Publication: A drug cost model for injuries due to road traffic accidents
Issued Date
2008-01-01
Resource Type
ISSN
18863655
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2-s2.0-42549086750
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Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
Pharmacy Practice. Vol.6, No.1 (2008), 9-14
Suggested Citation
Arthorn Riewpaiboon, Piyanuch Piyauthakit, Witsanuchai Srijariya, Usa Chaikledkaew A drug cost model for injuries due to road traffic accidents. Pharmacy Practice. Vol.6, No.1 (2008), 9-14. doi:10.4321/S1886-36552008000100002 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/19246
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Title
A drug cost model for injuries due to road traffic accidents
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Abstract
Objective: This study aimed to develop a drug cost model for injuries due to road traffic accidents for patients receiving treatment at a regional hospital in Thailand. Methods: The study was designed as a retrospective, descriptive analysis. The cases were all from road iiaiic accidents receiving treatment at a public regional hospital in the fiscal year 2004. Results: Three thousand seven hundred and twenty-three road accident patients were included in the study. The mean drug cost per case was USD 18.20 (SD)=73.49, median=2.36). The fitted drug cost model had an adjusted R2of 0.449. The positive significant predictor variables of drug costs were prolonged length of stay, age over 30 years old, male, Universal Health Coverage Scheme, time of accident during 18:00-24:00 o'clock, and motorcycle comparing to bus. To forecast the drug budget for 2006, there were two approaches identified, the mean drug cost and the predicted average drug cost. The predicted average drug cost was calculated based on the forecasted values of statistically significant (p<0.05) predictor variables. included in the fitted model; predicted total drug cost was USD44,334. Alternatively, based on the mean cost, predicted total drug cost in 2006 was USD63,408. This was 43% higher than the figure based on the predicted cost approach. Conclusions: The planned budget of drug cost based on the mean cost and predicted average cost were meaningfully different. The application of a predicted average cost model could result in a more accurate budget planning than that of a mean statistic approach.