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Predicting Length of Stay among Patients Discharged from the Emergency Department—Using an Accelerated Failure Time Model

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  • Chung-Hsien Chaou
  • Hsiu-Hsi Chen
  • Shu-Hui Chang
  • Petrus Tang
  • Shin-Liang Pan
  • Amy Ming-Fang Yen
  • Te-Fa Chiu

Abstract

Background: Emergency department (ED) crowding continues to be an important health care issue in modern countries. Among the many crucial quality indicators for monitoring the throughput process, a patient’s length of stay (LOS) is considered the most important one since it is both the cause and the result of ED crowding. The aim of this study is to identify and quantify the influence of different patient-related or diagnostic activities-related factors on the ED LOS of discharged patients. Methods: This is a retrospective electronic data analysis. All patients who were discharged from the ED of a tertiary teaching hospital in 2013 were included. A multivariate accelerated failure time model was used to analyze the influence of the collected covariates on patient LOS. Results: A total of 106,206 patients were included for analysis with an overall medium ED LOS of 1.46 (interquartile range = 2.03) hours. Among them, 96% were discharged by a physician, 3.5% discharged against medical advice, 0.5% left without notice, and only 0.02% left without being seen by a physician. In the multivariate analysis, increased age (>80 vs

Suggested Citation

  • Chung-Hsien Chaou & Hsiu-Hsi Chen & Shu-Hui Chang & Petrus Tang & Shin-Liang Pan & Amy Ming-Fang Yen & Te-Fa Chiu, 2017. "Predicting Length of Stay among Patients Discharged from the Emergency Department—Using an Accelerated Failure Time Model," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-11, January.
    • Handle: RePEc:plo:pone00:0165756
    DOI: 10.1371/journal.pone.0165756
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