Using electronic health records to predict severity of condition for Congestive Heart Failure patients

Costas Sideris*, Behnam Shahbazi, Mohammad Pourhomayoun, Majid Sarrafzadeh, Nabil Alshurafa

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

We propose a novel way to design an analytics engine based exclusively on electronic health records (EHR). We focus our efforts on Congestive Heart Failure (CHF) patients, although our approach could be extended to other chronic conditions. Our goal is to construct statistical models that predict a CHF patient's length of stay and by extension the severity of his/her condition. We show that it is possible to predict length of hospital stay based on physiological data collected from the first day of hospitalization. Using 10-fold cross validation we achieve accurate predictions with a root mean square error of 3.3 days for hospital stays that are less than 15 days in duration. We also propose a clustering of patients that organizes them to risk groups according to their estimated severity of condition.

Original languageEnglish (US)
Title of host publicationUbiComp 2014 - Adjunct Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing
PublisherAssociation for Computing Machinery, Inc
Pages1187-1192
Number of pages6
ISBN (Electronic)9781450330473
DOIs
StatePublished - Jan 1 2014
Event2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2014 - Seattle, United States
Duration: Sep 13 2014Sep 17 2014

Other

Other2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2014
CountryUnited States
CitySeattle
Period9/13/149/17/14

Keywords

  • Electronic health records
  • Heart failure
  • Intervention
  • Readmission
  • Remote monitoring systems

ASJC Scopus subject areas

  • Software

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  • Cite this

    Sideris, C., Shahbazi, B., Pourhomayoun, M., Sarrafzadeh, M., & Alshurafa, N. (2014). Using electronic health records to predict severity of condition for Congestive Heart Failure patients. In UbiComp 2014 - Adjunct Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 1187-1192). Association for Computing Machinery, Inc. https://doi.org/10.1145/2638728.2638815