學術產出-學位論文

題名 資料採礦為工具的策略性顧客關係管理-以開蘭聯合診所為例
作者 陳柏瑞
Chen, Po-Juei
貢獻者 劉文卿
Liou, Wen-ching
陳柏瑞
Chen, Po-Juei
關鍵詞 資料採礦
門診病人顧客關係管理
CRM策略管理
門診病人分群
資料探勘
開蘭聯合診所
日期 2002
上傳時間 18-九月-2009 14:42:11 (UTC+8)
摘要 顧客關係管理(CRM)在國內外已有不少應用實例,但在醫療服務業鮮少被研究過,本研究嚐試將資料採礦的三大核心技術:資料庫管理、Domain知識與資料採礦技術三者予以整合,針對一個獨立經營主體(聯合診所),從行銷策略制定、營運策略描述與執行到經由資料採礦得到具體結果,重新檢討行銷策略之STP定位與導引未來經營策略,並提出一對一行銷的診所病患管理架構。
本研究以一個新成立的診所,取其開業之初(89年12月)至92年1月底止,所累積九千三百多位患者的5萬多筆門診就醫記錄進行資料採礦分析希望研究以下幾個問題:
1.哪些病患帶來最大利潤?為甚麼?哪些患者容易流失?為甚麼?
2.哪些交叉服務對何種患者適合?哪些服務對增加慢性病患者有幫助?糖尿病患者接受視網膜檢查的可能原因為何?婦產科門診所增加的病患,是否會同時接受診所內其他科的服務?是否應該繼續擴大其他專科?
3.診所病患主要的居住地區如何描述?
研究結果顯示較高獲利組與高醫療費用,高忠誠度,高就診次數,高藥費比率,高慢性病費用比率有關,以疾病別來看,集中在慢性疾病患者身上。顯然經營策略上的意涵是如何爭取慢性病人的高度滿意及信賴度,贏得高忠程度,患者願意將診所視做健康上的守門人(Gate Keeper),而從地區別分析中也發現一些,診所服務之涵蓋範圍,可以區分為距離效益、慢性病患者口碑效應與轉移效益。慢性病患者之分群可以分成黃金老主顧、會忘記看病的老主顧、快流失的老主顧、高穩定低忠誠度高獲利新客戶、不常來但還會來的一般客戶、已流失的舊客戶、已流失的中期客戶及流失已久的舊客戶,至於非慢性病患則不需太複雜的分群,本研究建議將非慢性病患者依健保卡卡序計算就醫忠誠度區分。慢性病患群流失的原因與無法提供完整治療,疾病症狀不明顯或與民眾對治療效益的看法改變有關(如更年期)有關。
就病人區隔分析及交叉服務的相關分析都可以發現,以慢性疾病群為中心,針對不同疾病群發展網路治療團隊,應該是未來診所擴張時需要遵循的最重要策略原則;另外健保案件類別的交叉分析,也發現增加預防保健服務可以增加慢性病人的案件,診所需要將成人健康檢查業務當作策略性業務,加強重視並提升品質。
本研究針對描述患者求醫行為過程所發展出對個人主要疾病診斷碼的歸戶處理、RFM相關指標方式、健保卡卡序計算忠誠度及邊際利潤的計算方式對於類似研究應該有其參考價值。至於本研究所提出的診所病患群分群架構,則有待進一步評估其達到CRM顧客最佳化的效果。
At present, there are much of researches of Customer Relationship Management ( CRM ) and data mining in Taiwan. There is little research in medical service. Our research tried to integrate the three domains knowledge, DBA, domain knowledge of medical service and data mining techniques. This is a case study type research. The CRM Strategy Planning for Outpatient in Kai-Nan Group Practice Clinic by Data Mining on National Health Insurance Dataset. This research included 9300 cases of Kai-Nan Clinic, with nearly 50,000 records of OPD records from Dec, 2000 to Jan, 2003. Our research questions include as followings:
1、How to segment the outpatient, which segment is the most profitable? Which segment is loosing? Why?
2、Which cross service is necessary for what kinds of patients? What kinds of services will be benefit for recruiting chronic patient? What is the reason for the diabetes patient will receive funds examination in this clinic? Are the patients of GYN/OBS will also to be patients of other specialty? Is it necessary to include other specialty in this clinic?
