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博士論文
国立国会図書館館内限定公開
収録元データベースで確認する
国立国会図書館デジタルコレクション
デジタルデータあり(日本生体医工学会)
Development of a New Method to Trace Patient Data Using the National Database in Japan.
- 国立国会図書館永続的識別子
- info:ndljp/pid/12661654
国立国会図書館での利用に関する注記
資料に関する注記
一般注記:
- type:ThesisThe National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB) is a comprehensive database containing health ...
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デジタル
- 資料種別
- 博士論文
- 著者・編者
- Myojin, TomoyaNoda, TatsuyaKubo, ShinichiroNishioka, YuichiHigashino, TsuneyukiImamura, Tomoaki
- 出版事項
- 出版年月日等
- 202211
- 出版年(W3CDTF)
- 2022
- 並列タイトル等
- NDBを用いた新たな患者追跡手法の開発
- 授与機関名
- 奈良県立医科大学
- 授与年月日
- 2022-12-22
- 授与年月日(W3CDTF)
- 2022-12-22
- 報告番号
- 甲第854号
- 学位
- 博士(医学)
- 本文の言語コード
- eng
- 対象利用者
- 一般
- 一般注記
- type:ThesisThe National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB) is a comprehensive database containing health insurance claim information. The structure of the NDB complicates long-term cohorts for two main reasons. First, the NDB data are stored on a per-claim basis. Second, the NDB is a billing-focused record structure. Therefore, the objective of this study was to use ID0 to modify the data structure to allow for long-term cohorts, provided that the data volume is not increased and the runtime per data year is maintained within one month. The NDB uses two primary keys (ID1 and ID2) made from hash values that mask personally identifiable information. ID0 is our recently developed key from ID1 and ID2, which improves patient-matching efficiency with excellent long-term tracing performance. Our study used claim data with filing dates between April 2013 and March 2016 to trace hospitalizations of one month or longer, including outpatient care, in three steps. In Step 1, claims were transferred to a CD-record format. As some diagnosis procedure combination (DPC) claim records contain a mixture of overlapping comprehensive and piece-rate data, we sorted and reorganized them. In Step 2, pharmacy and medical outpatient claims were integrated using the ID0 key, the medical institution code for issuing a prescription, and the prescription issue date. In Step 3, the transferred data were combined and converted from consecutive hospitalization days into sequences based on ID0, the medical institution code, and hospital ward classification. Consequently, the size of the originally extracted comma-separated variable dataset for three years (approximately 10.5 TB) was reduced to an approximately 6 TB main database file that was usable for processing. The process took approximately three months. With similar conventional methods, the data size was 30 times larger, and it took more than seven months to process a year's worth of data. In addition, to demonstrate the application of this method, we conducted a six-year mortality cohort for all Japanese citizens. Our technique makes it easy to perform follow-up and longitudinal cohort surveys while accurately tracing patient data in large-scale medical claims databases.博士(医学)・甲第854号・令和4年12月22日Copyright: ©2022 The Author(s). This is an openaccess article distributed under the terms of theCreative Commons BY 4.0 International (Attribution) License (https://creativecommons.org/licenses/by/4.0/legalcode), which permits theunrestricted distribution, reproduction and use of the article providedthe original source and authors are credited.identifier:Advanced Biomedical Engineering Vol.11 p.203-217 (2022)identifier:21875219identifier:http://ginmu.naramed-u.ac.jp/dspace/handle/10564/4083identifier:Advanced Biomedical Engineering, 11: 203-217
- 国立国会図書館永続的識別子
- info:ndljp/pid/12661654
- コレクション(共通)
- コレクション(障害者向け資料:レベル1)
- コレクション(個別)
- 国立国会図書館デジタルコレクション > デジタル化資料 > 博士論文
- 収集根拠
- 博士論文(自動収集)
- 受理日(W3CDTF)
- 2023-03-03T17:22:18+09:00
- 記録形式(IMT)
- application/pdf
- オンライン閲覧公開範囲
- 国立国会図書館内限定公開
- デジタル化資料送信
- 図書館・個人送信対象外
- 遠隔複写可否(NDL)
- 可
- 掲載誌(URI)
- 連携機関・データベース
- 国立国会図書館 : 国立国会図書館デジタルコレクション