Can targeting high-risk patients reduce readmission rates? Evidence from Israel

Efrat Shadmi, Dan Zeltzer, Tzvi Shir, Natalie Flaks-Manov, Liran Einav, Ran D. Balicer

Research output: Contribution to journalArticlepeer-review


We study a large intervention intended to reduce hospital readmission rates in Israel. Since 2012, readmission risk was calculated for patients aged 65 and older, and high-risk patients were flagged to providers upon admission and after discharge. Analyzing 171,541 admissions during 2009–2016, we find that the intervention reduced 30-day readmission rates by 5.9% among patients aged 65–70 relative to patients aged 60–64, who were not targeted by the intervention and for whom no risk-scores were calculated. The largest reduction, 12.3%, was among high-risk patients, though some of it may reflect substitution of attention away from patients with unknown high-risk at the point of care. Post-discharge follow-up encounters were significantly expedited. Estimated effects declined after incentives to reduce readmission rates were discontinued. The evidence demonstrates that informing providers about patient risk in real-time coupled with incentives to reduce readmissions can improve care continuity and reduce hospital readmissions.

Original languageEnglish
Pages (from-to)729-745
Number of pages17
JournalJournal of Applied Economics
Issue number1
StatePublished - 2020

Bibliographical note

Funding Information:
Zeltzer acknowledges funding from the Pinhas Sapir Center for Development at Tel Aviv University. We thank participants of the 2018 ASHEcon Conference and David Slusky for helpful comments and suggestions. We especially thank Michael Leshchinsky for excellent assistance in revising the manuscript.

Publisher Copyright:
© 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.


  • Healthcare
  • hospital readmissions
  • predictive modeling

ASJC Scopus subject areas

  • Economics, Econometrics and Finance (all)


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