Measuring Childbirth Outcomes Using Administrative and Birth Certificate Data
Measuring Childbirth Outcomes Using Administrative and Birth Certificate Data
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DOI：
10.1097/aln.0000000000002759
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发表时间：
2019-08-01
期刊：
影响因子：
8.8
通讯作者：
Dick, Andrew W.
中科院分区：
文献类型：
--
作者：
Glance, Laurent G.;Hasley, Steve;Dick, Andrew W.
编辑的观点我们已经知道的关于这个主题分娩期间和分娩后的孕产妇并发症在医院之间表现出很大的差异国家报告系统在定义医院产科护理质量时没有整合孕产妇和新生儿结局本文告诉我们的是新的管理数据可用于计算医院级别的风险调整孕产妇，新生儿，产妇和新生儿医院的绩效相关性较差，这表明复合绩效指标还必须分别报告产妇和新生儿的基本绩效。在美国，与怀孕有关的死亡和严重的产妇并发症的数量继续上升，美国医院的产科护理质量参差不齐。向医院提供绩效反馈可能有助于降低母亲及其新生儿严重并发症的发生率。本研究的目的是根据行政管理和出生证明数据，制定一种经风险调整的重度孕产妇发病率和重度新生儿发病率综合指标。方法：本研究使用来自加州的关联行政数据和出生证明数据进行。使用2011年数据开发了重度孕产妇发病率和重度新生儿发病率的分层逻辑回归预测模型，并使用2012年数据进行了验证。使用重度孕产妇发病率和重度新生儿发病率的风险标准化率的几何平均值计算复合指标。结果：该研究基于2011年和2012年的883，121例产科分娩。重度孕产妇发病率为1.53%，重度新生儿发病率为3.67%。严重的孕产妇发病率模型和严重的新生儿模型表现出可接受的歧视和校准水平。医院风险调整的严重孕产妇发病率与医院严重新生儿发病率相关性较差（组内相关系数为0.016）。基于综合指标的医院排名与基于孕产妇指标或新生儿指标的医院排名具有中等水平的一致性（Kappa统计值分别为0.49和0.60）。然而，10%的医院被归类为平均使用的综合措施有低于平均水平的产妇结局，20%的医院被归类为平均使用的综合措施有低于平均水平的新生儿结局。结论：孕产妇和新生儿的结果应联合报告，因为孕产妇发病率和新生儿发病率的医院相关性较差。这可以通过使用分娩综合措施以及产妇和新生儿结果的单独措施来实现。
Editor's PerspectiveWhat We Already Know about This Topic Maternal complications during and after childbirth demonstrate wide variation across hospitals National reporting systems do not integrate maternal and newborn outcomes when defining hospital obstetric care quality What This Article Tells Us That Is New Administrative data can be used to calculate hospital-level risk-adjusted maternal, newborn, and composite maternal-newborn performance Maternal and newborn hospital performance were poorly correlated, suggesting that composite performance measures must also report underlying maternal and newborn performance separately Background: The number of pregnancy-related deaths and severe maternal complications continues to rise in the United States, and the quality of obstetrical care across U.S. hospitals is uneven. Providing hospitals with performance feedback may help reduce the rates of severe complications in mothers and their newborns. The aim of this study was to develop a risk-adjusted composite measure of severe maternal morbidity and severe newborn morbidity based on administrative and birth certificate data. Methods: This study was conducted using linked administrative data and birth certificate data from California. Hierarchical logistic regression prediction models for severe maternal morbidity and severe newborn morbidity were developed using 2011 data and validated using 2012 data. The composite metric was calculated using the geometric mean of the risk-standardized rates of severe maternal morbidity and severe newborn morbidity. Results: The study was based on 883,121 obstetric deliveries in 2011 and 2012. The rates of severe maternal morbidity and severe newborn morbidity were 1.53% and 3.67%, respectively. Both the severe maternal morbidity model and the severe newborn models exhibited acceptable levels of discrimination and calibration. Hospital risk-adjusted rates of severe maternal morbidity were poorly correlated with hospital rates of severe newborn morbidity (intraclass correlation coefficient, 0.016). Hospital rankings based on the composite measure exhibited moderate levels of agreement with hospital rankings based either on the maternal measure or the newborn measure (kappa statistic 0.49 and 0.60, respectively.) However, 10% of hospitals classified as average using the composite measure had below-average maternal outcomes, and 20% of hospitals classified as average using the composite measure had below-average newborn outcomes. Conclusions: Maternal and newborn outcomes should be jointly reported because hospital rates of maternal morbidity and newborn morbidity are poorly correlated. This can be done using a childbirth composite measure alongside separate measures of maternal and newborn outcomes.