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Accuracy of the Adverse Outcome Index: An Obstetrical Quality Measure

机译:不良结果指数的准确性:一种产科质量测量

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Article-at-a-Glance Background: In obstetrics, a nationally accepted set of quality indicators for patient safety was not available in the United States until the development of a set of 10 adverse outcome measures-the Adverse Outcome Index (AOI). The National Perinatal Information Center (NPIC) developed hospital discharge data-based algorithms combined with a small set of supplemental patient data for calculation of the AOI. A study was conducted to determine the specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV) of the AOI by using the National Perinatal Information Center (NPIC) algorithm. Methods: A retrospective chart review of 4,252 obstetrical and neonatal charts from 2003 through 2007 was performed. NPIC definitions were compared with the "gold standard"-chart review. Results: A total of 229 deliveries among the 4,000 randomly selected charts had at least one adverse outcome, reflecting an AOI of 5.7%. For detection of the 10 adverse outcomes within the AOI, the overall sensitivity of the AOI was 81.7%, specificity was 98.2%, PPV was 86.3%, and NPV was 97.4%. The Kappa value for agreement between the coded charts and the chart review was 0.82 (standard deviation = 0.01, 95% confidence interval [CI] = 0.80-0.85), which is considered very good. Discussion: The AOI is highly reliant on accurate coding and provider documentation and requires validation with manual chart review. Concurrent chart review improves the accuracy of the AOI. Caution is advised when using the AOI as an exclusive measure of assessing obstetric quality because it may be heavily influenced by a single outcome measure; perineal laceration rates represented twice the frequency of all other outcomes combined. The AOI should be modified to better measure preventable adverse events and include a means of accounting for preexisting conditions.
机译:概述背景:在产科领域,直到制定了10项不良结果指标(不良结果指数)后,美国才获得一套全国公认的患者安全质量指标。国家围产期信息中心(NPIC)开发了基于医院出院数据的算法,并结合了少量的补充患者数据来计算AOI。通过使用国家围产期信息中心(NPIC)算法进行了一项研究,以确定AOI的特异性,敏感性,阳性预测值(PPV)和阴性预测值(NPV)。方法:回顾性分析了2003年至2007年的4252例产科和新生儿图。将NPIC定义与“金标准”图表比较进行了比较。结果:在4,000张随机选择的图表中,总共229项分娩至少有一项不良结果,反映了AOI为5.7%。为了检测AOI内的10个不良结局,AOI的总体敏感性为81.7%,特异性为98.2%,PPV为86.3%,NPV为97.4%。编码图表与图表审阅之间的一致性Kappa值为0.82(标准偏差= 0.01,95%置信区间[CI] = 0.80-0.85),被认为是非常好。讨论:AOI高度依赖准确的编码和提供者文档,并且需要通过手动图表审查进行验证。并发图表检查可提高AOI的准确性。在将AOI用作评估产科质量的排他性措施时,建议谨慎,因为它可能受单个结果指标的严重影响;会阴裂伤率是所有其他结局合并频率的两倍。应修改AOI,以更好地衡量可预防的不良事件,并包括一种对已有疾病进行核算的手段。

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  • 来源
    《Joint Commission Journal on Quality and Safety 》 |2015年第8期| 370-377| 共8页
  • 作者单位

    Department of Obstetrics and Gynecology, Madigan Army Medical Center, Ta-coma, Washington;

    Western Regional Medical Command, and Obstetrics and Gynecology Consultant to US Army Surgeon General, Joint Base Lewis-McChord, Washington, General Leonard Wood Army Community Hospital, Fort Leonard Wood, Missouri;

    Department of Obstetrics and Gynecology, Madigan Army Medical Center;

    Pediatrics Division of Neonatology, University of Washington School of Medicine, Seattle;

    Department of Obstetrics and Gynecology, Madigan Army Medical Center;

    Maternal-Fetal Medicine Fellowship, Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Madigan Army Medical Center;

    Uniformed Services University of the Health Sciences Simulation Center, US Army Central Simulation Committee, Uniformed Services of the Health Sciences, Bethesda, Maryland;

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