建立健保藥費支出之預估方法研究

Accurately Predicting Drug Expenditures

董鈺琪(Yui-Chi Tung) ； 張順全(Shuan-Chuan Chang) ； 林恆慶(Herng-Ching Lin)

《醫護科技學刊》 4卷2期 (2002/04) Pp. 161-177

https://doi.org/10.6563/TJHS.2002.4(2).5

摘要

目標：本研究旨在建構計量模式，除預估八十九年每月藥費(並細分成門住診)，以利監測藥費之成長趨勢，並分析以往相關政策推行，對藥費成長是否有顯著影響，以評估管理措施的成效，供研擬未來對策的參考。方法：主要採用三種預測模型：複迴歸橫型(multiple regression model)、自我迴歸整合移動平均模型(auto-regressive integrated moving average model, ARIMA)及時點介入模型(ARIMA- intervention model)，以85年1月至88年9月共45個月之健保按月藥費資料，預估未來每月藥費支出。結果：以絕對誤差百分比之平均(mean absolute percent error, MAPE)比較發現，最小為時點介入模型介於1.79%至2.14%之間，預估89年全年總藥費的889.03億元(成長率約10.73%)，另顯著影響藥費成長有關的因素包括藥價調整、審查上軌道等介入。結論：本研究之預估模型係根據過去的藥費成長趨勢及介入措施所預估，發現89年的成長率仍高於預期值，因此，尚需更多的節制藥費措施(如縮小藥價差的各項措施)，來抑制藥費的高成長。

關鍵字

複迴歸模型 ； ARIMA模型 ； 時點介入模型

並列摘要

This study aims to develop a method for predicting monthly drug expenditures, and uses the prediction of monthly drug expenditures in 2000 as an example. Such a method could not only help the Bureau of National Health Insurance (BNHI) to monitor future trends in drug expenditures, but can also help BNHI evaluate the potential impact of certain policies on drug expenditures. Three forecasting models were performed in this study as follows: multiple regression analysis, the auto-regressive integrated moving average model (ARlMA), and the ARIMA- intervention model. This study used monthly drug expenditure data collected by BNHI from 1/1996 to 9/1999. Implementing the three models revealed that the mean absolute percent error (MAPE) of the ARIMA-intervention model is smallest, being between 1.79% and 2.14%. Meanwhile, total drug expenditure for 2000 was predicted as $88.9 billion (growth of around 10.73%). The factors of drug fee adjustment, and initiation of review are significantly related to the growth of drug expenditure. This study found that total drug expenditure was higher than expected in 2000, and thus BNHI needs to control drug expenditure more effectively.

並列關鍵字

multiple regression analysis ； auto-regressive integrated moving average model ； ARIMA- intervention model

參考文獻

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