题名

運用決策樹技術探討基層診所門診量之影響因素

并列篇名

Analysis of outpatient visits to primary care clinics and its influencing factors using a decision tree model

DOI

10.6288/TJPH201635104052

作者

許文錦(Wen-Chin Hsu);李佳桓(Jia-Huan Li);余致廷(Chih-Ting Yu)

关键词

選址分析 ; 基層診所 ; 資料探勘 ; 地理資訊系統 ; location analysis ; primary care clinic ; data mining ; geographical information system

期刊名称

台灣公共衛生雜誌

卷期/出版年月

35卷3期(2016 / 06 / 01)

页次

281 - 293

内容语文

繁體中文

中文摘要

目標:開業地點對醫療院所經營具有重要影響力,便利性高的地點可提高病患就診意願,更可讓醫療院所取得競爭優勢。隨著開放資料時代來臨,如何運用開放資料協助選址成為醫療機構經營重要課題。本研究旨在運用資料探勘技術分析開放資料,探勘影響基層診所門診量的關鍵分類規則,藉以協助選址決策。方法:本研究以台北市306間高門診量基層診所為對象,蒐集相關之開放資料,包括社經資料、診所門診量、地價金額、地理空間資料等19項資料,運用CART決策樹分析影響高門診量診所之成功關鍵因素。結果:研究結果顯示決策樹分析之資訊增益順序為(可支配家庭收入>所屬行政區診所密度>女性人口數)。迴歸分析發現65歲以上人口數(β=0.836)與離最近捷運站距離(β=-0.297)顯著影響基層診所門診量(p<0.001)。結論:本研究所發現之選址分類規則可協助診所、藥局、醫療器材與政府衛生部門找出符合高門診量診所地理條件且尚未設立診所的位址,提供開業者選址參考。

英文摘要

Objectives: The process of locating health facilities has been studied extensively using mathematical optimization (e.g., covering model); however, few researchers have applied the techniques of data mining to this problem. This study proposes a novel prediction model, based on the Geographic Information System and data mining to assist in the selection of optimum locations for medical clinics. Methods: This study examined 306 medical clinics in Taipei, focusing on those with a high number of outpatients, using 19 variables associated with location decisions. A CART decision tree was used in the development of the model based on the collected variables. Results: The decision tree model indicated that household disposable income has the strongest impact on the number of outpatients, followed by clinic density, and gender. Regression analysis identified age, and distance to the nearest Mass Rapid Transit station as the two factors with a significant effect on the number of outpatients at a given clinic (p<0.001). Conclusions: This study constructed a novel prediction model to aide in identifying the optimal location for a clinic and evaluating options with regard to clinic relocation.

