Delfina Care: Transforming Pregnancy Care with Machine Learning and Personalized Insights
Written by Dr. Brittany Barreto, Founder & CEO, FemHealth Insights
Delfina is at the forefront of a new era in maternal healthcare. As an integrated pregnancy platform, Delfina utilizes data insights to personalize care to each member's needs. The platform allows care teams to automate routine tasks while optimizing proactive care plans, ensuring that pregnant individuals receive continuous support and have healthier pregnancies. Delfina’s unique approach involves leveraging clinically validated machine learning techniques to predict future interventional needs, thereby bridging the maternal health gap and reducing healthcare costs.
In its ongoing commitment to improving maternal and child health outcomes, Delfina recently made significant strides in diabetes management during pregnancy. Their new study, published in the prestigious American Journal of Obstetrics and Gynecology, exemplifies Delfina’s data-driven approach to healthcare. The research, which focuses on the use of Continuous Glucose Monitoring (CGM) data, offers critical insights into how diabetes control during pregnancy impacts pregnancy outcomes.
Delfina's Commitment to Equitable Maternal Healthcare
Delfina’s mission is to transform pregnancy care with equitable access to individualized insights and integrated systems that improve health outcomes. This commitment to combating health inequity and addressing racial disparities in maternal care is central to their work. The Delfina Care platform is designed to provide all patients with personalized prenatal care, ensuring no one is left behind in their journey toward a safe, healthy, and supported pregnancy.
Delfina partners with healthcare providers, health plans, and employers nationwide to deliver equitable access. By providing the future standard of pregnancy care and making it accessible, Delfina aims to reduce adverse outcomes and significantly impact the maternal health crisis that continues to affect families, particularly those in underserved communities.
The Importance of Continuous Glucose Monitoring in Pregnancy
The recent study by Delfina’s data science team, led by Senior Data Scientist Sara Sauer, PhD, and Chief Scientific Officer Isabel Fulcher, PhD, in collaboration with researchers from the University of Alabama at Birmingham, underscores the potential of CGMs in pregnancy care. Traditional diabetes management during pregnancy typically involves manual blood sugar readings several times a day. However, CGMs provide a continuous stream of glucose data, capturing measurements every five minutes. This data offers a much clearer picture of glycemic trends and how diabetes control—or lack thereof—impacts pregnancy outcomes.
The study, “Discrete glucose profiles identified using continuous glucose monitoring data and their association with adverse pregnancy outcomes” explores this relationship in depth. Using machine learning techniques, the research team identified and classified CGM data into four discrete glucose profiles: “well-controlled,” two different “suboptimally controlled” profiles, and one “poorly controlled” profile. These profiles were then examined in relation to adverse pregnancy outcomes such as preterm birth, cesarean section, preeclampsia, large-for-gestational-age babies, and neonatal intensive care unit (NICU) admissions.
Key Findings from the Study
The findings of the study are both significant and actionable. Individuals with suboptimally or poorly controlled diabetes profiles were found to be at a higher risk of adverse pregnancy outcomes. For example, the poorly controlled profile, characterized by prolonged hyperglycemia overnight, was associated with an increased risk of preeclampsia, large-for-gestational-age newborns, NICU admissions, and neonatal hypoglycemia.
“CGM provides a rich longitudinal data source that is often overlooked in clinical practice because the sheer volume of data is overwhelming and difficult for providers to interpret,” explained Dr. Sauer, one of the study’s authors. “Our analysis is a step towards making CGM data more interpretable and, most importantly, more actionable.”
The study highlights the critical role data can play in improving pregnancy outcomes for individuals with diabetes. By making CGM data more interpretable, healthcare providers can better manage diabetes during pregnancy, potentially reducing the risk of adverse outcomes for both mothers and babies.
The Potential of CGMs in Personalized Pregnancy Care
Delfina’s Chief Scientific Officer, Dr. Isabel Fulcher, expressed excitement about the future of CGM in pregnancy care. “Our research team is excited about the potential of CGMs to deliver a more personalized patient care experience,” she said. “The ability to continuously monitor glucose levels allows for more tailored interventions, enabling healthcare providers to address issues in real-time rather than reacting to complications after they arise.”
