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題名：總額預算支付制度下醫師醫療資源最佳化分配對醫師行為之影響
作者：徐弘正
作者(外文)：Shyu, Horng-Jeng
校院名稱：亞洲大學
系所名稱：健康產業管理學系健康管理組
指導教授：藍守仁
學位類別：博士
出版日期：2013
主題關鍵詞：總額預算支付制度；醫師醫療資源；蒙地卡羅模擬；基因演算法；Global budget；Physicians' claims budget；Monte Carlo Simulation；Genetic Algorithms
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台灣全民健康保險實施論量計酬支付制度使醫療院所提供了病人極佳之醫療可近性及醫療品質；但因醫療費用不斷上漲，故實施了總額預算支付制度，其目的除節制醫療費用上漲外，也促進了醫療體系提升服務品質及增進管理效益。在健保總額預算支付制度下，醫師之健保申報額度亦即醫師之可分配醫療資源，如何有效的運用健保醫療資源管理，讓醫院能保障病患權益且同時獲取最理想之經營績效是醫院管理重大課題。醫師健保醫療資源的管理包含病患的求診量，醫療申報額度，處方藥費平均單價及處置平均單價等醫師行為指標。本研究分析總額預算支付制度下之醫師醫療資源配置議題，從醫療資源利用角度，瞭解健保額度最佳化分配後對醫師行為之影響。
本研究以醫院之健保申報額度作為醫療資源分配標的，尋求醫師健保申報額度最佳化分配所能得到之最佳經營模式。所建構之醫師醫療資源分配模式中，將考量病患看診之不確定風險因素。結合蒙地卡羅模擬與基因演算法，求取各醫師資源最佳分配額度。於健保申報額度最佳化分配後，藉由醫師行為指標廣義估計統計分析(GEE)，以瞭解醫師額度遵循情形與醫師行為指標之關係。
研究結果得知，門診申報部分顯示超出額度組醫師的病患疾病嚴重度較高，且醫學中心訓練背景之醫師較易超出額度，而低於額度組醫師達成額度狀況受季節影響，於第二季(春天)較不易達成額度，但於第四季(冬天)較易達成額度。而住院部分顯示超出額度組醫師病患疾病嚴重度較其他兩組高，且其處置平均單價四季均較其他二組高；於第三季(夏天)材料費占比亦較其他二組高，以上結果之差異均具統計學上之意義。由醫師行為指標變異數分析得知達到額度組較易控制處方平均單價，超出額度組之病人數雖少於其他兩組，但其病患疾病嚴重度較高；建議醫院在分配醫師額度之時，須考慮季節及病患疾病嚴重度。所得結論可作為醫院管理醫師時，健保額度最佳化策略之規劃基礎與輔助。醫院方面可結合醫療即時迴饋資訊系統來作為醫院與醫師之溝通平台，讓醫師自我管理最佳化分配後之醫療資源。
After the launch of Taiwan's National Health Insurance (NHI), the fee-for-service (FFS) payment system allowed hospitals to provide accessible health care. However, continually rising healthcare costs resulted in an unsustainable burden on the system. The global budget payment system (GBPS) has been implemented, which not only controlled health care costs but also motivated the hospital to enhance management efficacy. Determining how to appropriately allocate limited hospital claims resources among its physicians became an important management issue. Without proper allocation of physicians' claims resources, It could induce the unethical behaviors, such as unnecessary drug prescriptions leading to drug costs increasing and medical resources abuse. Thus, appropriate allocation of claims resources is essential to hospital revenue management. It also allows physicians to service a greater number of patients, while limiting the unnecessary waste of resources.
This study analyzed the issue of claims resources allocation under the consideration of patient needs and medical services supply of physicians. This study employed the genetic algorithms (GA)and Monte Carol simulation to tackle the uncertainty of patient volumes in the optimization process. The objects of this study was to find out the impacts of physicians' behavior affected by the optimal healthcare resources allocation under the global budget reimbursement system.
The study results of outpatient data revealed that physicians of over-budget group had character of well-trained background from center clinic. Their patient's profile had more severity nature with higher CMI. The physicians of below-budget group failed to meet budget in the spring season but better to meet budget in the winter season. The study results of inpatient data revealed over-budget physicians had higher CMI patients and higher service price of their prescription. The physicians' budget compliance of post allocation strategy revealed significant difference in seasons and physician's training background and patient's CMI nature by GEE statistic method. These conclusions could be suggested as a foundation of pre-implement planning of resources allocation strategy of hospital management. Hospitals could use historical data on claims' data as a basis for optimization, and utilize the existing health information system (HIS) as an self-regulation platform for managing budget by physicians.
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