1. Predicting Length of Stay among Patients Discharged from the Emergency Department-Using an Accelerated Failure Time Model
- Author
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Shu-Hui Chang, Te Fa Chiu, Hsiu Hsi Chen, Shin-Liang Pan, Chung-Hsien Chaou, Petrus Tang, and Amy Ming Fang Yen
- Subjects
Male ,Multivariate analysis ,Critical Care and Emergency Medicine ,Medical Doctors ,Health Care Providers ,lcsh:Medicine ,Nurses ,Accelerated failure time model ,Pediatrics ,Electrocardiography ,0302 clinical medicine ,Interquartile range ,Medicine and Health Sciences ,030212 general & internal medicine ,Young adult ,lcsh:Science ,Aged, 80 and over ,Multidisciplinary ,Middle Aged ,Patient Discharge ,Hospitals ,Professions ,Bioassays and Physiological Analysis ,Research Design ,Electronic data ,Female ,Medical emergency ,Emergency Service, Hospital ,Research Article ,Adult ,medicine.medical_specialty ,Census ,Laboratory Tests ,Research and Analysis Methods ,03 medical and health sciences ,Young Adult ,Internal medicine ,Physicians ,medicine ,Humans ,Aged ,Retrospective Studies ,Survey Research ,business.industry ,lcsh:R ,Electrophysiological Techniques ,030208 emergency & critical care medicine ,Retrospective cohort study ,Emergency department ,Length of Stay ,medicine.disease ,Triage ,Health Care ,Health Care Facilities ,Models, Organizational ,People and Places ,lcsh:Q ,Population Groupings ,Cardiac Electrophysiology ,business - 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
- Published
- 2016