On Analyzing Readmissions Using A Trajectory Model: Evidence from Israel

Ofir Ben-Assuli, Rema Padman, Martha Bowman, Moshe Leshno, Itamar Shabtai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations


The problem of readmission, wherein patients are readmitted for the same or a related condition shortly after discharge, has become a challenge worldwide from care quality and financial perspectives. In this study, we explore 30-day readmission data for predicting who is likely to be readmitted and understanding key factors contributing to preventable readmissions using the developmental trajectory of creatinine level as a key laboratory marker of serious illness and a potential predictor of future readmission. Using Electronic Health Record data on 928 patients over ten different visits to emergency departments across Israel, we apply a semi-parametric, statistical, group-based trajectory model to elicit three distinct creatinine-based trajectories over time with differing 30-day readmission rates for males and females. Analysis of readmission risk stratification of the patient population using other relevant factors is ongoing research.

Original languageEnglish
Title of host publicationMEDINFO 2015
Subtitle of host publicationeHealth-Enabled Health - Proceedings of the 15th World Congress on Health and Biomedical Informatics
EditorsAndrew Georgiou, Indra Neil Sarkar, Paulo Mazzoncini de Azevedo Marques
PublisherIOS Press
Number of pages1
ISBN (Electronic)9781614995630
StatePublished - 2015
Event15th World Congress on Health and Biomedical Informatics, MEDINFO 2015 - Sao Paulo, Brazil
Duration: 19 Aug 201523 Aug 2015

Publication series

NameStudies in Health Technology and Informatics
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365


Conference15th World Congress on Health and Biomedical Informatics, MEDINFO 2015
CitySao Paulo


  • Creatinine Level
  • Electronic Health Record
  • Group-Based Trajectory Model
  • Readmission Prediction


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