To develop and validate a maternal comorbidity index to predict severe maternal morbidity, defined as the occurrence of acute maternal end-organ injury, or mortality.
Data were derived from the Medicaid Analytic eXtract for the years 2000–2007. The primary outcome was defined as the occurrence of maternal end-organ injury or death during the delivery hospitalization through 30 days postpartum. The data set was randomly divided into a two-thirds development cohort and a one-third validation cohort. Using the development cohort, a logistic regression model predicting the primary outcome was created using a stepwise selection algorithm that included 24-candidate comorbid conditions and maternal age. Each of the conditions included in the final model was assigned a weight based on its beta coefficient, and these were used to calculate a maternal comorbidity index.
The cohort included 854,823 completed pregnancies, of which 9,901 (1.2%) were complicated by the primary study outcome. The derived score included 20 maternal conditions and maternal age. For each point increase in the score, the odds ratio for the primary outcome was 1.37 (95% confidence interval [CI] 1.35–1.39). The c-statistic for this model was 0.657 (95% CI 0.647–0.666). The derived score performed significantly better than available comorbidity indices in predicting maternal morbidity and mortality.
This new maternal comorbidity index provides a simple measure for summarizing the burden of maternal illness for use in the conduct of epidemiologic, health services, and comparative effectiveness research.
A developed and validated comorbidity index that predicts maternal morbidity performs in a superior fashion compared with existing comorbidity scores.
Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, the Department of Anesthesiology, Critical Care, and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, and the Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts; the Department of Anesthesiology, University of Michigan Health System, Ann Arbor, Michigan; and the Division of Reproductive Health, Centers for Disease Control and Prevention, Atlanta, Georgia.
Corresponding author: Brian T. Bateman, MD, MSc, Division of Pharmacoepidemiology & Pharmacoeconomics, Department of Medicine, Brigham & Women's Hospital, Division of Obstetric Anesthesia, Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, 1620 Tremont Street, Suite 3030, Boston, MA 02120; e-mail: firstname.lastname@example.org.
The Medicaid Analytic eXtract (MAX) pregnancy cohort was supported by the Agency for Healthcare Research and Quality (AHRQ) (Grant R01HS018533). Research reported in this publication was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health under Award Number K08HD075831 (B.T.B.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the Centers for Disease Control and Prevention.
The authors thank Helen Mogun for assistance with data analysis.
Financial Disclosure Dr. Hernandez-Diaz has consulted for Novartis, GSK-Biologics, and AstraZenaca for unrelated projects. The other authors did not report any potential conflicts of interest.