Simplification of the HOSPITAL score for predicting 30-day readmissions

Carole E. Aubert, Jeffrey L. Schnipper, Mark V. Williams, Edmondo J. Robinson, Eyal Zimlichman, Eduard E. Vasilevskis, Sunil Kripalani, Joshua P. Metlay, Tamara Wallington, Grant S. Fletcher, Andrew D. Auerbach, Drahomir Aujesky, Jacques D. Donzé

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


Objective The HOSPITAL score has been widely validated and accurately identifies high-risk patients who may mostly benefit from transition care interventions. Although this score is easy to use, it has the potential to be simplified without impacting its performance. We aimed to validate a simplified version of the HOSPITAL score for predicting patients likely to be readmitted. Design and setting Retrospective study in 9 large hospitals across 4 countries, from January through December 2011. Participants We included all consecutively discharged medical patients. We excluded patients who died before discharge or were transferred to another acute care facility. Measurements The primary outcome was any 30-day potentially avoidable readmission. We simplified the score as follows: (1) 'discharge from an oncology division' was replaced by 'cancer diagnosis or discharge from an oncology division'; (2) 'any procedure' was left out; (3) patients were categorised into two risk groups (unlikely and likely to be readmitted). The performance of the simplified HOSPITAL score was evaluated according to its overall accuracy, its discriminatory power and its calibration. Results Thirty-day potentially avoidable readmission rate was 9.7% (n=11 307/117 065 patients discharged). Median of the simplified HOSPITAL score was 3 points (IQR 2-5). Overall accuracy was very good with a Brier score of 0.08 and discriminatory power remained good with a C-statistic of 0.69 (95%CI 0.68 to 0.69). The calibration was excellent when comparing the expected with the observed risk in the two risk categories. Conclusions The simplified HOSPITAL score has good performance for predicting 30-day readmission. Prognostic accuracy was similar to the original version, while its use is even easier. This simplified score may provide a good alternative to the original score depending on the setting.

Original languageEnglish
Pages (from-to)799-805
Number of pages7
JournalBMJ Quality and Safety
Issue number10
StatePublished - Oct 2017

Bibliographical note

Funding Information:
Competing interests JDD worked as consultant at Profility, and Homeward Health, and was supported by the Swiss National Science Foundation and the Swiss Foundation for Medical-Biological Scholarships (grant no. PASMP3-142734). EZ is a consultant and advisory board member at Earlysense, which makes monitors for patients on hospital wards, a consultant and advisory board member at Hello Doctor, which develops patient record applications, a consultant to Profility, which develops big data applications for improvement of the management of elderly populations, a founder and advisory board member at ValueScope Health, which creates financial management systems for healthcare organisations, and a founder and advisory board member at Ethos, which develops mobile health applications for patient engagement. TW has been a consultant for Novartis to provide advice on screening for cardiovascular disease. JLS has received grant funding from Sanofi-Aventis for an investigator-initiated study to design and evaluate an intensive discharge and follow-up intervention in patients with diabetes.

Funding Information:
Funding Swiss National Science Foundation and the Swiss Foundation for Medical-Biological Scholarships (PASMP3-142734), Veterans Affairs Clinical Research Center of Excellence, Geriatric Research, Education, and Clinical Center (GRECC), National Institute on Aging of the National Institutes of Health (K23AG040157).

ASJC Scopus subject areas

  • Health Policy


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