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Reliability of Predicting Early Hospital Readmission After Discharge for an Acute Coronary Syndrome Using
David D McManus1, Jane S Saczynski1, Darleen Lessard2
1Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Medicine, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Medicine, Meyers Primary Care Institute, University of Massachusetts Medical School, Worcester, Massachusetts.
Insights
Early rehospitalization after acute coronary syndrome is common. An enhanced model, including factors beyond claims data, better predicts readmission risk for patients over 65 years. This improves hospital quality assessment.
Area of Science:
- Cardiology
- Health Services Research
- Geriatrics
Background:
- Early rehospitalization after acute coronary syndrome (ACS) is a significant concern.
- Centers for Medicare and Medicaid Services (CMS) use claims data for risk-adjusted readmission models.
- Factors beyond claims data may influence readmission risk.
Purpose of the Study:
- To compare a CMS-like readmission prediction model with an enhanced model.
- To identify additional clinical, psychosocial, and sociodemographic factors impacting readmission.
- To assess the discriminative ability of the enhanced model.
Main Methods:
- Analysis of 804 patients >65 years discharged after ACS (2011-2013).
- Comparison of a claims-based model with an enhanced model including additional patient characteristics.
- Principal components analysis used for model enhancement.
Main Results:
- Enhanced model identified previous coronary intervention, chronic kidney disease, and low health literacy as significant predictors of readmission.
- Lower serum sodium levels and current nonsmoker status were also associated with higher readmission risk.
- The enhanced model demonstrated higher discriminative ability compared to the claims-based model.
Conclusions:
- Measurable factors not included in CMS claims-based models influence ACS readmission.
- Incorporating additional patient data can improve the accuracy of readmission risk models.
- Enhanced risk models may offer a more valid assessment of hospital quality.
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.
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