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系統識別號 U0026-1907201317033800
論文名稱(中文) 以商業智慧方法論分析醫療專業人員職涯異動與醫事機構經營績效之研究
論文名稱(英文) A Business Intelligence Approach to the Analysis of Career Mobility of Medical Professionals and Healthcare Institutions Operating Performance
校院名稱 成功大學
系所名稱(中) 高階管理碩士在職專班(EMBA)
系所名稱(英) Executive Master of Business Administration (EMBA)
學年度 101
學期 2
出版年 102
研究生(中文) 陳憲煜
研究生(英文) Hsien-Yu Chen
學號 R07994043
學位類別 碩士
語文別 中文
論文頁數 108頁
口試委員 指導教授-李昇暾
口試委員-林清河
口試委員-耿伯文
口試委員-鄭亦君
中文關鍵字 商業智慧  醫事人員職涯異動  醫事機構  經營績效 
英文關鍵字 Business intelligence  Career mobility of medical professionals  Healthcare insititution  Operating performance 
學科別分類
中文摘要 人力資源管理是企業經營的核心能力之一,在勞力密集的醫療產業更是如此,「血汗醫院」議題點出台灣醫療產業在現今健保環境下所面臨的困境,醫師過勞,護理人員超時工作,導致醫療工作人員不堪負荷,紛紛求去,醫療業正面臨前所未有的挑戰。
國外研究指出,醫事機構內的工作人員的工作壓力越大,其滿意度會越低,相對的離職意圖會增加,而人員的流動會影響組織的財務收入,病人的滿意度及整體營運,對組織的經營產生不利的影響,然而,國內目前並沒有針對醫事人員流動率與醫事機構經營績效關聯性所做的研究。
巨量資料的時代已經來臨,企業如何藉由商業智慧分析工具將大量且複雜的數據進行切割、鑽取,並且能夠迅速產出有用及正確的資訊,提供經營管理者制定決策的依據,也是一大挑戰。全民健保資料庫為目前醫藥衛生領域研究中相當具有代表性的實證資料,我們利用「基本資料檔」中的「醫事機構基本資料檔」與「醫事人員基本資料檔」,以商業智慧概念建構一套台灣地區醫療人力資源線上分析系統,可以從不同面向探討每家機構醫事人力以及離職率的情況,並以「門診、住院費用總表」的資料計算出每家醫事機構的營收數據,分析不同屬性醫事機構間醫事人員離職率的差異,並探討醫事人員離職率與醫事機構經營績效的關係。
研究結果顯示,2007~2011年間女性執業藥師人數多於男性藥師,執業登記起始日於醫學中心的藥師平均年齡低於其他類型醫事機構,特約藥局與基層診所的家數有顯著的成長,特別是在臺北縣、臺北市及桃園縣。2010年的資料顯示,「地區醫院」、「慢性醫院」及「臺南市」的藥師離職率顯著高於其他類型醫院,「地區醫院」與「慢性醫院」的醫事人員平均流動率高於其他類型醫院,而「醫事人員年離職率」與「平均每人生產力」呈現些微的負相關,建議後續可針對醫事人員離職率較高的醫事機構深入探討原因。我們也建構了台灣地區醫事人員離職率視覺化儀表板,提供經營管理者參考。
英文摘要 Human resources management is one of the core competencies for business management, especially in a labor-intensive medical industry. This issue, "Sweat hospital", points out medical industry in Taiwan is in a dilemma under today’s health care system such as physician burnout and nurses overwork, leading these medical staffs to be overburdened due to additional workload and increase the likelihood of quitting their work in such working conditions. The medical industry is facing unprecedented challenges they have ever had.
The research showed that the greater pressure the medical staffs have in the medical institutions, the lower their satisfaction is, relatively representing that their intention to quit the job will increase. The employee turnover rate will affect the organization's income, patient satisfaction and the overall operations, resulting in negative impact on the organizational management. However, currently there is no research aimed at the correlation between the turnover rate of healthcare professionals and performance management of medical institutions.
The era of big data has come. How the enterprises slice and drill down large amounts of complex data by utilizing business intelligence analysis tools, which can quickly output useful and accurate information to assist the management in the decision making process, is also a big challenge. National Health Insurance Research Database(NHIRD) is typically the evidence-based information in the field of the current medical and health research. We use “registry for contracted medical facilities” and “registry for medical personnel” from registration files in the NHIRD to construct online analysis system of Taiwan’s medical human resources based on the concept of business intelligence. This online system can explore medical manpower and the turnover rate of employees in each medical institution from multidimensional aspects, calculate the revenue of each medical institution from monthly claim summary for inpatient claims and ambulatory care claims, analyze the difference in the turnover rate of healthcare professionals among medical institutions at different levels and further discuss the relationship between the turnover rate of healthcare professionals and performance management of medical institutions.