主题分类 醫藥衛生 > 預防保健與衛生學
醫藥衛生 > 社會醫學
参考文献
  1. 莊榮霖(2002)。全民健保對老人財務負擔及醫療需求的影響─以雲嘉南地區為例。醫務管理期刊,3,72-82。
    連結:
  2. 楊宜芬、孫志鴻、榮峻德(2007)。銀行區位選址決策支援系統之研發以台北市為例。中國地理學會會刊,38,45-65。
    連結:
  3. 衛生福利部:中華民國102年老人狀況調查報告,2014。http://www.mohw.gov.tw/。引用2015/06/10。Ministry of Health and Welfare, R.O.C. (Taiwan).Report of the senior citizen condition survey 2013. Available at: http://www.mohw.gov.tw/. Accessed June 10, 2015. [In Chinese]
  4. 衛生福利部中央健康保險署:全民健康保險醫療服務給付項目及支付標準,2015. http://www.nhi.gov.tw。引用2015/06/10。National Health Insurance Administration, Ministry of Health and Welfare, R.O.C. (Taiwan). National Health Insurance payment items and criteria for medical services, 2015. Available at: http://www.nhi.gov.tw.Accessed June 10, 2015. [In Chinese]
  5. 台北市政府民政局:台北市各區戶政事務所。http://ca.gov.taipei。引用2014/02/01。Department of Civil Affairs, Taipei City Governmen. Information of the household registration offices. Available at: http://ca.gov.taipei. Accessed February 1, 2014. [In Chinese]
  6. 信義房屋:統計資訊,2014。http://www.sinyi.com.tw/。引用2014/02/01。Sinyi Realty. Statistical information. Available at: http://www.sinyi.com.tw/. Accessed February 1, 2014. [In Chinese]
  7. 永慶房屋:統計資訊,2014。http://www.yungching.com.tw/。引用2014/02/01。Yung-Ching Realty. Statistical information. Available at: http://www.yungching.com.tw/. Accessed February 1, 2014. [In Chinese]
  8. 台北市政府主計處:102年台北市家庭收支訪問調查報告。台北:台北市政府,2014。Department of Budget, Accounting and Statistics, Taipei City Government. Report on the Survey of Family Income and Expenditure, 2013. Taipei: Taipei City Government, 2014. [In Chinese: English abstract]
  9. 台北市政府資料開放平台:統計資訊,2014。http://data.taipei.gov.tw/。引用2015/06/10。Data Taipei. Statistical information. Available at: http://data.taipei.gov.tw/. Accessed June 10, 2015. [In Chinese]
  10. Andersen, RM(1995).Revisiting the behavioral model and access to medical care: does it matter?.J Health Soc Behav,36,1-10.
  11. Arcury, TA,Gesler, WM,Preisser, JS,Sherman, J,Spencer, J,Perin, J(2005).The effects of geography and spatial behavior on health care utilization among the residents of a rural region.Health Serv Res,40,135-56.
  12. Bertakis, KD,Azari, R,Helms, LJ,Callahan, EJ,Robbins, JA.(2000).Gender differences in the utilization of health care services.J Fam Pract,49,147-52.
  13. Branas, CC,MacKenzie, EJ,ReVelle, CS(2000).A trauma resource allocation model for ambulances and hospitals.Health Serv Res,35,489-507.
  14. Delen, D,Walker, G,Kadam, A(2005).Predicting breast cancer survivability: a comparison of three data mining methods.Artif Intell Med,34,113-27.
  15. Dhingra, T,Singh, T,Sinha, A.(2009).Location strategy for competitiveness of special economic zones: a generic framework for India.Competitiveness Review,19,272-89.
  16. Doerner, K,Focke, A,Gutjahr, WJ(2007).Multicriteria tour planning for mobile healthcare facilities in a developing country.Eur J Oper Res,179,1078-96.
  17. Fayyad, U,Piatetsky-Shapiro, G,Smyth, P.(1996).From data mining to knowledge discovery in databases.AI Mag,17,37-54.
  18. Harper, P,Shahani, A,Gallagher, J,Bowie, C.(2005).Planning health services with explicit geographical considerations: a stochastic location-allocation approach.Omega,33,141-52.
  19. Hsu, WC,Bath, PA,Large, S,Williams, S(2013).The association of geographical location and neighbourhood deprivation with older people's use of NHS Direct: a population-based study.Age Ageing,42,57-62.
  20. Jiang, P,Liu, XS(2015).Big data mining yields novel insights on cancer.Nat Genet,47,103-4.
  21. Kavitha, KS,Ramakrishnan, KV,Singh, MK(2010).Modeling and design of evolutionary neural network for heart disease detection.IJCSI,7,272-83.
  22. Kavitha, PT,Sasipraba, T.(2012).Knowledge driven healthcare decision support system using distributed data mining.IJCSE,3,464-9.
  23. Khemphila, A,Boonjing, V.(2011).Heart disease classification using neural network and feature selection.Proceedings of 21st International Conference on Systems Engineering (ICSEng),Los Alamitos, CA:
  24. Mehrez, A,Sinuany-Stern, Z,Arad-Geva, T,Binyamin, S(1996).On the implementation of quantitative facility location models: the case of a hospital in a rural region.J Oper Res Soc,47,612-25.
  25. Oksuzyan, A,Juel, K,Vaupel, JW,Christensen, K(2008).Men: good health and high mortality. Sex differences in health and aging.Aging Clin Exp Res,20,91-102.
  26. Rahman, S,Smith, DK(2000).Use of location-allocation models in health service development planning in developing nations.Eur J Oper Res,123,437-52.
  27. Rosero-Bixby, L.(2004).Spatial access to health care in Costa Rica and its equity: a GIS-based study.Soc Sci Med,58,1271-84.
  28. Sainfort, F(ed.),Brandeau, M(ed.),Pierskalla, W(ed.)(2004).Handbook of OR/MS in Health Care: A Handbook of Methods and Applications.Boston:Kluwer Academic Publishers.
  29. Shalowitz, DI,Vinograd, AM,Giuntoli, RL.(2015).Geographic access to gynecologic cancer care in the United States.Gynecol Oncol,138,115-20.
  30. Stahl, JE,Kong, N,Shechter, SM,Schaefer, AJ,Roberts, MS(2005).A methodological framework for optimally reorganizing liver transplant regions.Med Decis Making,25,35-46.
  31. Tannenbaum, C,Diaby, V,Singh, D,Perreault, S,Luc, M,Vasiliadis, HM(2015).Sedative-hypnotic medicines and falls in community-dwelling older adults: a costeffectiveness (decision-tree) analysis from a US Medicare perspective.Drugs Aging,32,305-14.
  32. Tsumoto, S.(2004).Mining diagnostic rules from clinical databases using rough sets and medical diagnostic model.Inform Sci,162,65-80.
  33. Walker, PG,White, MT,Griffin, JT,Reynolds, A,Ferguson, NM,Ghani, AC.(2015).Malaria morbidity and mortality in Ebola-affected countries caused by decreased health-care capacity, and the potential effect of mitigation strategies: a modelling analysis.Lancet Infect Dis,15,825-32.
  34. Wun, YT,Lam, TP,Lam, KF,Goldberg, D,Li, DK,Yip, KC(2010).How do patients choose their doctors for primary care in a free market?.J Eval Clin Pract,16,1215-20.
  35. Zhou, S,Cheng, Y,Xiao, M,Bao, X(2013).Assessing the location of public-and-community facilities for the elderly in Beijing, China.GeoJournal,78,539-51.
  36. 姜文瑞、王玉英、郝小琪、李富鵬(2012)。決策樹方法在氣溫預測中的應用。計算機應用與軟件,29,141-4。
  37. 梅明德、許御衡、邱玉文、蔡靜慧(2009)。運用地理資訊系統輔助連鎖式商店開設位址評選。地理資訊系統季刊,3,21-31。
  38. 陳盈君(2015)。台北=Taipei,國立台灣大學台大─復旦EMBA境外專班=NTU-Fudan EMBA Program, National Taiwan University。
  39. 歐陽鍾玲(2006)。台北市醫療設施分佈之地理研究。地理研究,45,51-72。