Contribution of different data sources to the prediction of emergency department revisits in a safety-net population

Joshua Vest, Ofir Ben-Assuli

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

1 Scopus citations

Abstract

Electronic health records (EHR) and health information exchange (HIE), are key capabilities to address challenges facing the health care system. We aimed to understand the role that EHR and HIE data can play in reducing the probabilities of a patients' return visit to the emergency department (ED) within 30 days (i.e. a revisit). We examined the impact of four different classes of information available to health organizations. Models utilizing all data sources had the highest prediction scores. Information combined from EHRs, HIE, and area-level residential characteristics applied to Two-Class Boosted Decision Trees prediction models performed well and findings were robust. These findings show that the ability to access patients' medical history and their long term health conditions (via the HIE and EHR), including information about medications, diagnoses, recent procedures and laboratory tests is critical to forming an appropriate plan of care and eventually making more accurate admission decisions.

Original languageEnglish (US)
Title of host publicationInternational Conference on Information Systems 2018, ICIS 2018
PublisherAssociation for Information Systems
ISBN (Electronic)9780996683173
StatePublished - Jan 1 2018
Event39th International Conference on Information Systems, ICIS 2018 - San Francisco, United States
Duration: Dec 13 2018Dec 16 2018

Publication series

NameInternational Conference on Information Systems 2018, ICIS 2018

Conference

Conference39th International Conference on Information Systems, ICIS 2018
CountryUnited States
CitySan Francisco
Period12/13/1812/16/18

Keywords

  • ED ReVisits
  • Electronic health record
  • Health information exchange
  • Predictive analytics

ASJC Scopus subject areas

  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences
  • Applied Mathematics

Fingerprint Dive into the research topics of 'Contribution of different data sources to the prediction of emergency department revisits in a safety-net population'. Together they form a unique fingerprint.

  • Cite this

    Vest, J., & Ben-Assuli, O. (2018). Contribution of different data sources to the prediction of emergency department revisits in a safety-net population. In International Conference on Information Systems 2018, ICIS 2018 (International Conference on Information Systems 2018, ICIS 2018). Association for Information Systems.