運用類神經網路預測門診醫師人力之分析研究

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Title:	運用類神經網路預測門診醫師人力之分析研究 A study for estimating then Ambulatory Physician Manpower using Artificial Neural Network Analysis
Authors:	陳僅璇 Chin-Hsuan Chen
Contributors:	徐宏修嘉南藥理科技大學：醫療資訊管理研究所
Keywords:	資料探勘醫師人力生產力 productivity Data Mining doctor manpower
Date:	2006
Issue Date:	2010-06-01 09:21:32 (UTC+8)
Abstract:	經濟富裕、科技發達、醫療品質提高，讓人口結構已改變，台灣己走向老人化國家，整體醫療服務產業，從原本的疾病治療為目的，至今己是以健康預防為醫療服務為主要目標項目。當前台灣醫療環境裡，受到全民健康保險政策影響性很大，首當其衝受到影響的是醫師人力，因不斷變化的全民健康保險給付政策裡，誘發醫師做有選擇特定的醫療服務之科別與項目，使得各診療科別之醫師人力分佈不均；再者全民健康保險政策的變化也使得各醫療院所之經營管理策略上要不斷的更新調整，以達到永續經營之目的。本研究主要目的是利用資料探勘技術以類神經網路之方法來預測醫師人數成長率，並且檢定預測與實際之醫師人數成長率之差異。研究結果顯示生育率逐年下降及老年化的上升，也使得醫療服務量在0-4歲、75-90歲的比率也跟隨變化。藉由統計軟體分析醫療服務量及醫療費用之成長率是否會影響醫師人數之成長，得到結果為醫療服務量、醫療費用及醫師人數有顯著性差異較之診療科別皆為次專科。運用SPSS資料探勘軟體以各醫療層級的醫療服務量、醫療費用之成長率來預測醫師人數成長率，預測之準確度高達98%以上，最後建立的預測醫師人數成長率模式只有醫學中心的牙科、放射診斷科、放射腫瘤科等科別。 Wealthy economy, developed science and technology, enhance medical quality enhances, causes the population structure to change. Taiwan starts to move towards the agedness person country, the overall medical service industry, from the goal of originally disease treatment , until the goal of taking the health prevention as the main medical service. In the current Taiwan medical service environment, the people health insurance policy has a important influence in medical service, bears the brunt is the doctor manpower, because unceasingly changes all the people health insurance pays in the policy, induces doctor to select special medical service subject, causes respectively the doctor manpower is unevenness distribution in diagnose subject. Furthermore all the people health insurance policy change also causes management strategy in various healing institutes to want the unceasing renewal adjustment, achieved the goal of sustainability management. This research main goal is estimate the growth rate of doctor population using by the kind nerve network technology of Data Mining, and examination estimation and actual the growth rate of doctors. The result for the population structure showed the fertility rate drops and the old agedness rise year by year, also causes the medical service quantity in 0-4 year old and 75-90 year-old ratio analyzes changes. By statistical software analyzes medical service quantity and the medical income whether can affect the growth rate of doctors. Obtain the medical service quantity, the medical income and the growth rate of doctors has evident difference in sub-specialty. Uses the Data Mining software of SPSS the average growth rate calculates doctor based on the medical service quantity and the medical expense the population rate of increment, estimated the accuracy arrives above 98%, Finally establishes doctor the population growth rate only to have the Medical center the dentistry, radio diagnosis, the emission tumor branch and so on.
Relation:	校內外均一年後公開
Appears in Collections:	[Dept. of Hospital and Health (including master's program)] Dissertations and Theses

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