The results showed that between 2007 and 2011 there were more female than male licensed pharmacists in the workforce and the average age of the registered date of the pharmacists employed by medical centers was lower than by other types of medical institutions, with significant growth in the number of contracted pharmacies and primary care clinics, especially in Taipei county, Taipei city and Taoyuan county. The data in 2010 showed that the turnover rate among pharmacists in regional hospitals, chronic hospitals and Tainan city was significantly higher than that in other types of hospitals while the annual average turnover rate of healthcare professionals had a slight negative correlation with the average productivity per person. We suggested that the identification of the causes can be further discussed in the follow-up study concerning medical institutions with higher turnover rate of healthcare professionals. In our study, to assess the turnover rate of healthcare professionals in Taiwan, visual analytic dashboard was developed, which can provide the references for managers.
論文目次 摘 要 I
Abstract III
誌  謝 V
目 錄 VI
表 目 錄 VIII
圖 目 錄 IX
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 4
1.3 研究範圍與限制 5
1.4 研究架構 6
1.4.1 建構全民健康保險資料庫「基本資料檔」之商業智慧系統 6
1.4.2 進行醫療專業人員職涯異動分析-以藥師為例 6
1.4.3進行醫療專業人員職涯異動對於醫院營運績效之關係分析 6
1.5 研究流程 11
第二章 文獻回顧 13
2.1 醫療專業人員職涯異動與組織營運績效 13
2.1.1 醫療專業人員之工作滿意度、工作壓力、工作負荷與人員離職意向的關係 14
2.1.2 醫療工作人員離職率調查 15
2.1.3 員工流動對組織績效的影響 16
2.1.4 離職率定義 18
2.2 全民健康保險研究資料庫與相關研究 19
2.2.1 全民健康保險研究資料庫簡介 19
2.2.2 健保資料庫應用於醫事機構人力資源與醫事機構營運績效的相關研究 19
2.3 商業智慧 21
2.3.1 商業智慧的定義 21
2.3.2 線上分析處理 22
2.3.3 商業智慧於醫療照護產業的應用 23
2.3.4 國內應用商業智慧於醫療照護產業的相關研究 25
2.4 資料探勘 26
2.4.1 資料探勘的定義 26
2.4.2 預測 27
2.4.3 決策樹分析 29
2.4.4 資料探勘於健保資料庫的應用 30
第三章 研究方法 32
3.1 研究資料變數選定 32
3.2 決策問題之確立 34
3.3 商業智慧雛形系統之建置 36
3.4 研究工具 38
第四章 研究結果 39
4.1 建置開發全民健保資料庫「基本資料檔」商業智慧雛形系統 39
4.2 分析不同維度下醫事機構家數及變化趨勢 41
4.3 分析不同維度下各醫事機構藥師在職人數及性別、年齡分佈的變化情形,並預測未來藥師需求人數 44
4.4 分析不同維度下各醫事機構藥師歷年離職率的變化情形 57
4.5 由藥師執業登記資料分析影響藥師於兩年內離職的因素 61
4.6 影響醫事機構「醫事人員平均在職人數」的變數分析 76
4.7 影響醫事機構「醫事人員年離職率」的變數分析 80
4.8 影響醫事機構「醫療費用收入」的變數分析 84
4.9 影響醫事機構「平均每位醫事人員生產力」的變數分析 88
4.10 醫事人員平均在職人數、醫事人員離職率、醫療費用收入、平均每位醫事人員生產力之間的相關性分析 93
4.11 運用視覺化圖表呈現不同類型醫事機構之醫事人員離職率與經營績效發展趨勢 94
第五章 結論與建議 97
5.1 結論 97
5.2 管理意涵 100
5.3 後續研究建議 101
參考文獻 102
參考文獻 一、中文部份
1. 文羽苹、江東亮(2002),全民健康保險學術資料庫基本檔的應用經驗,台灣衛誌,第21卷,第2期,第150-155頁。
2. 李正揚(2008),台灣醫院經營者壓力來源之探討與經營之道,國立成功大學高階管理碩士在職專班碩士論文。
3. 吳坤山 & 張宏吉 (2010),管理科學導論,華泰文化事業股份有限公司。
4. 洪昌億(2005),決策樹應用在中西醫腦中風診斷之研究,長庚大學資訊管理研究所碩士論文。
5. 林敬淵(2012),應用資料探勘發掘健保醫療費用之特徵分析,玄奘大學資訊管理學系碩士論文。
6. 夏祥泰(2004),商業智慧應用於醫院管理之研究—以區域級醫院為例,中原大學資訊管理研究所碩士論文。
7. 高鴻文、林詩偉、萬書言(2012),運用決策樹演算法於護理人員離職預測-以某公立醫院為例,醫療資訊雜誌,第21眷,第4期,第15-30頁。
8. 陳啟元(2003),資料探勘技術於健保資料之應用-以醫院門診服務點數預測為例,國立中正大學資訊管理學系碩士論文。
9. 陳雪芳(2011),運用資料探勘技術探討國人主要癌症之關聯性與健保醫療資源耗用之研究,輔仁大學商學研究所博士論文。
10. 陳淑真(2005),醫療服務業人力需求分析,國立高雄師範大學工業科技教育學系碩士論文。
11. 陳偉佳(2013),運用資料探勘技術探討住院高醫療資源使用者之特性,明新科技大學電機工程研究所碩士論文。
12. 陳麗如(2011),應用商業智慧於醫療管理指標之決策輔助-以A區域醫院為例,國立高雄應用科技大學資訊管理系碩士在職專班碩士論文。
