Potentially avoidable 30-day hospital readmissions in medical patients: derivation and validation of a prediction model

Donzé, Jacques; Aujesky, Drahomir; Williams, Deborah; Schnipper, Jeffrey L. (2013). Potentially avoidable 30-day hospital readmissions in medical patients: derivation and validation of a prediction model. JAMA Internal Medicine, 173(8), pp. 632-638. American Medical Association 10.1001/jamainternmed.2013.3023

Text ioi120113_632_638.pdf - Published Version Restricted to registered users only Available under License Publisher holds Copyright. Download (193kB)

IMPORTANCE

Because effective interventions to reduce hospital readmissions are often expensive to implement, a score to predict potentially avoidable readmissions may help target the patients most likely to benefit.

OBJECTIVE

To derive and internally validate a prediction model for potentially avoidable 30-day hospital readmissions in medical patients using administrative and clinical data readily available prior to discharge.

DESIGN

Retrospective cohort study.

SETTING

Academic medical center in Boston, Massachusetts.

PARTICIPANTS

All patient discharges from any medical services between July 1, 2009, and June 30, 2010.

MAIN OUTCOME MEASURES

Potentially avoidable 30-day readmissions to 3 hospitals of the Partners HealthCare network were identified using a validated computerized algorithm based on administrative data (SQLape). A simple score was developed using multivariable logistic regression, with two-thirds of the sample randomly selected as the derivation cohort and one-third as the validation cohort.

RESULTS

Among 10 731 eligible discharges, 2398 discharges (22.3%) were followed by a 30-day readmission, of which 879 (8.5% of all discharges) were identified as potentially avoidable. The prediction score identified 7 independent factors, referred to as the HOSPITAL score: h emoglobin at discharge, discharge from an o ncology service, s odium level at discharge, p rocedure during the index admission, i ndex t ype of admission, number of a dmissions during the last 12 months, and l ength of stay. In the validation set, 26.7% of the patients were classified as high risk, with an estimated potentially avoidable readmission risk of 18.0% (observed, 18.2%). The HOSPITAL score had fair discriminatory power (C statistic, 0.71) and had good calibration.

CONCLUSIONS AND RELEVANCE

This simple prediction model identifies before discharge the risk of potentially avoidable 30-day readmission in medical patients. This score has potential to easily identify patients who may need more intensive transitional care interventions.

Interest & Impact

Downloads

2 since deposited on 01 Apr 2014
0 in the past 12 months

Citations

5 Citations in Web of Science ®
6 Citations in Scopus

Search

in Google Scholar™

Services

Actions (login required)

Edit item

Actions (login required)

Edit item