3. Where is the most profitable patient in nearby area?
Our study revealed that the most profitable patients is characterized by high medical cost, high loyalty to this clinic, high visit frequencies, high portion of medication fee and high portion of fee for chronic disease. Most of the profitable patients are suffered with chronic diseases. This implies that how to satisfy chronic patient with high satisfaction and earn their trust to be health gate keeper for this patient is very import issue for a clinic. From the results of area analysis for these chronic patients, we concluded the three effects for different areas, such as near-distant effect, public praise and addict effect for original doctors. The segments of chronic patients include golden regular customer、forgetful regular customer、loosing old customer、regular but lower loyalty profitable new customer、irregular general customer、loosed old customer、loosed past customer and loosed old customer. Regarding the segmentation of outpatients of acute illness, we recommended simplify classification according to loyalty that was calculated from the sequence of national health insurance card used in Taiwan. The chronic patients loosed in the clinic was due to lack of comprehensive treatment options, non obvious symptoms or the fears of treatment side effects announced from public media,such as hormone replacement therapy for post menopausal syndrome. We conclude that multidisciplinary team for comprehensive disease management is very important for clinics as our previous success experiences on diabetes patients. Our clinic should expand teams with out bond member according to the needs of our profiles of chronic patients. From association mining, periodic health examinations increase the base of chronic patients. It is strategic important to enhance the staffs and facility for handling periodic health examinations. Our research will also contribute to the following research issues , such as how to describe patients behaviors, how to extract the dominant diagnosis from patients health insurance records, modified RFM dimensions indexes、loyalty based on sequences of health insurance card in Taiwan and the model of calculation of marginal revenue for clinics. As regarding the efficacy of the patients’ segmentation model deserved further study.
參考文獻 第一節 中文部分
1. 彭文正譯(2001) ,「Data Mining資料採礦─顧客關係管理暨電子行銷之應用」,台北:維科圖書有限公司。 譯自Michael J.A. Berry,Gordon S. Linoff。
2. 吳旭智、賴淑貞譯(2001),「Data Mining 資料採礦理論與實務顧客關係管理的技巧與科學」。台北:維科圖書有限公司。譯自 Berry, Michael J.A.and Gordon S. Linoff。
3. 安訊資訊(2000),「會員導向時代的企業智慧腦」,資訊與電腦,第240期,民國89年7月,頁50-53。
4. 榮泰生(2002),顧客關係管理的策略規劃--以台灣大型醫療產業為例,輔仁大學管理學研究所碩士論文。
5. 孫安華(2002),醫院採用顧客關係管理之研究,國立成功大學企業管理學系碩士碩士論文。
6. 侯世環(2002),醫療院所顧客關係管理架構之建立及實證,國立交通大學經營管理研究所碩士論文。
7. 廖舜怡(2002),一對一顧客關係管理系統之建構—以醫療體系為例,國立成功大學工業管理科學系碩士論文。
8. 陳冠華(2002),藉由顧客關係管理方法提升門診病患的醫療服務品質∼以某區域醫院高齡慢性病患為例,雲林科技大學工業工程與管理研究所碩士論文
9. 江士彥(2002),醫療顧客關係管理之顧客需求與滿意度分群分析-以國內某準醫學中心為例,元智大學/資訊管理學系碩士論文。
10. 楊珮伶(2001),企業整體顧客關係管理運作模式之研究,國立政治大學資訊管理學系碩士論文
11. 陳佳楨(2003),資料探勘應用於就診行為與醫師排班之研究─ 以埔里基督教醫院為例,暨南國際大學資訊管理研究所碩士論文。
12. 黃仁貴(2002),以叢集分析技術探討病患就診屬性與看診時間之關係, 台北醫學院醫學資訊研究所碩士論文。
13. 李姿儀(2001),醫院門診資料探勘—以虎尾若瑟醫院為例,南華大學資訊管理學系碩士論文。
14. 黃勝崇(2001),資料探勘應用於醫療院所輔助病患看診指引之研究,南華大學資訊管理學系碩士論文。
15. 吳佩璟(2000),「全民健保實施下影響門診病患選擇就醫層級之因素探討」,台北大學財政學系碩士論文。
16. 吳國禎(2000),「資料探索在醫學資料庫之應用」,中原大學醫學工程學系碩士論文。
17. 李姿儀(2000),「醫院門診資料探勘—以虎尾若瑟醫院為例」,南華大學資訊管理研究所碩士論文。
18. 林信忠(1998),「資料發掘技術應用於健保醫療費用稽核之研究」,元智大學管理研究所碩士論文
19. 陳才友(2001),「慢性病患者的醫病關係與待診時間」,台北醫學院醫學研究所碩士論文
20. 黃仁貴(2001),「以叢集分析技術探討病患就診屬性與看診時間之關係」,台北醫學院醫學 研究所碩士論文。
