| Development and Validation of a Prediction Model for the Number of Patients Visiting Emergency Departments |
| Jeong Eun Kim, Sang Do Shin, Chang Bae Park, Kang Hyun Lee, Sang Chul Kim |
1Department of Epidemiology and Bioinformatics, Korea University Graduate School of Public Health, Korea.
2Department of Emergency Medicine, Seoul National University College of Medicine, Korea. shinsangdo@medimail.co.kr
3Department of Emergency Medicine, Yonsei University Wonju College of Medicine, Korea.
4Department of Emergency Medicine, Konkook University College of Medicine, Korea.
5Laboratory for Emergency Medical Service System Design, Seoul National University Hospital Clinical Research Institute, Korea. |
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| 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. |
| Key words:
Emergency medical services, Statistical models, Reproducibility of results, Prediction, Validity |
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