by time of readmission after discharge within the 30-day window. CONCLUSIONS: Thirty-day readmissions after an AECOPD remain a major healthcare burden, and are characterized by a similar spectrum of readmission diagnoses. Predictors associated with readmission include both patient and clinical factors. Development of a COPD-specific risk stratification algorithm based on these factors may be necessary to better predict patients with AECOPD at high risk of early readmission.
RATIONALE: Understanding the causes and factors related to readmission for an acute exacerbation of chronic obstructive pulmonary disease (AECOPD) within a nationwide database including all payers and ages can provide valuable input for the development of generalizable readmission reduction strategies. OBJECTIVES: To determine the rates, causes, and predictors for early (3-, 7-, and 30-d) readmission in patients hospitalized with AECOPD in the United States using the Nationwide Readmission Database after the initiation of the Hospital Readmissions Reduction Program, but before its expansion to COPD. METHODS: We conducted an analysis of the Nationwide Readmission Database from 2013 to 2014. Index admissions and readmissions for an AECOPD were defined consistent with Hospital Readmissions Reduction Program guidelines. We investigated the percentage of 30-day readmissions occurring each day after discharge and the most common readmission diagnoses at different time periods after hospitalization. The relationship between predictors (categorized as patient, clinical, and hospital factors) and early readmission were evaluated using a hierarchical two-level logistic model. To examine covariate effects on early-day readmission, predictors for 3-, 7-, and 30-day readmissions were modeled separately. RESULTS: There were 202,300 30-day readmissions after 1,055,830 index AECOPD admissions, a rate of 19.2%. The highest readmission rates (4.2-5.5%) were within the first 72 hours of discharge, and 58% of readmissions were within the first 15 days. Respiratory-based diseases were the most common reasons for readmission (52.4%), and COPD was the most common diagnosis (28.4%). Readmission diagnoses were similar at different time periods after discharge. Early readmission was associated with patient (Medicaid payer status, lower household income, and higher comorbidity burden) and clinical factors (longer length of stay and discharge to a skilled nursing facility). Predictors did not vary substantially by time of readmission after discharge within the 30-day window. CONCLUSIONS: Thirty-day readmissions after an AECOPD remain a major healthcare burden, and are characterized by a similar spectrum of readmission diagnoses. Predictors associated with readmission include both patient and clinical factors. Development of a COPD-specific risk stratification algorithm based on these factors may be necessary to better predict patients with AECOPD at high risk of early readmission.
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