Predictive Models for Very Preterm Birth: Developing a Point-of-Care Tool.

OBJECTIVE: The objective of this study was to create three point-of-care predictive models for very preterm birth using variables available at three different time points: prior to pregnancy, at the end of the first trimester, and mid-pregnancy. STUDY DESIGN: This is a retrospective cohort study of 359,396 Ohio Medicaid mothers from 2008 to 2015. The last baby for each mother was included in the final dataset. Births prior to 22 weeks were excluded. Multivariable logistic regression was used to create three models. These models were validated on a cohort that was set aside and not part of the model development. The main outcome measure was birth prior to 32 weeks. RESULTS: The final dataset contained 359,396 live births with 6,516 (1.81%) very preterm births. All models had excellent calibration. Goodness-of-fit tests suggested strong agreement between the probabilities estimated by the model and the actual outcome experience in the data. The mid-pregnancy model had acceptable discrimination with an area under the receiver operator characteristic curve of approximately 0.75 in both the developmental and validation datasets. CONCLUSION: Using data from a large Ohio Medicaid cohort we developed point-of-care predictive models that could be used before pregnancy, after the first trimester, and in mid-pregnancy to estimate the probability of very preterm birth. Future work is needed to determine how the calculator could be used to target interventions to prevent very preterm birth. KEY POINTS: · We developed predictive models for very preterm birth.. · All models showed excellent calibration.. · The models were integrated into a risk calculator..

Using Telehealth Approaches to Address Social Determinants of Health and Improve Pregnancy and Postpartum Outcomes.

Telehealth has expanded its reach significantly since its inception due to the advances in technology over the last few decades. Social determinants of health (SDOH) negatively impact the health of pregnant and postpartum women and need to be considered when deploying telehealth strategies. In this article, we describe telehealth modalities and their application to improve the SDOH that impact pregnancy and postpartum outcomes. Physicians and patients alike report satisfaction with telehealth as it improves access to education, disease monitoring, specialty care, prenatal and postpartum care. Ten years ago, we developed a program, Moms2B, to eliminate disparities in pregnancy outcomes for underserved women. Using a case study, we describe how Moms2B, devoted to improve the SDOH for pregnant women, transitioned from an in-person to a virtual format. Telehealth benefited women before the recent coronavirus disease 2019 pandemic and increasingly after emergency authorizations has allowed telehealth to flourish.