Tracking Engagement with Remote Patient Monitoring in Prenatal Care and Detection of Preeclampsia: A Retrospective Review

<b>Introduction:</b> Mobile technology may enhance traditional prenatal care by supporting screening and patient compliance. Although prior studies report high satisfaction with mobile prenatal technologies, the impact of integrating remote patient monitoring (RPM) into routine workflows on clinical outcomes remains uncertain. This retrospective study assessed whether higher engagement with RPM via the Babyscripts™ digital health platform was associated with increased detection of preeclampsia (PEC). <b>Methods:</b> In this university-based obstetric practice, pregnant patients received the Babyscripts™ platform in addition to standard care. The platform enabled tracking of gestational weight gain and blood pressure and delivered scheduled education on symptoms and screening tests. Patients were included if they initiated RPM use before the end of the first trimester; those without available pregnancy outcomes were excluded. Chart reviews were performed using structured data forms by trained abstractors. RPM engagement was defined as the percentage of weeks with at least one remote blood pressure measurement. Outcomes included PEC and a composite of maternal complications. Multivariate logistic regression identified predictors of engagement. <b>Results:</b> A total of 823 patients were included: 28% identified as Black, 32% were Medicaid/Medicare recipients, 43% were over age 35, and 5% had a history of hypertension. Thirty-seven patients developed PEC or pregnancy-induced hypertension. Living in a distressed community and having at least one prior full-term pregnancy were associated with reduced engagement, with decreases of 7.9% (95% confidence interval [CI]: 1.2-14.6%) and 12.2% (95% CI: 5.2-19.1%), respectively. There was a nonsignificant trend toward increased detection of PEC with higher RPM engagement (odds ratio: 1.014, 95% CI: 0.999-1.846). <b>Conclusion:</b> Higher maternal age and first-time pregnancy were associated with increased RPM engagement, while living in a distressed community was linked to lower engagement. There was a nonsignificant positive association between RPM engagement and detection of PEC. Future studies should explore whether engagement with digital health platforms in prenatal care can modify risk factors for pregnancy complications.

Authors

Institutions

Publication Details

Journal
Telemedicine Journal and e-Health
Published
2025-10-08
DOI
https://doi.org/10.1177/15305627251371519
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Tracking Engagement with Remote Patient Monitoring in Prenatal Care and Detection of Preeclampsia: A Retrospective Review

Andrew C. Meltzer, Meylakh Barshay, Kathryn Marko, Anish Sebastian et al.
Telemedicine Journal and e-Health
Artificial Intelligence in Healthcare
article

Tracking Engagement with Remote Patient Monitoring in Prenatal Care and Detection of Preeclampsia: A Retrospective Review

Andrew C. Meltzer, Meylakh Barshay, Kathryn Marko, Anish Sebastian, Taylor Bolden, Andrew Sudimack, Crystal Zang, Aditya Loganathan, Lauren Rosenfeld, Yan Ma
article en

Abstract

<b>Introduction:</b> Mobile technology may enhance traditional prenatal care by supporting screening and patient compliance. Although prior studies report high satisfaction with mobile prenatal technologies, the impact of integrating remote patient monitoring (RPM) into routine workflows on clinical outcomes remains uncertain. This retrospective study assessed whether higher engagement with RPM via the Babyscripts™ digital health platform was associated with increased detection of preeclampsia (PEC). <b>Methods:</b> In this university-based obstetric practice, pregnant patients received the Babyscripts™ platform in addition to standard care. The platform enabled tracking of gestational weight gain and blood pressure and delivered scheduled education on symptoms and screening tests. Patients were included if they initiated RPM use before the end of the first trimester; those without available pregnancy outcomes were excluded. Chart reviews were performed using structured data forms by trained abstractors. RPM engagement was defined as the percentage of weeks with at least one remote blood pressure measurement. Outcomes included PEC and a composite of maternal complications. Multivariate logistic regression identified predictors of engagement. <b>Results:</b> A total of 823 patients were included: 28% identified as Black, 32% were Medicaid/Medicare recipients, 43% were over age 35, and 5% had a history of hypertension. Thirty-seven patients developed PEC or pregnancy-induced hypertension. Living in a distressed community and having at least one prior full-term pregnancy were associated with reduced engagement, with decreases of 7.9% (95% confidence interval [CI]: 1.2-14.6%) and 12.2% (95% CI: 5.2-19.1%), respectively. There was a nonsignificant trend toward increased detection of PEC with higher RPM engagement (odds ratio: 1.014, 95% CI: 0.999-1.846). <b>Conclusion:</b> Higher maternal age and first-time pregnancy were associated with increased RPM engagement, while living in a distressed community was linked to lower engagement. There was a nonsignificant positive association between RPM engagement and detection of PEC. Future studies should explore whether engagement with digital health platforms in prenatal care can modify risk factors for pregnancy complications.

Telemedicine Journal and e-HealthVol. 31(12)
University of Pittsburgh (US), George Washington University (US), Brown University (US), Allscripts (United States) (US), Centers for Medicare and Medicaid Services (US)
Openalex Percentile: Top 74%
Artificial Intelligence in Healthcare
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.