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Article
Reliability of Predicting Early Hospital Readmission After Discharge for an Acute Coronary Syndrome Using Claims-Based Data
UMass Center for Clinical and Translational Science Supported Publications
  • David D. McManus, University of Massachusetts Medical School
  • Jane S. Saczynski, University of Massachusetts Medical School
  • Darleen M. Lessard, University of Massachusetts Medical School
  • Molly E. Waring, University of Massachusetts Medical School
  • Jeroan J. Allison, University of Massachusetts Medical School
  • David C. Parish, University of Massachusetts Medical School
  • Robert J. Goldberg, University of Massachusetts Medical School
  • Arlene S. Ash, University of Massachusetts Medical School
  • Catarina I. Kiefe, University of Massachusetts Medical School
UMMS Affiliation
Department of Quantitative Health Sciences; Department of Medicine, Division of Cardiovascular Medicine; Meyers Primary Care Institute
Date
2-15-2016
Document Type
Article
Abstract
Early rehospitalization after discharge for an acute coronary syndrome, including acute myocardial infarction (AMI), is generally considered undesirable. The Centers for Medicare and Medicaid Services (CMS) base hospital financial incentives on risk-adjusted readmission rates after AMI, using claims data in its adjustment models. Little is known about the contribution to readmission risk of factors not captured by claims. For 804 consecutive patients > 65 years discharged in 2011 to 2013 from 6 hospitals in Massachusetts and Georgia after an acute coronary syndrome, we compared a CMS-like readmission prediction model with an enhanced model incorporating additional clinical, psychosocial, and sociodemographic characteristics, after principal components analysis. Mean age was 73 years, 38% were women, 25% college educated, and 32% had a previous AMI; all-cause rehospitalization occurred within 30 days for 13%. In the enhanced model, previous coronary intervention (odds ratio [OR] = 2.05, 95% confidence interval [CI] 1.34 to 3.16; chronic kidney disease OR 1.89, 95% CI 1.15 to 3.10; low health literacy OR 1.75, 95% CI 1.14 to 2.69), lower serum sodium levels, and current nonsmoker status were positively associated with readmission. The discriminative ability of the enhanced versus the claims-based model was higher without evidence of overfitting. For example, for patients in the highest deciles of readmission likelihood, observed readmissions occurred in 24% for the claims-based model and 33% for the enhanced model. In conclusion, readmission may be influenced by measurable factors not in CMS' claims-based models and not controllable by hospitals. Incorporating additional factors into risk-adjusted readmission models may improve their accuracy and validity for use as indicators of hospital quality.
Rights and Permissions
Citation: Am J Cardiol. 2016 Feb 15;117(4):501-7. doi: 10.1016/j.amjcard.2015.11.034. Epub 2015 Dec 2. Link to article on publisher's site
Related Resources
Link to Article in PubMed
Keywords
  • UMCCTS funding
PubMed ID
26718235
Citation Information
David D. McManus, Jane S. Saczynski, Darleen M. Lessard, Molly E. Waring, et al.. "Reliability of Predicting Early Hospital Readmission After Discharge for an Acute Coronary Syndrome Using Claims-Based Data" Vol. 117 Iss. 4 (2016) ISSN: 0002-9149 (Linking)
Available at: http://works.bepress.com/catarina_kiefe/246/