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Health Innovation Program, the University of Wisconsin School of Medicine and Public Health from The Wisconsin Partnership Program, and the Community–Academic Partnerships core of the University of Wisconsin Institute for Clinical and Translational Research through National Center for Advancing Translational Sciences, Geriatric Research, Education and Clinical Center of the William S. Middleton Memorial Veterans Affairs Hospital, American Federation for Aging Research Hartford Center of Excellence National Center of Excellence Award, University of Wisconsin Hospitals and Clinics; National Institute on Aging Beeson Career Development Award, National Institute on Aging Award, National Institute on Minority Health and Health Disparities Research Award, and the Madison Veterans Affairs Geriatrics Research, Education and Clinical Center, University of Wisconsin School of Medicine and Public Health from the Wisconsin Partnership Program, AcademyHealth New Investigator and the National Institutes of Health Loan Repayment Program.
BACKGROUND: To determine the extent of agreement between four commonly used definitions of multiple chronic conditions (MCCs) and compare each definition’s ability to predict 30-day hospital readmissions.
METHODS: This retrospective cohort study used Medicare claims data from 2004 to 2009 from a 5% random sample of Medicare beneficiaries in the Chronic Condition Data Warehouse.The Medicare provider of service file was used to obtain hospital characteristics. Medicare fee-for-service beneficiaries aged 65 and older who were discharged from the hospital between January 1, 2005, and December 1, 2009; were enrolled in Medicare Part A and Part B for 12 months before the date of admission and for 12 months after the date of discharge unless they died during the postdischarge period; and experienced at least one inpatient or two outpatient (evaluation and management visit or emergency department visit) encounters in the 12 months before the index admission to ensure an adequate number of claims from which to obtain diagnostic codes during the baseline year were focused on. Beneficiaries who died in the hospital or left against medical advice during their index admission were excluded, consistent with Medicare’s readmission metric approach. The University of Wisconsin-Madison Institutional Review Board determined that this study did not meet criteria for human subjects research.
RESULTS: The sample prevalence of hospitalized Medicare beneficiaries with two or more chronic conditions ranged from 18.6% (Johns Hopkins Adjusted Clinical Groups (ACG) Case-Mix System software) to 92.9% (Medicare Chronic Condition Warehouse (CCW)). There was slight to moderate agreement (kappa = 0.03-0.44) between pair-wise combinations of MCC definitions. CCW-defined MCC was the most sensitive (sensitivity 95.4%, specificity 7.4%), and ACG-defined MCC was the most specific (sensitivity 32.7%, specificity 83.2%) predictor of being readmitted. In the fully adjusted model, the risk of readmission was higher for those with chronic condition Special Needs Plan (c-SNP)-defined MCCs (odds ratio (OR) = 1.50, 95% confidence interval (CI) = 1.47-1.52), Charlson Comorbidity Index-defined MCCs (OR = 1.45, 95% CI = 1.42-1.47), ACG-defined MCCs (OR = 1.22, 95% CI = 1.19-1.25), and CCW-defined MCCs (OR = 1.15, 95% CI = 1.11-1.19) than for those without MCCs.
DISCUSSION: Comparing four commonly used definitions of MCCs in the same population of Medicare beneficiaries demonstrated fair to poor agreement in classifying individuals as having or not having MCCs. Although low agreement was expected, the hypothesis that the definitions including the greatest number of possible chronic conditions would be the most-sensitive but least-specific predictors of 30-day hospital readmission was incorrect. CCW-defined MCCs (≥2/21 conditions) were the most sensitive and ACG defined MCCs (≥2/119 EDCs) were the most specific.
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