21. 劉偉文(1999),「醫療行銷對病患滿意度之實證研究」,中正大學企業管理研究所碩士論文。
22. 方世榮編譯(1995),「行銷管理學-分析、計畫、執行與控制」,二版,東華書局,台北,譯自Kolter, Philip原著
23. 周麗芳(2000),我國藥品部分負擔經濟效果衡量模型之建立An Economic Model on the Cost Sharing of Presciription Drugs in the National Health Insurance國立政治大學學報民89.06 頁33-56
24. 吳思華(2000),策略九說,三版 臉譜出版 頁38
25. 張倩茜譯(2001) ,資料庫行銷實用策略,台北:麥格羅希爾國際出版公司。 譯自Strategic Database Marketing by Arthur M. Hughes 。
第二節 英文部分
1. Dickson, Peter R. Erson-Situration:Segmentation’s Missing Link ; Journal of Marketing, Vol.46 Issue 4, Fall 1982, pp.56-64
2. Rigby DK. Reichheld FF. Schefter P. Avoid the four perils of CRM. [Journal Article] Harvard Business Review. 80(2):101-6, 108-9, 130, 2002 Feb.
3. Beveridge RN. Creating value-focused healthcare delivery systems: Part three--Core competencies. [Journal Article] Journal of Oncology Management. 6(6):16-23, 1997 Nov-Dec.
4. Berwick DM. The total customer relationship in health care: broadening the bandwidth. [Journal Article] Joint Commission Journal on Quality Improvement. 23(5):245-50, 1997 May.
5. Pak S. Pol LG. Segmenting the senior health care market. [Journal Article] Health Marketing Quarterly. 13(4):63-77, 1996
6. Powers TL. Trawick IF Jr. Health care seeking behavior of the elderly: an empirical investigation. [Journal Article] Journal of Ambulatory Care Marketing. 5(1):49-57, 1992.
7. Chilingerian JA. New directions for hospital strategic management: the market for efficient care. [Journal Article] Health Care Management Review. 17(4):73-80, 1992 Fall.
8. Pointer DD. Offering-level strategy formulation in health service organizations. [Journal Article] Health Care Management Review. 15(3):15-23, 1990 Summer.
9. MacStravic S. Market and market segment portfolio assessment for hospitals. [Review] [21 refs] [Journal Article. Review. Review, Tutorial] Health Care Management Review. 14(3):25-32, 1989 Summer.
10. Klegon DA. Gregory DD. Kingstrom PO. Planning for ambulatory care delivery systems: a market segment approach. [Journal Article] Health Care Management Review. 7(1):35-45, 1982 Winter.
11. Becker, Brian E. The HR Scorecard:linking people,Strategy, and performance.(Boston,MA:Harvard Business School Press, 2001).
第三節網路部分
1. IBM Corporation(1999): 使用 Intelligent Miner for Data 版本六,版次一 (http://www.redbooks.ibm.com)
2. Nick Poulos(1999):How to identify your ideal Customer(and beat everyone else to the punch) or 【Actionable Segmentation:(A Versioning Approach:Applying Rapid Prototyping to Needs-AND Value-Based Segmentation)】(http://www.eloyaltyco.com)
描述 碩士
國立政治大學
經營管理碩士學程(EMBA)
89932068
91
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0089932068
資料類型 thesis
dc.contributor.advisor 劉文卿zh_TW
dc.contributor.advisor Liou, Wen-chingen_US
dc.contributor.author (作者) 陳柏瑞zh_TW
dc.contributor.author (作者) Chen, Po-Jueien_US
dc.creator (作者) 陳柏瑞zh_TW
dc.creator (作者) Chen, Po-Jueien_US
dc.date (日期) 2002en_US
dc.date.accessioned 18-九月-2009 14:42:11 (UTC+8)-
dc.date.available 18-九月-2009 14:42:11 (UTC+8)-
dc.date.issued (上傳時間) 18-九月-2009 14:42:11 (UTC+8)-
dc.identifier (其他 識別碼) G0089932068en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/35308-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 經營管理碩士學程(EMBA)zh_TW
dc.description (描述) 89932068zh_TW
dc.description (描述) 91zh_TW
dc.description.abstract (摘要) 顧客關係管理(CRM)在國內外已有不少應用實例,但在醫療服務業鮮少被研究過,本研究嚐試將資料採礦的三大核心技術:資料庫管理、Domain知識與資料採礦技術三者予以整合,針對一個獨立經營主體(聯合診所),從行銷策略制定、營運策略描述與執行到經由資料採礦得到具體結果,重新檢討行銷策略之STP定位與導引未來經營策略,並提出一對一行銷的診所病患管理架構。
本研究以一個新成立的診所,取其開業之初(89年12月)至92年1月底止,所累積九千三百多位患者的5萬多筆門診就醫記錄進行資料採礦分析希望研究以下幾個問題:
1.哪些病患帶來最大利潤?為甚麼?哪些患者容易流失?為甚麼?
