Predicting the Risk of Readmission in Pneumonia: A Systematic Review of Model Performance.

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Predicting the Risk of Readmission in Pneumonia: A Systematic Review of Model Performance.

Ann Am Thorac Soc. 2016 Jun 14;

Authors: Weinreich M, Nguyen OK, Wang D, Mayo H, Mortensen EM, Halm EA, Makam AN

BACKGROUND: Predicting which patients are at highest risk for readmission after hospitalization for pneumonia could enable hospitals to proactively reallocate scarce resources to reduce 30- day readmissions.
OBJECTIVE: To synthesize the available literature readmission risk prediction models for adults who are hospitalized because of pneumonia and describe their performance.
DATA SOURCES: We systematically searched Ovid MEDLINE, Embase, The Cochrane Library, and CINAHL databases from inception through July 2015. We included studies of adults discharged with pneumonia that developed or validated a model that predicted hospital readmission.
DATA EXTRACTION: Two independent reviewers abstracted data and assessed the risk of bias.
SYNTHESIS: Of 992 citations reviewed, 7 studies, all performed in the United States, met inclusion criteria, which included 11 unique risk prediction models. All-cause 30-day readmission rates ranged from 11.8%-20.8% (median: 17.3%). Model discrimination (c-statistic) ranged from 0.59 -0.77 (median 0.63) and the highest quality, best-validated model, the Centers for Medicare and Medicaid Services Pneumonia Administrative Model, performed model was described in a single-site study that lacked internal validation. The models had adequate calibration with patients predicted as high risk for readmission, having a higher average observed readmission rate compared to those predicted to be low risk. None of the studies included pneumonia illness severity scores, and only one included measures of inhospital clinical trajectory and stability on discharge, robust predictors of readmission.
CONCLUSIONS: We found a limited number of validated pneumonia-specific readmission models and their predictive ability was modest. To improve predictive accuracy, future models should include measures of pneumonia illness severity, hospital complications, and stability on discharge.

PMID: 27299853 [PubMed - as supplied by publisher]

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