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本文引用的文献

1
Validity of the Agency for Health Care Research and Quality Patient Safety Indicators and the Centers for Medicare and Medicaid Hospital-acquired Conditions: A Systematic Review and Meta-Analysis.医疗保健研究与质量机构患者安全指标及医疗保险与医疗补助服务中心医院获得性疾病的有效性:一项系统评价与荟萃分析
Med Care. 2016 Dec;54(12):1105-1111. doi: 10.1097/MLR.0000000000000550.
2
How Accurate is the AHRQ Patient Safety Indicator for Hospital-Acquired Pressure Ulcer in a National Sample of Records?在全国记录样本中,医疗保健研究与质量局(AHRQ)的医院获得性压疮患者安全指标的准确性如何?
J Healthc Qual. 2015 Sep-Oct;37(5):287-97. doi: 10.1111/jhq.12052.
3
Detecting postoperative hemorrhage or hematoma from administrative data: the performance of the AHRQ Patient Safety Indicator.从行政数据中检测术后出血或血肿:AHRQ 患者安全指标的性能。
Surgery. 2013 Nov;154(5):1117-25. doi: 10.1016/j.surg.2013.04.062. Epub 2013 Sep 26.
4
Validity of the AHRQ patient safety indicator for postoperative physiologic and metabolic derangement based on a national sample of medical records.基于全国范围内的病历样本,评估 AHRQ 术后生理和代谢紊乱患者安全指标的有效性。
Med Care. 2013 Sep;51(9):806-11. doi: 10.1097/MLR.0b013e31829c8b91.
5
Improved coding of postoperative deep vein thrombosis and pulmonary embolism in administrative data (AHRQ Patient Safety Indicator 12) after introduction of new ICD-9-CM diagnosis codes.引入新的ICD-9-CM诊断编码后,行政数据中术后深静脉血栓形成和肺栓塞编码的改进(AHRQ患者安全指标12)
Med Care. 2015 May;53(5):e37-40. doi: 10.1097/MLR.0b013e318287d59e.
6
Test result-based sampling: an efficient design for estimating the accuracy of patient safety indicators.基于测试结果的抽样:一种用于估计患者安全指标准确性的有效设计。
Med Decis Making. 2012 Jan-Feb;32(1):E1-12. doi: 10.1177/0272989X11426176. Epub 2011 Nov 7.
7
Validating the patient safety indicators in the Veterans Health Administration: do they accurately identify true safety events?验证退伍军人健康管理局的患者安全指标:它们是否能准确识别真实的安全事件?
Med Care. 2012 Jan;50(1):74-85. doi: 10.1097/MLR.0b013e3182293edf.
8
A review of patient safety measures based on routinely collected hospital data.基于常规收集的医院数据对患者安全措施进行的综述。
Am J Med Qual. 2012 Mar-Apr;27(2):154-69. doi: 10.1177/1062860611414697. Epub 2011 Sep 6.
9
Automated identification of postoperative complications within an electronic medical record using natural language processing.利用自然语言处理技术在电子病历中自动识别术后并发症。
JAMA. 2011 Aug 24;306(8):848-55. doi: 10.1001/jama.2011.1204.
10
Positive predictive value of the Agency for Healthcare Research and Quality Patient Safety Indicator for central line-related bloodstream infection ("selected infections due to medical care").医疗保健研究与质量局患者安全指标对中心静脉导管相关血流感染(“因医疗护理导致的特定感染”)的阳性预测值。
J Healthc Qual. 2011 Mar-Apr;33(2):29-36. doi: 10.1111/j.1945-1474.2010.00114.x. Epub 2011 Jan 11.

评估医疗保健研究与质量局患者安全指标敏感性的方法学技术

Methodological Techniques to Estimate the Sensitivity of the Agency for Healthcare Research and Quality Patient Safety Indicators.

作者信息

Tancredi Daniel J, Zrelak Patricia A, Utter Garth H, Geppert Jeffrey J, Romano Patrick S

机构信息

Department of Pediatrics, University of California Davis, Sacramento, CA, USA.

Center for Healthcare Policy and Research, University of California Davis, Sacramento, CA, USA.

出版信息

Perm J. 2025 Jun 16;29(2):54-63. doi: 10.7812/TPP/24.180. Epub 2025 May 7.

DOI:10.7812/TPP/24.180
PMID:40329637
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12168039/
Abstract

BACKGROUND

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.

METHODS

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.

RESULTS

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%).

CONCLUSIONS

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.

摘要

背景

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。

方法

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。

结果

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%)。

结论

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。