Digital health technologies for high-risk pregnancy management: three case studies using Digilego framework

Area of Science:

• Digital Health
• Maternal Health
• Social Computing
• Data Science

Background:

• High-risk pregnancy (HRP) conditions like gestational diabetes mellitus (GDM), hypertension (HTN), and peripartum depression (PPD) significantly impact maternal and neonatal health.
• Effective management of HRP requires robust patient engagement, yet current commercial digital solutions offer limited support.
• There is a critical need for advanced digital tools to enhance patient engagement and self-management in HRP.

Purpose of the Study:

• To develop a portfolio of digital health products leveraging social computing, data science, and digital health advancements for HRP management.
• To address the gap in suboptimal digital support for conditions including GDM, HTN, and PPD.
• To create tools that facilitate patient engagement and improve health outcomes in high-risk pregnancies.

Main Methods:

• Utilized the Digilego digital health development framework across three studies.
• Conducted large-scale social media analysis (n=55,301 posts) to identify population-level needs.
• Developed a digital repository for curating HRP information and a platform for PPD prevention, employing qualitative coding, machine learning, and theory-mapping.
• Performed preliminary acceptance testing with pregnant women for GDM/HTN information management (n=10) and PPD prevention (n=30).

Main Results:

• Developed two digital health solutions: MyPregnancyChart and MomMind.
• Scalable social computing models accurately identified psychosociobehavioral drivers for HRP management.
• Initial evaluations demonstrated positive acceptance of both tools by potential end-users.
• MomMind showed statistically significant improvements (P < .05) in PPD recognition and knowledge of seeking PPD information.

Conclusions:

• The Digilego framework offers an integrative approach for understanding women's needs and optimizing digital engagement in disease management.
• Developed digital solutions show promise for enhancing self-management of high-risk conditions.
• Future work should focus on implementation and testing to improve prenatal information utilization and health outcomes.