13. 張國安(2008),以時間數列分析預測台灣地區麻醉專科醫師人力供需,高雄醫學大學醫務管理學研究所碩士在職專班碩士論文。
14. 張淑芬(2010),資料探勘技術應用於健保資料庫探討重大疾病患者就診特性分析-以雲林縣居民為例,虎尾科技大學資訊管理研究所碩士論文。
15. 楊小芳(2010),商業智慧應用於健保局資料之醫療利用情形—以糖尿病為例,虎尾科技大學資訊管理研究所碩士論文。
16. 翟浩宇(2009),運用資料探勘分析中醫健保資料庫之研究,虎尾科技大學資訊管理研究所碩士論文。
17. 廖述賢&溫志皓(2009),資料採礦與商業智慧,雙葉書廊有限公司。
18. 鄭守夏(1999),全民健康保險學術資料庫簡介,中華民國公共衛生雜誌,第18卷,第3期,第235-236頁。
19. 鄭增加(2009),資料採礦之商業智慧於醫療院所經營管理之應用,國立政治大學經營管理碩士學程(EMBA) 碩士論文。
20. 劉純萍(2009),應用資料探勘技術於全民健保資料庫-以敗血症為例,國立中正大學資訊管理所暨醫療資訊管理所碩士論文。

二、英文部份
1. Aghion, P. and Howitt, P. (1996). The Observational Implications of Schumpeterian Growth Theory. Empirical Economics, 21(1), 13.
2. Beer, T., Newman, J. Job stress, employee health, and organizational effectiveness: A facet analysis, model and literature review.(1978).Personal Psychology, 1978; 31: 665-699.
3. Bernus, P., Jacek, G. S., & Błażewicz, M. S. (2008). International Handbooks on Information Systems. Springer.
4. Bonnarens, J. K. (2008). Characteristics of unmet demand for pharmacists: a survey of rural community pharmacies in Wisconsin. J Am Pharm Assoc, 48, 598-609.
5. Calgan, Z., Aslan, D., & Yegenoglu, S. (2011). Community pharmacists’ burnout levels and related factors: an example from Turkey. International Journal of Clinical Pharmacy, 33(1), 92-100.
6. Chaudhuri, S., Dayal, U., & Narasayya, V. (2011). An overview of business intelligence technology. Communications of the ACM, 54(8), 88-98.
7. Codd, E. F., Codd, S. B., & Salley, C. T. (1993). Providing OLAP (On-line Analytical Processing).
8. Dalton, D. R., Todor, W. D. and Krackhardt, D. M. (1982). Turnover Overstated: The Functional Taxonomy. Academy of Management Review, 7(1), 117-123.
9. Patterson, P. D., Jones, C. B., Hubble, M. W., Carr, M., Weaver, M. D., Engberg, J., & Castle, N. (2010). The longitudinal study of turnover and the cost of turnover in emergency medical services. Prehospital Emergency Care, 14(2), 209-221.
10. Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). From data mining to knowledge discovery in databases. AI magazine, 17(3), 37-54.
11. Ferranti, J. M., Langman, M. K., Tanaka, D., McCall, J., & Ahmad, A. (2010). Bridging the gap: leveraging business intelligence tools in support of patient safety and financial effectiveness. Journal of the American Medical Informatics Association, 17(2), 136-143.
12. Gaither, C. A., Nadkarni, A., Mott, D. A., Schommer, J. C., Doucette, W. R., Kreling, D. H., & Pedersen, C. A. (2007). Should I stay or should I go? The influence of individual and organizational factors on pharmacists’ future work plans. Journal of the American Pharmacists Association, 47(2), 165-173.
13. Gaither, C. A., Kahaleh, A. A., Doucette, W. R., Mott, D. A., Pederson, C. A., & Schommer, J. C. (2008). A modified model of pharmacists' job stress: The role of organizational, extra-role, and individual factors on work-related outcomes. Research in Social and Administrative Pharmacy, 4(3), 231-243.
