Data mining model for ambulance run forecast

C. H. Chi, Y. S. Tzeng, X. Z. Lin, T. S. Chen, L. M. Tsai

Research output: Contribution to journalArticlepeer-review


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
Issue number4
Publication statusPublished - 1999 Dec 1

All Science Journal Classification (ASJC) codes

  • Medicine(all)


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