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  3. クレームの時代における心臓血管健康結果の研究 データ:心臓血管健康研究
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  3. クレームの時代における心臓血管健康結果の研究 データ:心臓血管健康研究

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クレームの時代における心臓血管健康結果の研究 データ:心臓血管健康研究

Bruce M Psaty1, Joseph A Delaney2, Alice M Arnold2

  • 1From Cardiovascular Health Research Unit, Department of Medicine (B.M.P.), Department of Epidemiology (B.M.P., J.A.D., S.R.H.), Department of Health Services (B.M.P.), Department of Biostatistics (A.M.A., B.M.), Department of Global Health (A.L.F.), Department of Family Medicine (A.L.F.), and Department of Neurology (W.T.L.), University of Washington, Seattle; Group Health Research Institute, Group Health Cooperative, Seattle, WA (B.M.P., S.R.H.); Department of Medicine, Duke University, Durham, NC (L.H.C.); Department of Epidemiology, University of Pittsburgh, PA (D.I., L.H.K.); and Department of Medicine, University of Maryland, Baltimore (J.S.G.). psaty@u.washington.edu.

Circulation
|November 6, 2015

PubMed で要約を見る

まとめ
この要約は機械生成です。

臨床的アウトカムを定義するために,行政上のクレームデータから診断コードを使用すると,特にプライマリ診断に限定すると,イベント率を過小評価します. この方法は,イベント以外の入院も含み,複合エンドポイントを作成します.

キーワード:
流行病学について心不全発生率心筋梗塞ストローク

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科学分野:

  • 心血管疾患の疫学
  • 医療サービス研究
  • バイオ統計学

背景:

  • 行政上の主張のデータは,臨床的結果の評価のためにますます利用されています.
  • クレームデータからの診断コードは,健康上の出来事を特定するための便利だが,不正確な方法である.
  • 判断された出来事に対して主張に基づく結果を検証することは,信頼性の高い研究にとって極めて重要です.

研究 の 目的:

  • 断言に基づく診断コードの精度と,心血管疾患のアウトカムを定義するための判断されたイベントを比較する.
  • 事故発生率とリスク因子の関連性を,さまざまな損害賠償データ分析方法を用いて評価する.
  • コード位置 (プライマリと任意の) が結果確認に与える影響を評価する.

主な方法:

  • 心血管健康研究 (CHS) のデータを活用した.
  • 心筋梗塞 (MI),脳卒中,心不全をCHS判定イベント (CHS[adj]),国際疾病分類,第9版コードをプライマリポジション (CMS[1st]),および任意のポジション (CMS[any]) で定義する.
  • 3つの定義におけるイベント率と心血管疾患のリスク因子の関連を比較した.

主要な成果:

  • クレームベースの方法は高いポジティブな予測値を示したが,イベントを特定するための感度は低い.
  • CMS[1st]方法は,CHS[adj]と比較してイベント率を著しく過小評価した (例えば,MI発生率:1000人当たり8.6対14.9).
  • 心血管疾患の危険因子関連は,一般的に3つのイベント定義方法において一致した.

    • 結論:

    • 診断コードをクレームデータの中での主要な位置に制限することは,心血管疾患の発生率を過小評価することにつながります.
    • クレームに基づくイベントデータは,実際のイベントと誤った非イベント入院を含む複合エンドポイントとして機能することができます.
    • クリニカルアウトカム研究のためにクレームデータを使用する際には,方法論を慎重に検討する必要があります.