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Epidemiology

Poster Session 1

(201) Digital health utilization during pregnancy and the likelihood of preterm birth

Tuesday, February 13, 2024

10:30 AM – 12:00 PM

Location: Prince George's Exhibit Hall CDE, Lower Atrium Level

Primary & Presenting Author(s)

AB

Alison Brinson, MSPH

Maven Clinic
New York, NY, United States

Coauthor(s)

HJ

Hannah R. Jahnke, PhD

Maven Clinic
New York, NY, United States
NH

Natalie Henrich, MPH, PhD

Maven Clinic
New York, NY, United States
SK

Smriti Karwa, MPH

Maven Clinic
New York, NY, United States
CM

Christa Moss, PhD

Maven Clinic
New York, NY, United States
NS

Neel Shah, MD

Maven Clinic
New York, NY, United States

Objective: Research suggests interventions to reduce rates of preterm birth should be multifaceted. Maven, a comprehensive digital platform for women’s and family health, offers continuous access to virtual providers, patient education, and care coordination. This analysis explored the association between Maven use and odds of preterm birth among a sample of nulliparous, low-risk individuals.

Study Design: Data for this retrospective analysis came from 3491 low-risk pregnant Maven users who gave birth between 1/1/2020 and 9/19/2022. The sample excluded parous users, and users pregnant with multiple gestation, conceived with fertility treatment, or reported cigarette, drug, or alcohol use during pregnancy. Chi-square and Fisher’s exact tests compared characteristics between users who developed gestational conditions and users who did not. Adjusted multivariable logistic regression models estimated the association between the number of hours of Maven use and odds of preterm birth, stratified by presence of gestational conditions.

Results: Compared to those without gestational conditions, individuals who developed gestational conditions were more likely to have a preterm birth (8.7% vs. 3.4%; p< 0.001). For every 1 hour of Maven use, users experienced a 2% reduction in their odds of experiencing a preterm birth [AOR (95% CI) = 0.98 (0.95, 0.998), p = 0.043]. Adjusted models revealed that among individuals who developed gestational conditions, every 1 hour increase in Maven use was associated with a 5% reduction in the odds of experiencing a preterm birth [AOR (95% CI) = 0.95 (0.91, 0.99), p = 0.037] (Table 1). Among individuals who did not develop gestational conditions, there was no statistically significant association between use and preterm birth.

Conclusion: Among those who developed gestational conditions, increased use of a digital health platform was associated with a decreased likelihood of preterm birth. A digital health platform that provides continuous care coordination, access to providers, and educational information has the potential to support disease management and reduce preterm births.