Revolutionizing Maternal Care: AI-Powered Precision Nudging for Maternity Management

Client

Focused on leveraging data and analytics to help providers, payers, and Accountable Care Organizations (ACOs) improve the quality and affordability of healthcare, this client manages ~1M lives under its contracts.

Problem Addressed

Reducing the number of NICU days post-delivery among pregnancies identified as High Risk based on family history and other known risk factors such as hypertension, diabetes, smoking, age, etc.
Reduce the number of pregnancy-related hospital admissions among high-risk cohorts, Reduction of spontaneous preterm birth among nulliparous, asymptomatic mothers and Manage care remotely throughout the 4^th trimester (post-partum)

what we did

Approach

Manage high-risk pregnancies remotely staying digitally connected with expectant mothers 24x7 and deploying our unified health algorithm to continually gather signals (from symptom checks, IoT devices including BP cuffs, and relevant EHR data) to assess the risk of pre-term birth. Using the participants’ MoBe (motivation + ability) Map, the platform delivers hyper- personalized nudges to take mitigatory action and prolong the pregnancy to enable the mother deliver at term.

Enrollment – multiple clinics identify and enroll both pregnancies classified as High Risk and Unknown Risk. Participants use this connected care Healthy Maternity program as a safety net – interacting to provide patient reported data when required (symptom surveys), and to report adherence to specific therapies when relevant. The average nudge open rate has been at 31% throughout the past 20 months of the program that has touched over 1020 pregnancies so far.

Program effectivness

Clinical Outcomes

NICU Length of Stay

Dropped by 36% among high-risk cohort compared to 2020-2022 baseline (pre-program)

Average NICU LoS across all high-risk participants

Was 2.5 days per patient

66% of preterm births in high-risk cases

occurred at 36 weeks, indicating successful pregnancy prolongation

AI-Driven Risk Identification

~14% of participants were reclassified from unknown to high-risk category by AI, approved by clinicians

Preterm Birth Management

81% of high-risk mothers delivered full-term, and 12.4% of pre-term births in the High-Risk cohort occurred during the 36th week of gestation

Twin Pregnancy Outcomes

6 twin deliveries in high-risk group; 4 full-term, 2 with vaginal delivery; Only 1 NICU admission among twin deliveries.

Patient Satisfaction

The program has a Net Promoter Score of 76%