Charlson合併症指數對全民健康保險資料庫適用性之探討

Adaptability of Charlson Comorbidity Index (CCI) on the National Health Insurance Research Database

10.6288/TJPH2007-26-06-06

柯玲晶(Ling-Ching Ko)；譚醒朝(Sing-Chew Tam)；譚家惠(Chia-Hui Tan)

Charlson合併症指數 ； 合併症 ； charlson comorbidity index CCI ； comorbidity

台灣公共衛生雜誌

26卷6期（2007 / 12 / 01）

491 - 498

繁體中文

目標：以全民健保資料庫實証不同合併症指數對病人存活情形解釋力的差異，本研究試以Charlson合併症加權方法與合併症疾病定義，發展適合本國之合併症疾病加權值。方法：以民國90年12月內科住院病人共615人為樣本，收集其住院前11個月西醫門、住診就醫資料及住院後1年存活日期及狀態，參考Charlson制定權重方法產製合併症指數，檢討本研究與Charlson合併症指數對病人存活情形解釋力之差異。結果：同病人僅一種Charlson合併症疾病分類佔37.36%、同時有二種分類佔30.86%、同時有三種分類佔18.18%、同時有四種以上分類佔13.6%。以Charlson原始加權方式可解釋存活月數變異為6.48%；而本研究加權值方式可解釋存活月數變異為9.22%。結論：本研究之加權值可解釋病人存活月數之變異高於原始Charlson合併症指數，其中癌症無論本研究或Charlson之合併症疾病加權方式均為被加權的對象，若有此合併症疾病，會加重就醫時的病情，影響後續治療。

Objectives: The goal of this study is to adapt the Charlson Index, a measure that takes into account the number and severity of comorbid illnessnes, into a comorbidity index suitable for use in the health care system in Taiwan. Using data from the National Health Insurance Research Database (NHRID), this study examines the effectiveness of various comorbidity indices. Furthermore, the study attempts to develop a weighted comorbidity index suitable for use by the national health care system. Methods: Samples of inpatients hospitalized as of December 2001 were the subjects of the study. Individual data on the number of hospital visits within 11 months prior to hospitalization and the inpatient status after hospitalization were collected. A weighted Charlson comorbidity index was proposed. Next, we compared the effectiveness of the Charlson Index with the weighted Charlson index developed in our study. Results: According to the Cox's regression model, the weighted Charlson Index can explain 6.48% of variability in inpatient status, whereas our approach explains 9.22% of the variability. Conclusions: More variability in inpatient status can be explained by our weighted method than the CCI. In future computations of comorbidity index, one should consider using the weighted index developed in our study.

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