Data mining model for ambulance run forecast

Chih-Hsien Chi, Y. S. Tzeng, Xi-Zhang Lin, T. S. Chen, Liang-Miin Tsai

Research output: Contribution to journalArticle

Abstract

Objective: The purpose of this study was to evaluate a forecast model to predict ambulance run and ambulance non-transport. Metorials and Methods: The model was set up by using a Back-Propagation Network for ambulance mission prediction. Input variables included month, holidays, time of ambulance call, result of ambulance call, temperature, and humidity. Output results included ambulance run and non-transport. Data from the Tainan City dispatch center from 1996 and 1997 were used for setting up the model. Data from 1998 was used to test the model. Results: The averages mean prediction error was between [-6.1, 6.1] percent. A larger error was noted during January and February (spring vacation period in Taiwan). Conclusion: The data mining model could provide forecasts of future ambulance service run volume and non-transport. With the development of medical informatics, using a predicting model for planning medical demand is feasible. Further evaluation and application are warranted for cost-effective medical resource management.

Original languageEnglish
Pages (from-to)337-341
Number of pages5
JournalTzu Chi Medical Journal
Volume11
Issue number4
Publication statusPublished - 1999 Dec 1

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Ambulances
Data Mining
Medical Informatics
Holidays
Humidity
Taiwan
Costs and Cost Analysis
Temperature

All Science Journal Classification (ASJC) codes

  • Medicine(all)

Cite this

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Data mining model for ambulance run forecast. / Chi, Chih-Hsien; Tzeng, Y. S.; Lin, Xi-Zhang; Chen, T. S.; Tsai, Liang-Miin.

In: Tzu Chi Medical Journal, Vol. 11, No. 4, 01.12.1999, p. 337-341.

Research output: Contribution to journalArticle

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AU - Chi, Chih-Hsien

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