On Analyzing Readmissions Using A Trajectory Model: Evidence from Israel

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

doi:10.3233/978-1-61499-564-7-1063

On Analyzing Readmissions Using A Trajectory Model: Evidence from Israel

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

Coller School of Management

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

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 language	English
Title of host publication	MEDINFO 2015
Subtitle of host publication	eHealth-Enabled Health - Proceedings of the 15th World Congress on Health and Biomedical Informatics
Editors	Andrew Georgiou, Indra Neil Sarkar, Paulo Mazzoncini de Azevedo Marques
Publisher	IOS Press
Pages	1063
Number of pages	1
ISBN (Electronic)	9781614995630
DOIs	https://doi.org/10.3233/978-1-61499-564-7-1063
State	Published - 2015
Event	15th World Congress on Health and Biomedical Informatics, MEDINFO 2015 - Sao Paulo, Brazil Duration: 19 Aug 2015 → 23 Aug 2015

Publication series

Name	Studies in Health Technology and Informatics
Volume	216
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Conference

Conference	15th World Congress on Health and Biomedical Informatics, MEDINFO 2015
Country/Territory	Brazil
City	Sao Paulo
Period	19/08/15 → 23/08/15

Keywords

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

Access to Document

10.3233/978-1-61499-564-7-1063

Cite this

Ben-Assuli, O., Padman, R., Bowman, M., Leshno, M., & Shabtai, I. (2015). On Analyzing Readmissions Using A Trajectory Model: Evidence from Israel. In A. Georgiou, I. N. Sarkar, & P. M. de Azevedo Marques (Eds.), MEDINFO 2015: eHealth-Enabled Health - Proceedings of the 15th World Congress on Health and Biomedical Informatics (pp. 1063). (Studies in Health Technology and Informatics; Vol. 216). IOS Press. https://doi.org/10.3233/978-1-61499-564-7-1063

Ben-Assuli, Ofir ; Padman, Rema ; Bowman, Martha et al. / On Analyzing Readmissions Using A Trajectory Model : Evidence from Israel. MEDINFO 2015: eHealth-Enabled Health - Proceedings of the 15th World Congress on Health and Biomedical Informatics. editor / Andrew Georgiou ; Indra Neil Sarkar ; Paulo Mazzoncini de Azevedo Marques. IOS Press, 2015. pp. 1063 (Studies in Health Technology and Informatics).

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abstract = "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.",

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Ben-Assuli, O, Padman, R, Bowman, M, Leshno, M & Shabtai, I 2015, On Analyzing Readmissions Using A Trajectory Model: Evidence from Israel. in A Georgiou, IN Sarkar & PM de Azevedo Marques (eds), MEDINFO 2015: eHealth-Enabled Health - Proceedings of the 15th World Congress on Health and Biomedical Informatics. Studies in Health Technology and Informatics, vol. 216, IOS Press, pp. 1063, 15th World Congress on Health and Biomedical Informatics, MEDINFO 2015, Sao Paulo, Brazil, 19/08/15. https://doi.org/10.3233/978-1-61499-564-7-1063

On Analyzing Readmissions Using A Trajectory Model: Evidence from Israel. / Ben-Assuli, Ofir; Padman, Rema; Bowman, Martha et al.
MEDINFO 2015: eHealth-Enabled Health - Proceedings of the 15th World Congress on Health and Biomedical Informatics. ed. / Andrew Georgiou; Indra Neil Sarkar; Paulo Mazzoncini de Azevedo Marques. IOS Press, 2015. p. 1063 (Studies in Health Technology and Informatics; Vol. 216).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Ben-Assuli O, Padman R, Bowman M, Leshno M, Shabtai I. On Analyzing Readmissions Using A Trajectory Model: Evidence from Israel. In Georgiou A, Sarkar IN, de Azevedo Marques PM, editors, MEDINFO 2015: eHealth-Enabled Health - Proceedings of the 15th World Congress on Health and Biomedical Informatics. IOS Press. 2015. p. 1063. (Studies in Health Technology and Informatics). doi: 10.3233/978-1-61499-564-7-1063

On Analyzing Readmissions Using A Trajectory Model: Evidence from Israel

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