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Predicting Preterm Birth Among Women Screened by North Carolina’s Pregnancy Medical Home Program

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Abstract

Objective

To determine which combination of risk factors from Community Care of North Carolina’s (CCNC) Pregnancy Medical Home (PMH) risk screening form was most predictive of preterm birth (PTB) by parity and race/ethnicity.

Methods

This retrospective cohort included pregnant Medicaid patients screened by the PMH program before 24 weeks gestation who delivered a live birth in North Carolina between September 2011–September 2012 (N = 15,428). Data came from CCNC’s Case Management Information System, Medicaid claims, and birth certificates. Logistic regression with backward stepwise elimination was used to arrive at the final models. To internally validate the predictive model, we used bootstrapping techniques.

Results

The prevalence of PTB was 11 %. Multifetal gestation, a previous PTB, cervical insufficiency, diabetes, renal disease, and hypertension were the strongest risk factors with odds ratios ranging from 2.34 to 10.78. Non-Hispanic black race, underweight, smoking during pregnancy, asthma, other chronic conditions, nulliparity, and a history of a low birth weight infant or fetal death/second trimester loss were additional predictors in the final predictive model. About half of the risk factors prioritized by the PMH program remained in our final model (ROC = 0.66). The odds of PTB associated with food insecurity and obesity differed by parity. The influence of unsafe or unstable housing and short interpregnancy interval on PTB differed by race/ethnicity.

Conclusions

Evaluation of the PMH risk screen provides insight to ensure women at highest risk are prioritized for care management. Using multiple data sources, salient risk factors for PTB were identified, allowing for better-targeted approaches for PTB prevention.

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Acknowledgments

This research received support from the Population Research Training Grant (T32 HD007168) and the Population Research Infrastructure Program (R24 HD050924) awarded to the Carolina Population Center at The University of North Carolina at Chapel Hill by the Eunice Kennedy Shriver National Institute of Child Health and Human Development. Funding was also provided by and the University of North Carolina, Chapel Hill Dissertation Completion Award and the Health Resources and Services Administration (HRSA) of the US Department of Health and Human Services (HHS) under training Grant No. T03MC07643. This information or content and conclusions are those of the author and should not be construed as the official position or policy of, nor should any endorsements be inferred by HRSA, HHS or the U.S. Government. Special thanks to Jill Ruppenkamp, Analytics Manager at Community Care of North Carolina, for pulling the data and providing technical assistance.

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Authors and Affiliations

  1. Department of Maternal and Child Health, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Campus Box #8120, Chapel Hill, NC, 27599-8120, USA

    Christine M. Tucker & Carolyn Tucker Halpern

  2. Carolina Population Center, 206 W. Franklin St., Chapel Hill, NC, 27516, USA

    Christine M. Tucker, Amy H. Herring & Carolyn Tucker Halpern

  3. Community Care of North Carolina, 2300 Rexwoods Drive, Suite 100, Raleigh, NC, 27607, USA

    Kate Berrien

  4. Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, School of Medicine, University of North Carolina at Chapel Hill, 101 Manning Drive, Chapel Hill, NC, 27514, USA

    M. Kathryn Menard

  5. Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Campus Box #7420, Chapel Hill, NC, 27599-7420, USA

    Amy H. Herring

  6. Department of Epidemiology and Maternal and Child Health, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Campus Box #7435, Chapel Hill, NC, 27599-7435, USA

    Julie Daniels

  7. Department of Maternal and Child Health, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Campus Box #7445, Chapel Hill, NC, 27599-7445, USA

    Diane L. Rowley

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  1. Christine M. Tucker
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  3. M. Kathryn Menard
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Correspondence to Kate Berrien.

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Tucker, C.M., Berrien, K., Menard, M.K. et al. Predicting Preterm Birth Among Women Screened by North Carolina’s Pregnancy Medical Home Program. Matern Child Health J 19, 2438–2452 (2015). https://doi.org/10.1007/s10995-015-1763-5

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  • DOI: https://doi.org/10.1007/s10995-015-1763-5

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