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Circ Cardiovasc Qual Outcomes. 2013 Jul;6(4):429-35. doi: 10.1161/CIRCOUTCOMES.111.000093. Epub 2013 Jul 2.

A prediction model to identify patients at high risk for 30-day readmission after percutaneous coronary intervention.

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1
Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.

Abstract

BACKGROUND:

The Affordable Care Act creates financial incentives for hospitals to minimize readmissions shortly after discharge for several conditions, with percutaneous coronary intervention (PCI) to be a target in 2015. We aimed to develop and validate prediction models to assist clinicians and hospitals in identifying patients at highest risk for 30-day readmission after PCI.

METHODS AND RESULTS:

We identified all readmissions within 30 days of discharge after PCI in nonfederal hospitals in Massachusetts between October 1, 2005, and September 30, 2008. Within a two-thirds random sample (Developmental cohort), we developed 2 parsimonious multivariable models to predict all-cause 30-day readmission, the first incorporating only variables known before cardiac catheterization (pre-PCI model), and the second incorporating variables known at discharge (Discharge model). Models were validated within the remaining one-third sample (Validation cohort), and model discrimination and calibration were assessed. Of 36,060 PCI patients surviving to discharge, 3760 (10.4%) patients were readmitted within 30 days. Significant pre-PCI predictors of readmission included age, female sex, Medicare or State insurance, congestive heart failure, and chronic kidney disease. Post-PCI predictors of readmission included lack of β-blocker prescription at discharge, post-PCI vascular or bleeding complications, and extended length of stay. Discrimination of the pre-PCI model (C-statistic=0.68) was modestly improved by the addition of post-PCI variables in the Discharge model (C-statistic=0.69; integrated discrimination improvement, 0.009; P<0.001).

CONCLUSIONS:

These prediction models can be used to identify patients at high risk for readmission after PCI and to target high-risk patients for interventions to prevent readmission.

KEYWORDS:

outcomes research; percutaneous coronary intervention; performance measures

PMID:
23819957
DOI:
10.1161/CIRCOUTCOMES.111.000093
[Indexed for MEDLINE]
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