MIHARI project, a preceding study of MID-NET, adverse event detection database of Ministry Health of Japan －Validation study of the signal detection of adverse events of drugs using export data from EMR and medical claim data

• Material Type: 博士論文
• Title: MIHARI project, a preceding study of MID-NET, adverse event detection database of Ministry Health of Japan －Validation study of the signal detection of adverse events of drugs using export data from EMR and medical claim data
• Author/Editor: 渡邊, 浩
• Author Heading: 渡邊, 浩
• Publication, Distribution, etc.: PLOS (Public Library of Science)
• Publication Date: 2021-09-08
• Publication Date (W3CDTF): 2021-09-08
• Alternative Title: 厚生労働省の有害事象検出データベースであるMID-NETの先行研究であるMIHARIプロジェクト －電子カルテからのデータと医療請求データを使用した薬物の有害事象の信号検出の検証研究
• Degree grantor/type: 浜松医科大学
• Date Granted: 2022-05-20
• Date Granted (W3CDTF): 2022-05-20
• Dissertation Number: 乙第588号
• Degree Type: 博士（医学）
• Text Language Code: eng
• Subject Heading: electronic medical records (EMR); post-marketing safety surveillance of drugs; SS-MIX2 Standardized Storage
• Target Audience: 一般
• Note (General): doctoral; 医学系研究科; We studied the effectiveness of the direct data collection from electronic medical records (EMR) when it is used for monitoring adverse drug events and also detection of already known adverse events. In this study, medical claim data and SS-MIX2 standardized storage data were used to identify four diseases (diabetes, dyslipidemia, hyperthyroidism, and acute renal failure) and the validity of the outcome definitions was evaluated by calculating positive predictive values (PPV). The maximum positive predictive value (PPV) for diabetes based on medical claim data was 40.7% and that based on prescription data from SS-MIX2 Standardized Storage was 44.7%. The PPV for dyslipidemia was 50% or higher under either of the conditions. The PPV for hyperthyroidism based on disease name data alone was 20?30%, but exceeded 60% when prescription data was included in the evaluation. Acute renal failure was evaluated using information from medical records in addition to the data. The PPV for acute renal failure based on the data of disease names and laboratory examination results was slightly higher at 53.7% and increased to 80?90% when patients who previously had a high serum creatinine (Cre) level were excluded. When defining a disease, it is important to include the condition specific to the disease; furthermore, it is very useful if laboratory examination results are also included. Therefore, the inclusion of laboratory examination results in the definitions, as in the present study, was considered very useful for the analysis of multi-center SS-MIX2 standardized storage data.
• Persistent ID (NDL): info:ndljp/pid/12694243; https://dl.ndl.go.jp/pid/12694243
• Collection: 障害者向け資料
• Collection (Materials For Handicapped People:1): テキストデータ
• Collection (particular): 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; https://dl.ndl.go.jp/collections/A00014
• Acquisition Basis: 博士論文（自動収集）
• Date Accepted (W3CDTF): 2023-03-07T16:07:55+09:00
• Format (IMT): application/pdf
• Access Restrictions: 国立国会図書館内限定公開
• Service for the Digitized Contents Transmission Service: 図書館・個人送信対象外
• Availability of remote photoduplication service: 可
• Periodical Title (URI): http://hdl.handle.net/10271/00004263; https://hama-med.repo.nii.ac.jp/records/4141
• Data Provider (Database): 国立国会図書館 : 国立国会図書館デジタルコレクション; https://dl.ndl.go.jp

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