14. Gray, A.M., Phillips, V.L.(1996). Labour turnover in the British National Health Service: a local labour market analysis. Health Policy, 36 (3), 273–289.
15. Huselid, M. (1995). The impact of human resource management practices on turnover, productivity, and corporate financial performance. Academy of management journal, 38(3), 635-672.
16. Ilmakunnas, P., & Maliranta, M. (2007). Aging, labor turnover and firm performance (No. 1092). ETLA Discussion Papers, The Research Institute of the Finnish Economy (ETLA).
17. Kindig, D.A., Schmelzer, J.R., & Hong, W. (1992). Age distribution and turnover of physicians in nonmetropolitan counties of the United States. Health Serv Res. 1992 October; 27(4): 565–578.
18. Lin, B. Y. J., Yeh, Y. C., & Lin, W. H. (2007). The influence of job characteristics on job outcomes of pharmacists in hospital, clinic, and community pharmacies. Journal of medical systems, 31(3), 224-229.
19. Liu, C. S., & White, L. (2011). Key determinants of hospital pharmacy staff's job satisfaction. Research in Social and Administrative Pharmacy, 7(1), 51-63.
20. Liu, L.F., Lee, S., Chia, P.F., Chi, S.C., Yin, Y.C.(2012). Exploring the association between nurse workload and nurse-sensitive patient safety outcome indicators. J Nurs Res. 2012 Dec; 20(4):300-9.
21. Mansukhani, M.P., Kolla, B.P., Surani, S., Varon, J., Ramar, K.(2012). Sleep deprivation in resident physicians, work hour limitations, and related outcomes: a systematic review of the literature. Postgrad Med. 2012 Jul; 124(4):241-9.
22. McCann, L., Hughes, C. M., Adair, C. G., & Cardwell, C. (2009). Assessing job satisfaction and stress among pharmacists in Northern Ireland. Pharmacy world & science, 31(2), 188-194.
23. Meier, K. J., & Hicklin, A. (2008). Employee turnover and organizational performance: Testing a hypothesis from classical public administration. Journal of Public Administration Research and Theory, 18(4), 573-590.
24. Mettler, T., & Vimarlund, V. (2009). Understanding business intelligence in the context of healthcare. Health Informatics Journal, 15(3), 254-264.
25. Misra, H., Kay, R., Stoller, J.K.(2004). A review of physician turnover: Rates, causes, and consequences. AJMQ. 2004 Mar; 19(2):56-66.
26. Montgomery, V.L.(2007). Effect of fatigue, workload, and environment on patient safety in the pediatric intensive care unit. Pediatr Crit Care Med. 2007 Mar; 8(2 Suppl):S11-6.
27. Negash, S. (2004). Business intelligence. Communications of the Association for Information Systems, 13(1), 177-195.
28. Parmanto, B., Paramita, M., Sugiantara, W., Pramana, G., Scotch, M., & Burke, D. (2008). Spatial and multidimensional visualization of Indonesia's village health statistics. International journal of health geographics, 7(1), 30.
29. Scotch, M., Parmanto, B., & Monaco, V. (2008). Evaluation of SOVAT: An OLAP-GIS decision support system for community health assessment data analysis. BMC medical informatics and decision making, 8(1), 22.
30. Seston, E., Hassell, K., Ferguson, J., & Hann, M. (2009). Exploring the relationship between pharmacists' job satisfaction, intention to quit the profession, and actual quitting. Research in social & administrative pharmacy: RSAP, 5(2), 121.
31. Shader, K., Broome, M. E., Broome, C. D., West, M. E., & Nash, M. (2001). Factors influencing satisfaction and anticipated turnover for nurses in an academic medical center. Journal of Nursing Administration, 31(4), 210-216.
32. Shields, M.A., Ward, M., 2001. Improving nurse retention in the National Health Service in England: the impact of job satisfaction on intentions to quit. Journal of Health Economics, 20 (5), 677–701.
33. Spetz, J., Rickles, J., Chapman, S., & Ong, P. M. (2008). Job and industry turnover for registered and licensed vocational nurses. Journal of Nursing Administration, 38(9), 372-378.
34. Thearling, K. (1999). An introduction to data mining. Whitepaper. http://www3. shore. net/~ kht/dmwhite/dmwhite. htm.
35. Vanasse, A., Scott, S., Courteau, J. & Orzanco, G. M. (2009). Canadian family physicians’ intentions to migrate - Associated factors. Can Fam Physician. 2009 April; 55(4): 396–397.e6.
36. Waldman, J.D., Kelly, F., Arora, S., Smith, H.L., 2004. The shocking cost of turnover in health care. Health Care Management Review, 29 (1), 2–7.
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