多重疾患測定のためのコア疾患セットを定義するための専門家コンセンサスの合成:ナラティブレビュー
Weihao Shao1, Zuolin Lu1, Xiaoxia Wei1
1School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Science progress
|February 10, 2026
まとめ
多重疾患測定の一貫性のなさは、研究の障壁となっている。この研究は、標準化された測定のための105の疾患のコアセットを特定し、研究の比較可能性のための柔軟なフレームワークを提案する。
科学分野:
- 医療サービス研究
- 疫学
- 臨床情報学
背景:
- 多重疾患測定の一貫性のなさは、比較研究およびエビデンスの統合を複雑にします。
- 多重疾患研究の信頼性と比較可能性を向上させるためには、標準化されたアプローチが必要です。
研究 の 目的:
- 多重疾患測定のための基本的なコア疾患セットを特定すること。
- 研究における多重疾患測定の標準化のための実用的なフレームワークを開発すること。
主な方法:
- 3つの主要なデータベースの体系的なスコーピング検索によって情報を得たナラティブレビュー。
- 一貫して推奨される疾患カテゴリを特定するための正式な専門家コンセンサス研究の合成。
主要な成果:
- 国際疾病分類第10版(ICD-10)の3桁レベルで105の疾患カテゴリのコアセットが特定されました。
- これらの疾患は10の主要な臨床領域にまたがり、ICD-10およびICD-11コードにマッピングされました。
結論:
- 多重疾患測定のための基本的なコンセンサスが出現しつつあります。
- 「コアプラスカスタマイゼーション」フレームワークは、研究のためのエビデンスに基づいた適応可能な出発点を提供し、測定の標準化を促進します。
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