Tancredi Daniel J, Zrelak Patricia A, Utter Garth H, Geppert Jeffrey J, Romano Patrick S
Department of Pediatrics, University of California Davis, Sacramento, CA, USA.
Center for Healthcare Policy and Research, University of California Davis, Sacramento, CA, USA.
Perm J. 2025 Jun 16;29(2):54-63. doi: 10.7812/TPP/24.180. Epub 2025 May 7.
Little is known about how comprehensively the Agency for Healthcare Research and Quality's patient safety indicators (PSIs) capture true complications. Therefore, the authors sought to assess the PSIs' sensitivity using a novel sampling and analytic strategy tailored for unusual events to ensure adequate capture of false negative cases.
The authors retrospectively reviewed hospitalization records not flagged by 7 selected PSIs, oversampling those with specific diagnosis or procedure codes suggesting an unreported complication, with a special interest in PSI 09 (Postoperative Hemorrhage or Hematoma) and PSI 10 (Postoperative Physiologic and Metabolic Derangement). The authors evaluated data from 27 hospitals in 11 states between 2006 and 2009. For each PSI, the authors determined the negative predictive value (NPV), accounting for sampling weights, and used previous estimates of positive predictive value (PPV) and incidence to estimate sensitivity.
For PSI 09, 32 of 281 abstracted records (including 30 of 116 high-risk records) were falsely negative (NPV 99.73%; 97.5%, confidence interval [CI], 98.96-99.94); the estimated sensitivity was 40% (95% CI, 12-76). For PSI 10, 3 of 230 records (including 3 of 108 high-risk records) were falsely negative (NPV 99.92%; 97.5% CI, 99.28-99.99); the sensitivity was 53% (95% CI, 9-92). The estimated sensitivity of other PSIs varied (19%-100%).
The sensitivity of several Agency for Healthcare Research and Quality PSIs, estimated from a sample of hospitalizations enriched with records suggesting an unreported complication, varied widely. Although the 2-stage complex stratified sampling design (using weights based on sampling probabilities) allows estimation of the sensitivity of hospital outcome measures, large sample sizes are still required for unusual events.
对于医疗保健研究与质量局的患者安全指标(PSI)在多大程度上全面捕捉真正的并发症,人们了解甚少。因此,作者们试图采用一种针对异常事件量身定制的新颖抽样和分析策略来评估PSI的敏感性,以确保充分捕捉假阴性病例。
作者们回顾性审查了7个选定PSI未标记的住院记录,对那些具有特定诊断或程序代码提示未报告并发症的记录进行过度抽样,特别关注PSI 09(术后出血或血肿)和PSI 10(术后生理和代谢紊乱)。作者们评估了2006年至2009年期间11个州27家医院的数据。对于每个PSI,作者们确定了考虑抽样权重后的阴性预测值(NPV),并使用先前的阳性预测值(PPV)和发病率估计值来估计敏感性。
对于PSI 09,281份提取记录中有32份(包括116份高风险记录中的30份)为假阴性(NPV 99.73%;97.5%置信区间[CI],98.96 - 99.94);估计敏感性为40%(95% CI,12 - 76)。对于PSI 10,230份记录中有3份(包括108份高风险记录中的3份)为假阴性(NPV 99.92%;97.5% CI,99.28 - 99.99);敏感性为53%(95% CI,9 - 92)。其他PSI的估计敏感性各不相同(19% - 100%)。
从富含提示未报告并发症记录的住院样本中估计,医疗保健研究与质量局的几个PSI的敏感性差异很大。尽管两阶段复杂分层抽样设计(使用基于抽样概率权重)允许估计医院结局指标的敏感性,但对于异常事件仍需要大样本量。