Investigating patients’ visits to emergency departments: A behavior-based icd-9-cm codes decision tree induction approach

Yen Yi Feng, I. Chin Wu, Yu Ping Ho

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

Abstract

Increasing healthcare costs have motivated researchers to seek ways to more efficiently use medical resources. The aim of our study was to adopt the explanatory data-mining approach to identify characteristics of emergency department (ED) visits for ED management. To that end, we adopted a behavior-based decision tree (DT) induction method that considers medical diagnoses and individual patients’ information, i.e., 11 input variables, in order to analyze characteristics of patients’ visits to EDs and predict the length of the stays. We interpreted the results based on the communicability and consistency of the DT, represented as a behavior-based DT profile in order to increase its explanatory power. Among the major preliminary findings, the DT with International Classification of Diseases diagnosis codes achieved better clinical values for explaining the characteristics of patients’ visits. Our results can serve as a reference for ED personnel to examine overcrowding conditions as part of medical management.

Original languageEnglish
Title of host publicationHCI in Business, Government and Organizations - 7th International Conference, HCIBGO 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Proceedings
EditorsFiona Fui-Hoon Nah, Keng Siau
PublisherSpringer
Pages34-45
Number of pages12
ISBN (Print)9783030503406
DOIs
Publication statusPublished - 2020
Externally publishedYes
Event7th International Conference on HCI in Business, Government, and Organizations, HCIBGO 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020 - Copenhagen, Denmark
Duration: 2020 Jul 192020 Jul 24

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12204 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Conference on HCI in Business, Government, and Organizations, HCIBGO 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020
CountryDenmark
CityCopenhagen
Period20/7/1920/7/24

Keywords

  • Behavior-based profile
  • Decision tree
  • Emergency department
  • International Classification of Diseases diagnosis codes

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Feng, Y. Y., Wu, I. C., & Ho, Y. P. (2020). Investigating patients’ visits to emergency departments: A behavior-based icd-9-cm codes decision tree induction approach. In F. F-H. Nah, & K. Siau (Eds.), HCI in Business, Government and Organizations - 7th International Conference, HCIBGO 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Proceedings (pp. 34-45). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12204 LNCS). Springer. https://doi.org/10.1007/978-3-030-50341-3_3