This proactive approach is at the heart of Delfina’s vision for maternal healthcare. By harnessing the power of data and machine learning, Delfina aims to remove the guesswork from pregnancy care, allowing parents and care teams to focus on what matters most—the health and well-being of both mother and baby.
A Closer Look at the Study's Design and Results
The study conducted by Delfina and its collaborators was a retrospective cohort study involving 203 pregnant individuals with Type 1 or Type 2 diabetes who used CGM during their pregnancies. After excluding pregnancies with major fetal anomalies, multiple pregnancies, and those with incomplete CGM data, the final sample included 177 participants. The study aimed to identify distinct glucose profiles using machine learning and evaluate their association with adverse maternal and neonatal outcomes.
The study found that participants with suboptimal or poorly controlled glucose profiles had higher odds of experiencing adverse pregnancy outcomes. For example, the poorly controlled glucose profile was associated with a higher likelihood of preeclampsia, large-for-gestational-age babies, and NICU admissions. These findings emphasize the importance of maintaining well-controlled glucose levels during pregnancy to reduce the risk of complications.
The Broader Implications for Maternal Healthcare
The implications of Delfina’s research extend beyond diabetes management during pregnancy. The study highlights the broader potential of data-driven healthcare to improve maternal and child health outcomes. By leveraging advanced technologies like CGMs and machine learning, healthcare providers can gain deeper insights into each patient’s unique needs and tailor care accordingly. In addition to insights into CGM, Delfina has applied machine learning to model hypertensive disorders of pregnancy (winning an award from NICHD), gestational diabetes, small for gestational age, and gestational weight gain.
This personalized approach is particularly important in addressing health disparities. Historically, underserved populations have faced significant barriers to accessing quality maternal healthcare. By providing equitable access to individualized care, Delfina aims to reduce these disparities and ensure all individuals have the support they need for a healthy pregnancy.
Delfina’s Vision for the Future
Delfina’s vision for the future of pregnancy care is one in which every pregnancy is safe, healthy, and supported. The company’s mission is to transform pregnancy care through equitable access to individualized insights and integrated systems that improve health outcomes. Delfina’s work is driven by the belief that data has the power to create a safe, healthy, and happy journey for every pregnancy.
Delfina’s CEO, Senan Ebrahim, MD, PhD, commented on the implications of this study for maternal metabolic health: “Our clinician partners regularly hear from patients asking if they can use CGM to track their glucose. Our study demonstrates that in addition to being patient-preferred, CGM data analyzed with our advanced AI approach holds great promise for metabolic health in pregnancy. We are excited to incorporate this powerful technology safely and effectively into Delfina Care.”
The recent study on pregestational diabetes is just one example of how Delfina is using data to improve maternal healthcare. By continuing to innovate and collaborate with healthcare providers and payors, Delfina aims to set new standards for pregnancy care and ensure that all families have the best possible outcomes.
Conclusion: The Future Standard of Data-Driven Pregnancy Care
Delfina Care is leading the way in transforming pregnancy care through its innovative use of data and machine learning. The company’s recent study on diabetes during pregnancy exemplifies its commitment to improving maternal health outcomes by providing personalized care based on deep insights into each patient’s needs.
As the maternal health crisis continues to affect families across the nation, Delfina’s work is more important than ever. By bridging the gap in maternal healthcare and addressing health disparities, Delfina is helping to create a future where every pregnancy is safe, healthy, and supported.
In the years to come, Delfina will undoubtedly continue to push the boundaries of what is possible in maternal healthcare. With its commitment to data-driven, patient-centered care, Delfina is poised to make a lasting impact on the lives of countless families, ensuring that all individuals have access to the care they need for a successful pregnancy journey.
If you are an employer, healthcare plan, or healthcare provider interested in Delfina Care services and technologies, please contact partner@delfina.com.
About the Author:
Dr. Brittany Barreto, Ph.D., is the Founder and Chief Innovation Officer at FemHealth Insights. Every day, Brittany dedicates her work to advancing women’s health innovation by equipping key stakeholders with data-driven insights and strategic advice on the FemHealth market. She is also host of the FemTech Focus Podcast - the number 1 femtech podcast globally.
