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Author
Amanda N. Davis-Juarez -
Co-Author
Amanda Davis-Juarez, Anugrah Prakash, Natalia Rodriguez Muxica, Priyesh Priyesh, Neha Agrawal
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Abstract Title
Happy Heartbeats
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Abstract Description
Title: Happy Heartbeats
Authors: Amanda Davis-Juarez, Anugrah Prakash, Natalia Rodriguez Muxica, Priyesh Priyesh, Neha Agrawal
Area of Concentration: Medical Device
Specialty: Obstetrics and Gynecology
Keywords: Medical device, Pregnancy, Health Equity
Background High-risk pregnancies require frequent nonstress tests (NSTs) to monitor fetal health. Inadequate monitoring can lead to severe consequences, including stillbirth and long-term developmental issues. Access to NST testing is challenging, particularly for those living in maternal healthcare deserts, where hospitals and obstetric providers are scarce. The burden of travel, financial constraints, and hospital resource limitations make frequent in-person NST testing difficult for many pregnant individuals. Happy Heartbeats aims to bridge this gap by providing an innovative remote monitoring solution that enables expectant mothers to perform NSTs at home while ensuring timely physician oversight and intervention.
Objectives Happy Heartbeats’ goal is to improve access to prenatal care by providing a reliable, insurance-covered remote monitoring system. The solution seeks to reduce travel burdens, increase patient compliance with NST recommendations, and improve health outcomes for both mothers and babies. By integrating Remote Patient Monitoring (RPM) and Clinical Decision Support (CDS), Happy Heartbeats ensures that expectant mothers, especially those in underserved regions, receive timely and accurate fetal monitoring.
Design Happy Heartbeats developed HomeBeats Sense, a software platform that interfaces with existing FDA-approved cardiotocography (CTG) machines. The system includes:
- Remote Patient Monitoring (RPM): Enables real-time data transmission from home to healthcare providers.
- Clinical Decision Support (CDS): Provides automated preliminary analysis and alerts for abnormal results, aiding physicians in timely intervention.
Patients receive training for proper device usage through certified staff or video tutorials. The program is structured to align with ACOG guidelines, with patients completing NSTs based on physician recommendations. The software platform ensures secure data transmission via HIPAA-compliant cloud storage, integrating seamlessly into electronic health records (EHRs). The initial pilot focuses on high-risk pregnancies in rural areas, with a goal of expanding nationwide.
Impact/Effectiveness A comprehensive study involving 88+ interviews with stakeholders, including physicians, insurance representatives, and patients, as well as surveys with over 200 expectant mothers and 50+ fetal specialists, demonstrated strong support for remote NST testing. Key findings include:
- 73.5% of mothers are comfortable performing NSTs at home if trained.
- 80% of physicians would use a software-aided system for NST interpretation.
- 64% of physicians agree that increased NST frequency improves health outcomes.
- 100% of surveyed physicians found a remote solution valuable for high-risk pregnancies.
By ensuring continuous access to fetal monitoring, HomeBeats Sense has the potential to improve neonatal outcomes, while decreasing the financial burden on healthcare providers and insurers.
Lessons Learned
Key challenges include:
- Ensuring proper patient training for device use.
- Addressing concerns about receiving and interpreting negative results.
- Managing liability concerns and physician workload.
Key successes include:
- High patient and physician interest in remote NST solutions.
- Strong potential for insurance reimbursement through existing RPM CPT codes.
- Positive initial feedback from pilot trials and prototypes.
Summary Happy Heartbeats presents a transformative approach to prenatal care by providing an accessible, physician-supported, remote NST solution. This innovation enhances monitoring capabilities, particularly for underserved populations, while maintaining clinical accuracy
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Project Specialty (Please select one)
Academic Medicine