免疫情報システムにおける欠落している患者の人口統計を扱うための複数の推定方法の比較:遡及的なコホート研究
Sara Brown1, Ousswa Kudia1, Kaye Kleine1
1Scientific Services - Analytics, Scientific Technologies Corporation (United States), 411 S 1st St, Phoenix, AZ, 85004, United States, 1 480-745-8500.
JMIR public health and surveillance
|August 26, 2025
まとめ
MICEやmiceforestのような複数の推定方法は,免疫監視で欠けている人種/民族データを効果的に管理し,人口統計を保存し,公衆衛生の介入の正確性を向上させます. Miceforestは大きなデータセットに対して 優れた計算効率を提供します
科学分野:
- 公衆衛生の監視
- バイオ統計学
- 医療情報学
背景:
- 予防接種情報システム (IIS) と監視データは公衆衛生にとって極めて重要ですが,しばしば欠けているデータに苦しんでおり,ワクチン接種率の評価に偏見をもたらし,健康格差に対処する努力を妨げています.
- ワクチンの接種率を正確に評価することは,特に不平等を減らすことを目的として,効果的な公衆衛生プログラムと介入に不可欠です.
研究 の 目的:
- 大規模な公衆衛生監視データセット内の欠落した人種と民族のデータを処理する3つの複数の帰算方法の性能を評価する.
- 人口分布を保持する能力,計算効率,および人種/民族とインフルエンザワクチン接種状態の関連性を評価する能力に基づいてこれらの推定方法を比較する.
主な方法:
- 遡及的なコホート研究では,ウェストバージニア予防接種情報システム (N=2,302,036) の2021-2022年のインフルエンザワクチン接種と人口統計データを分析し,人種 (15%) と民族 (34%) の有意な欠落がありました.
- 3つの複数の推定技術 (MICE,Iterative-Imputer,miceforest) を適用して,それぞれ15の推定データセットを生成した.
- 性能は,G統計と確率比統計を用いた人口分布保存,計算効率,空間クラスタリングパターンの比較によって評価された.
主要な成果:
- すべての推定方法は,人種を推定するために有意な空間的クラスタリングを示した. MICEとmiceforestは,Iterative-Imputerと比較して,人口比例分布の優れた保存を示した.
- MICEは14時間,Iterative-Imputerは2分,miceforestは15分かかりました.
- 推算後の分析では,分層化されたインフルエンザワクチン接種率の減少 (0. 87% - 18%) と26%から19%への全体的な減少が示され,見積もりに欠けているデータの影響が強調されました.
結論:
- MICEとmiceforestは,欠けている人口データを割り当てるための信頼できる方法を提供し,Iterative-Imputerよりもバイアスをより効果的に軽減します. Miceforestは,特に大規模なデータセットでは,クラウドベースの処理を通じて,計算効率を向上させます.
- 計算方法の選択は研究結果に大きく影響し,慎重に選択する必要性を強調しています.
- 推定ワクチン接種率の大幅な減少は 欠けているデータが本当の格差を 隠していることを示しています 医療の公平性評価を改善し,公衆衛生の介入に指針を定めるために,定期的な推算方法の適用が推奨されています.
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