title: Predictive factors for hospitalization of nonurgent patients in the emergency department.
abstract: Nonurgent emergency department (ED) patients are a controversial issue in the era of ED overcrowding. However, a substantial number of post-ED hospitalizations were found, which prompted for investigation and strategy management. The objective of this study is to identify risk factors for predicting the subsequent hospitalization of nonurgent emergency patients. This was a retrospective study of a database of adult nontrauma ED visits in a medical center for a period of 12 months from January 2013 to December 2013. Patient triages as either Taiwan Triage and Acuity Scale (TTAS) level 4 or 5 were considered "nonurgent." Basic demographic data, primary and secondary diagnoses, clinical parameters including blood pressure, heart rate, body temperature, and chief complaint category in TTAS were analyzed to determine if correlation exists between potential predictors and hospitalization in nonurgent patients.A total of 16,499 nonurgent patients were included for study. The overall hospitalization rate was 12.47 % (2058/16,499). In the multiple logistic regression model, patients with characteristics of males (odds ratio, OR = 1.37), age more than 65 years old (OR = 1.56), arrival by ambulance (OR = 2.40), heart rate more than 100/min (OR = 1.47), fever (OR = 2.73), and presented with skin swelling/redness (OR = 4.64) were predictors for hospitalization. The area under receiver-operator calibration curve (AUROC) for the prediction model was 0.70. Nonurgent patients might still be admitted for further care especially in male, the elderly, with more secondary diagnoses, abnormal vital signs, and presented with dermatologic complaints. Using the TTAS acuity level to identify patients for diversion away from the ED is unsafe and will lead to inappropriate refusal of care for many patients requiring hospital treatment.
authors.affiliation: aEmergency Department, Chang Gung Memorial Hospital and College of Medicine, Chang Gung University, Tao-Yuan bDepartment of Health Care Administration, Oriental Institute of Technology, New Taipei City cDepartment of Medical Education, Chang Gung Memorial Hospital and College of Medicine, Chang Gung University dLaboratory for Epidemiology, Department of Health Care Management, and Healthy Aging Research Center, and Department of Urology, Chang Gung Memorial Hospital, Chang Gung University, Kwei-Shan, Tao-Yuan, Taiwan.
authors.forename: Chip-Jin
authors.initials: CJ
authors.lastname: Ng
authors.forename: Pei-Ju
authors.initials: PJ
authors.lastname: Liao
authors.forename: Yu-Che
authors.initials: YC
authors.lastname: Chang
authors.forename: Jen-Tze
authors.initials: JT
authors.lastname: Kuan
authors.forename: Jih-Chang
authors.initials: JC
authors.lastname: Chen
authors.forename: Kuang-Hung
authors.initials: KH
authors.lastname: Hsu
mesh_terms: D000368:Aged; D015331:Cohort Studies; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D005544:Forecasting; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008875:Middle Aged; D012189:Retrospective Studies; D013624:Taiwan; D014218:Triage / Q000706:statistics & numerical data*