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| 標題: | 癌症臨終病患選擇安寧療護之特性探討一利用決策樹於健保研究資料庫
Characteristics of terminal cancer patients in hospice care units：a decision tree analysis of insurance data |
| 作者: | 郭育廷
Yu-Ting Kuo |
| 貢獻者: | 楊美雪
嘉南藥理科技大學：醫療資訊管理研究所 |
| 關鍵字: | 決策樹
癌症
安寧療護
Hospice
Decision tree
Cancer |
| 日期: | 2008 |
| 上傳時間: | 2010-06-01 09:21:32 (UTC+8) |
| 摘要: | 目標:從文獻探討，安寧療護之住院醫療費用比非安寧療護節省，又可有效地減輕癌症病患身、心、靈痛苦，是值得推展的照護型態。本研究以資料探勘決策樹技術分析健保資料庫癌症末期選擇安寧之病患的有意義資訊，作為提升安寧療護使用率之政策制定的參考。方法:擷取2005年健保研究資料庫住院癌症死亡病患為研究樣本，與醫事機構基本資料檔連結獲取病患醫院權屬別、評鑑等級及分局別資料。依Charlson comorbidity index , CCI計算病患診斷共存疾病指標分數，並將年齡與CCI資料轉換為類別變數，統計分析包括描述性與卡方統計檢定，以SPSS Clementine 7.2建構決策樹模型，目標變數(輸出變數)為照護型態類別(安寧/非安寧);輸入變數包括人口學、臨床及醫院特性。評估決策樹C5.0及CART演算法建模預測正確績效，選擇較佳的演算法建模，萃取安寧療護分類規則。結果:臨終癌症病患安寧住院療護的平均每人次費用35,385，63元比傳統住院安寧療護的平均費用145,478低(p<0.001)。病患性別、年齡、癌症別、CCI別、醫院權屬別、評鑑等級別、分局別等變數，分別與照護型態有統計上顯著關聯(p<0.0001)。本研究資料C5.0演算法之正確率大於CART演算法。決策樹C5.0演算法資訊增益三大變數依序為醫院權屬別、分局別、等級別，以醫院權屬別為最重要之照護型態分類預測變數。性別變數並沒有被選取為樹之內部節點，顯示在其他變數存在下，性別並不是影響臨終病患選擇安寧之因素，即使性別在女性使用率27.62%顯著高於男性23.01%。本研究萃取安寧療護分類規則7條，其中較有意義的資訊，依信心度大小有宗教財團法人醫院(0.893) 、財團法人北區地區醫院(0.872) 、私立中區地區醫院(0.857)及財團法人東區醫學中心(0.837)。結論:安寧療護的費用比非安寧節省，宗教財團法人醫院是為癌症末期臨終病患或家屬之最佳善終醫療場所。本研究建議宗教財團法人醫院可為非宗教醫院之標竿學習對象。至於宗教與安寧療護之相關，有待後續的研究進一步深入探討。
Objectives: From literature review, inpatient medicare expenditure of hospice saving than non-hospice, and effectively reduce cancer patients physical and mental and spiritual pain, worthwhile to promote type of care. The aim of this study was use Data Mining Decision tree analyze the Bureau of National Health Insurance database that the terminal cancer patient which chose hospice, to find out the meaning information, to promote hospice’s using provide a policy for government referable.
Method: Data from National Health Insurance Research Database of the inpatient cancer patients who had death in 2005 were studied, connect with HOSP obtains patient’s data of ownership, ranking level, Branch Bureau. Count Charlson comorbidity index of patient diagnosis(Charlson comorbidity index, CCI), age and CCI transform category variable, statistical analysis including descriptive statistics and Chi test, Utilization SPSS Clementine 7.2 to establish decision tree model, Output variables for the type of care patterns(hospice/nonhospice); input variable including demographic, clinical and hospital characteristics. Assessment decision tree C5.0 and CART algorithm modeling of correctly predicted performance, choose better algorithm modeling to extraction classification rule of hospice.
Results: Variables of patient gender, age, type of cancer, ownership, ranking level, Branch Bureau has significant difference in statistical with type of care, respectively (p<0.001). The study data of C5.0 algorithms correct rate is greater than the CART algorithm. Decision tree algorithms of C5.0 gain information were the three major variables for the hospital ownership, Branch Bureau, ranking level, hospital ownership is most important classification predict variable of care type. All of characteristics in hospice and nonhospice of relatively has significant difference, The other hand, the result shows while other variables exist, gender was not impact factor of patient who choose hospice, even female in the utilization rate of 27.62% was significantly higher than male of 23.01%.The study extraction 7 rule from hospice classification, all of rule choose meaningful information, in accordance with the size of confidence in a Religious Foundation Hospital (0.893), Foundation North Region Branch AREA Hospital(0.872), Private Center Region Branch AREA Hospitals(0.857), Foundation Eastern Medical Centers(0.837).
Conclusions: The study found that patients with terminal cancer, medicare expenditure of hospice has significant lower than nonhospice, analysis result of decision tree, information gain for the largest hospital ownership, Religious Foundation Hospital predicted accuracy rate of 0.893, Religion Foundation hospitals show that is dying for terminal cancer patients or their families for the best hospice medical establishments. Finally, the study suggest that Religion Foundation hospitals can be learning objects to non- Religion Foundation hospitals. In the case of correlation between religion and hospice, waiting for follow-up researchers to further study. |
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