2.哪些交叉服務對何種患者適合?哪些服務對增加慢性病患者有幫助?糖尿病患者接受視網膜檢查的可能原因為何?婦產科門診所增加的病患,是否會同時接受診所內其他科的服務?是否應該繼續擴大其他專科?
3.診所病患主要的居住地區如何描述?
研究結果顯示較高獲利組與高醫療費用,高忠誠度,高就診次數,高藥費比率,高慢性病費用比率有關,以疾病別來看,集中在慢性疾病患者身上。顯然經營策略上的意涵是如何爭取慢性病人的高度滿意及信賴度,贏得高忠程度,患者願意將診所視做健康上的守門人(Gate Keeper),而從地區別分析中也發現一些,診所服務之涵蓋範圍,可以區分為距離效益、慢性病患者口碑效應與轉移效益。慢性病患者之分群可以分成黃金老主顧、會忘記看病的老主顧、快流失的老主顧、高穩定低忠誠度高獲利新客戶、不常來但還會來的一般客戶、已流失的舊客戶、已流失的中期客戶及流失已久的舊客戶,至於非慢性病患則不需太複雜的分群,本研究建議將非慢性病患者依健保卡卡序計算就醫忠誠度區分。慢性病患群流失的原因與無法提供完整治療,疾病症狀不明顯或與民眾對治療效益的看法改變有關(如更年期)有關。
就病人區隔分析及交叉服務的相關分析都可以發現,以慢性疾病群為中心,針對不同疾病群發展網路治療團隊,應該是未來診所擴張時需要遵循的最重要策略原則;另外健保案件類別的交叉分析,也發現增加預防保健服務可以增加慢性病人的案件,診所需要將成人健康檢查業務當作策略性業務,加強重視並提升品質。
本研究針對描述患者求醫行為過程所發展出對個人主要疾病診斷碼的歸戶處理、RFM相關指標方式、健保卡卡序計算忠誠度及邊際利潤的計算方式對於類似研究應該有其參考價值。至於本研究所提出的診所病患群分群架構,則有待進一步評估其達到CRM顧客最佳化的效果。
zh_TW
dc.description.abstract (摘要) At present, there are much of researches of Customer Relationship Management ( CRM ) and data mining in Taiwan. There is little research in medical service. Our research tried to integrate the three domains knowledge, DBA, domain knowledge of medical service and data mining techniques. This is a case study type research. The CRM Strategy Planning for Outpatient in Kai-Nan Group Practice Clinic by Data Mining on National Health Insurance Dataset. This research included 9300 cases of Kai-Nan Clinic, with nearly 50,000 records of OPD records from Dec, 2000 to Jan, 2003. Our research questions include as followings:
1、How to segment the outpatient, which segment is the most profitable? Which segment is loosing? Why?
2、Which cross service is necessary for what kinds of patients? What kinds of services will be benefit for recruiting chronic patient? What is the reason for the diabetes patient will receive funds examination in this clinic? Are the patients of GYN/OBS will also to be patients of other specialty? Is it necessary to include other specialty in this clinic?
