Development and Validation of a Prediction Model for the Number of Patients Visiting Emergency Departments.
- Author:
Jeong Eun KIM
1
;
Sang Do SHIN
;
Chang Bae PARK
;
Kang Hyun LEE
;
Sang Chul KIM
Author Information
1. Department of Epidemiology and Bioinformatics, Korea University Graduate School of Public Health, Korea.
- Publication Type:Original Article
- Keywords:
Emergency medical services;
Statistical models;
Reproducibility of results;
Prediction;
Validity
- MeSH:
Chronology as Topic;
Emergencies;
Emergency Medical Services;
Holidays;
Humans;
Information Systems;
Male;
Moclobemide;
Models, Statistical;
Reproducibility of Results
- From:Journal of the Korean Society of Emergency Medicine
2010;21(5):678-686
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
PURPOSE: We aimed to develop and validate a prediction model for the number of patients visiting emergency departments. METHODS: Enrolled patients were from eleven regional emergency departments (EDs) (level-1) that inputted information on emergency patients into the National Emergency Department Information System since 2004. We developed the automated regressive integrated moving average (ARIMA)-based prediction model using a dataset covering 2005 to 2007. To validate the prediction model, we performed Bland-Altman plot analysis for a new dataset, that of 2008, calculating the agreement rate. RESULTS: The total number of enrolled patients was 1,532,294. Of these, 844,802 (55.1%) were male and mean age was 36.5. The ARIMA (1, 1, 1) (1, 1, 1) 7 was selected as the best-fit prediction model. When we tested the validity using Bland-Altman plots, the agreement rate was 96.4% (95% CI, 94.0%~98.1%). Non-agreement dates were national holidays (n=9), and the other weekdays (n=4), respectively. CONCLUSION: We developed the ARIMA-based prediction model for emergency patients at regional EDs. The model showed a very high validity.
