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公元1980至1997年本國衛生署死因資料庫準確性之確認與補正

Verification and Correction of Error for Death Registration Data of the Department of Health R.O.C. Between 1980 and 1997

摘要


目標:目前國內將死亡診斷書建立成死因資料庫有衛生署及內政部兩個單位。本研究之目的係使用內政部死因資料檔中正確及完整部份來補正衛生署自公元1985至1997年死亡之身分證字號及戶政資料,同時填補衛生署自公元1980至1997年教育及村里兩變項及衛生署自公元1980至1984年之身分證字號,以作為未來相關研究之參考與應用。方法:首先將兩死因資料庫內身分證字號及戶政資料皆相同之個案,先填補衛生署死因資料庫之教育及村里之資料,然後把不可連結之部分以身分證字號或戶政資料各做連結碼,來補正衛生署死因資料庫內缺漏或錯誤之戶政資料或身分證字,及填補教育及村里之資料。同時建立兩資料庫間互相無法連結之個案資料庫。結果:第一部分,自公元1980至1997年以身分證字號與戶政資料為連結碼,經由兩資料庫互連,可連結出1,259,600個個案。連結不上之個案利用身分證字號與戶政資料分別比對後,可補正衛生署之戶政資料有3,168個個案,身分證字號有33,036個個案。另外,兩資料庫可連結之部分,教育及村里變項補正百分比都達98%以上。第二部分,公元1980至1984年,主要填補衛生署身分證字號。以戶政資料包括出生年月日、死亡年月日、縣市代碼、鄉鎮代碼全部變項為連結碼可以填補身分證字號達88.83%。公元1980至1997年,兩資料庫未連結上之個案未作補正者,共有衛生署46,305個個案及內政部63,157個個案,可能是失去追蹤及延遲申報個案。結論:本研究結果可使世代研究及存活分析在使用衛生署的死因資料檔案範圍往前推至公元1980年;研究族群之區域分層只能切割到最小單位鄉鎮,但補正後可使之細分到村里。另外衛生署及內政部未連結上之個案可建立檔案作為延遲申報個案及失蹤建檔個案之參考,以便作為將來研究追蹤死亡個案之依據。

並列摘要


Objective: Both the Department of Health (DOH) and Ministry of Interior (MOI) of Taiwan have established a computerized death registry based on the death certificates of the dead in Taiwan during the past two decades. The purpose of this study is to verify the accuracy of the dataset of death registration for the DOH with the dataset from the MOL .Because the data of the DOH during 1980-84 lacked the identification number (ID no.), our second objective is to establish guidelines for replacing the missing ID no.. Method: Firstly, decedents in the two datasets linked by same ID no. and demography including dates of birth, death, and places of living between 1985 and 1997 were identified and codes of education and village taken from the MOI were filed in those of the DOH. Decedents that could only be linked by ID no. or demography between 1985 and 1997, were refiled the demography or ID no. after making sure of the correction in the MOI. Secondly, due to the lack of information of ID no. in the DOH for decedents between 1980 and 1984, we linked the two decedents with social demography including dates of birth and death, area codes of detailed address, and then imputed ID no. into dataset of the DOH based on dataset of the MOI. Result: There were 1,259,600 decedents identified from 1985-97 with completely the same ID no. and demographic data. After verification of the data, we refiled the missing demographic data for 3,168 subjects and the missing ID no. for 33,036 subjects into the dataset of the DOH. According to the study results, there were 0.0512% of total subjects with complete overlapping demographic data. Thus, after linking the two datasets with the same complete demographic data, we were able to refile 88.83% of the missing Ids for all the death certificate data of the DOH during 1980-84. There were 46,305 cases in the dataset of the DOH and 63,157 cases in that of the MOI during 1980-97, that were unlinkable. This was probably because they were lost track of or there was a delay in registration. Conclusion: This study corrected many errors, filled in ID no. for 1980-84, and imputed information of education and village into the death registration dataset of the DOH. This can be useful for future studies. Beside, the unlinkable cases in the datasets of the DOH and MOI were identified and a separate dataset files for future usage was built up.

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