3. Where is the most profitable patient in nearby area?
Our study revealed that the most profitable patients is characterized by high medical cost, high loyalty to this clinic, high visit frequencies, high portion of medication fee and high portion of fee for chronic disease. Most of the profitable patients are suffered with chronic diseases. This implies that how to satisfy chronic patient with high satisfaction and earn their trust to be health gate keeper for this patient is very import issue for a clinic. From the results of area analysis for these chronic patients, we concluded the three effects for different areas, such as near-distant effect, public praise and addict effect for original doctors. The segments of chronic patients include golden regular customer、forgetful regular customer、loosing old customer、regular but lower loyalty profitable new customer、irregular general customer、loosed old customer、loosed past customer and loosed old customer. Regarding the segmentation of outpatients of acute illness, we recommended simplify classification according to loyalty that was calculated from the sequence of national health insurance card used in Taiwan. The chronic patients loosed in the clinic was due to lack of comprehensive treatment options, non obvious symptoms or the fears of treatment side effects announced from public media,such as hormone replacement therapy for post menopausal syndrome. We conclude that multidisciplinary team for comprehensive disease management is very important for clinics as our previous success experiences on diabetes patients. Our clinic should expand teams with out bond member according to the needs of our profiles of chronic patients. From association mining, periodic health examinations increase the base of chronic patients. It is strategic important to enhance the staffs and facility for handling periodic health examinations. Our research will also contribute to the following research issues , such as how to describe patients behaviors, how to extract the dominant diagnosis from patients health insurance records, modified RFM dimensions indexes、loyalty based on sequences of health insurance card in Taiwan and the model of calculation of marginal revenue for clinics. As regarding the efficacy of the patients’ segmentation model deserved further study.
en_US
dc.description.tableofcontents 目錄
第一章 緒論 12
第二章 文獻探討 14
第一節 客戶關係管理的定義與運用 14
第二節 策略性CRM 14
第三節 資料採礦 15
第四節 醫療產業下的CRM倫理觀點 15
第五節 市場區隔相關討論 16
第六節 國內醫療產業下的CRM現況 18
第七節 人口統計叢集化採礦功能簡介 23
第八節 樹狀分類採礦功能(IBM1999) 24
第九節 「關聯」採礦功能(IBM1999) 25
第三章 研究架構:個案研究與資料分析架構圖 26
第四章 個案介紹 29
第五章 研究流程與設計 41
第一節 經營問題定義(Define Business Issues) 41
第二節 可供分析資料定義(Define a data model to use) 43
第三節 重要欄位特殊處理方式說明 Sourcing and preprocessing 46
第四節 Evaluating the data quality 53
第六章 使用Intelligent Miner軟體工具的實做結果 54
第七章 經營決策與行銷意涵Deploying the results into our business 97
第一節 行銷策略檢討: 97
第二節 經營策略檢討 98
第三節 一對一行銷模式:Mass Customization 101
第八章 結論 104
第一節 論文貢獻 104
第二節 未來發展方向 105
第九章 參考文獻 106
第一節 中文部分 106
第二節 英文部分 108
第三節 網路部分 110
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dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0089932068en_US
dc.subject (關鍵詞) 資料採礦zh_TW
dc.subject (關鍵詞) 門診病人顧客關係管理zh_TW
dc.subject (關鍵詞) CRM策略管理zh_TW
dc.subject (關鍵詞) 門診病人分群zh_TW
dc.subject (關鍵詞) 資料探勘zh_TW
dc.subject (關鍵詞) 開蘭聯合診所en_US
dc.title (題名) 資料採礦為工具的策略性顧客關係管理-以開蘭聯合診所為例zh_TW
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 第一節 中文部分zh_TW
dc.relation.reference (參考文獻) 1. 彭文正譯(2001) ,「Data Mining資料採礦─顧客關係管理暨電子行銷之應用」,台北:維科圖書有限公司。 譯自Michael J.A. Berry,Gordon S. Linoff。zh_TW
dc.relation.reference (參考文獻) 2. 吳旭智、賴淑貞譯(2001),「Data Mining 資料採礦理論與實務顧客關係管理的技巧與科學」。台北:維科圖書有限公司。譯自 Berry, Michael J.A.and Gordon S. Linoff。zh_TW
dc.relation.reference (參考文獻) 3. 安訊資訊(2000),「會員導向時代的企業智慧腦」,資訊與電腦,第240期,民國89年7月,頁50-53。zh_TW
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dc.relation.reference (參考文獻) 10. 楊珮伶(2001),企業整體顧客關係管理運作模式之研究,國立政治大學資訊管理學系碩士論文zh_TW
dc.relation.reference (參考文獻) 11. 陳佳楨(2003),資料探勘應用於就診行為與醫師排班之研究─ 以埔里基督教醫院為例,暨南國際大學資訊管理研究所碩士論文。zh_TW
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dc.relation.reference (參考文獻) 第二節 英文部分zh_TW
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dc.relation.reference (參考文獻) 第三節網路部分zh_TW
dc.relation.reference (參考文獻) 1. IBM Corporation(1999): 使用 Intelligent Miner for Data 版本六,版次一 (http://www.redbooks.ibm.com)zh_TW
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