• Xiao Wang, Luyu Xie, Yolande M Pengetnze, Weiwei Ouyang, Hannah K Ligon, Donna I Persaud, Sarah E Messiah, and Barry Lachman.
• Parkland Center for Clinical Innovation, 8435 Stemmons Fwy, Ste 1150, Dallas, TX 75247. Email: yolande.pengetnze@pccinnovation.org.
• Am J Manag Care. 2021 May 1; 27 (5): e145-e151.

ObjectivesTo develop and prospectively validate a novel model incorporating claims and community-level socioeconomic data to predict preterm birth at scale among pregnant Medicaid women with no history of preterm birth (PTB).Study DesignA longitudinal Texas Medicaid cohort study, with 2-year retrospective model building (October 2015-October 2017) and a 1-year prospective model validation phase (January 2018-December 2018).MethodsInclusion criteria were females aged 11 to 55 years with at least 1 live singleton birth and no history of PTB. The primary outcome was live singleton birth earlier than 35 weeks. Covariates were medical/mental/behavioral comorbidities, obstetric history, sociodemographic characteristics, and health services utilization. Of multiple models built, the most parsimonious was selected to classify pregnancies as very high, high, medium, and low risk. Model performance was evaluated using positive predictive value (PPV), sensitivity, case identification ratio (1 / PPV), and timing of prediction.ResultsThe model was built on 6689 pregnancies and validated on 7855 pregnancies. PTB rate earlier than 35 weeks was approximately 3.3%. Significant risk predictors included prenatal visit attendance, insurance gap days, and medical/obstetrical comorbidities. Model PPV was approximately 4-fold higher for very high-risk women (14.7%) vs cohort (3.3%) and so was the case identification ratio (1:7 vs 1:30, respectively). Sensitivity was good, with 57% of PTBs classified as medium risk or higher. Timing of prediction was clinically relevant, with more than 80% of PTBs risk stratified before 24 weeks.ConclusionsWe report a novel PTB prediction model among pregnant Medicaid women without PTB history, which is timely, accurate, practical, and scalable. We leverage Medicaid and community data readily accessible by Medicaid plans to support population-level interventions to prevent PTBs.

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