Measuring Childbirth Outcomes Using Administrative and Birth Certificate Data. (August 2019)

• Record Type: Journal Article
• Authors: Glance, Laurent G.; Hasley, Steve; Glantz, J. Christopher; Stevens, Timothy P.; Faden, Eric; Kreso, Melissa A.; Pyne, Sonia G.; Wissler, Richard N.; Fichter, Jennifer; Gloff, Marjorie S.; Dick, Andrew W.
• Is Part Of: Anesthesiology. Volume 131:Number 2(2019)
• Publication Date: 2019-08
• Subjects: Anesthesiology -- Periodicals; Anesthetics -- Periodicals; Anesthesia -- Periodicals; 617.9605
• DOI: 10.1097/ALN.0000000000002759
• Languages: English
• ISSNs: 0003-3022

Abstract

Editor's Perspective: What 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 (κ 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. Abstract : 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.Supplemental Digital Content is available in the text.