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How Artificial Intelligence Can Improve Pregnancy Outcomes

Senan Ebrahim, MD, PhD
CEO at Delfina
01 Sep 2022 · 5 min read
AI in pregnancy care

In the past decade, the healthcare field has seen a surge in the utilization of artificial intelligence (AI) technologies across many different medical specialties. Delfina is building an AI-driven platform, with the goal of improving pregnancy outcomes and access to data-driven care for birthing people everywhere.

AI Uses in Healthcare and Pregnancy

AI-based technologies are already helping physicians and other healthcare providers in analyzing multiple data sources more efficiently, leading to improved accuracy of diagnosis and better informed decisions on treatment options for their patients. By providing physicians with AI-enhanced tools such as virtual nursing, workflow assistance, medication dosage error correction, connected medical devices and automated image diagnosis, these advances have been time- and cost-saving for providers and healthcare systems and life-saving for the people they care for.

AI techniques have been used to predict pregnancy disorders like gestational diabetes, preterm birth, suicidal behavior and preeclampsia (a blood pressure disorder that can have serious complications for both parent and child). AI-enhanced models have also assisted in the management and treatment of ectopic pregnancies and in risk assessment analyses for adverse outcomes associated with congenital heart disease in pregnant women.

The Importance of Prenatal Care

Advances in AI have been propelled forward, in part, by a need to tackle the US maternal health crisis. This past March, the Centers for Disease Control and Prevention (CDC) released the maternal mortality statistics for 2020, which assessed the overall maternal mortality rate across the country. In contrast to the decreasing maternal mortality rates in all other industrialized nations, the U.S. has seen an increase from 2019 to 2020—an increase driven by worsening maternal health outcomes, which are considered preventable in about two-thirds of cases.

Bridging the Access Gap

Next generation models of care, such as telehealth services and AI-driven technologies, are now being explored more than ever as a way to level the playing field for our most vulnerable birthing people. In particular, the use of AI-driven connected medical devices has proven promising.

A well-known example of a connected medical system is IntelliVue GuardianSoftware by Philips Healthcare. Their Early Warning Scoring system uses AI techniques to analyze data from sensor-equipped wearables to identify abnormal changes in the patient’s vital signs, like blood pressure and heart rate, and proactively notifies providers so they can prevent any life-threatening events. This system has allowed for significant improvements in patient outcomes.

Similarly connected medical systems in pregnancy care, such as our technology at Delfina, can provide a measurable way to improve pregnancy outcomes for those who have historically had less access to quality healthcare. Wearable sensors and other smart health innovations present exciting opportunities to improve the diagnosis, clinical monitoring, and management of pregnancy health outside of traditional, less accessible healthcare settings. New advancements in wearable devices can extend the capabilities of clinical monitoring and have the potential to increase early detection of pregnancy complications.

Where does Delfina fit in?

Delfina Care is a system offering pregnant people and their providers a comprehensive care management platform to support pregnancy journeys. It is a multi-product platform that facilitates continuous data integration, incorporating data from the pregnant user, her electronic medical records, and remote monitoring provided by Delfina, ultimately facilitating real-time bi-directional interactions, guidance, and support between provider and patient.

Delfina Care incorporates deep learning models that deliver predictive risk scores for conditions including perinatal mental health, hypertensive disorders of pregnancy, and diabetes in pregnancy to optimize care throughout a patient’s pregnancy journey. Prediction models are developed from rich health data sources including information on social determinants of health and a patient’s health history. To ensure equitable risk prediction across all patients, we build our models from racially, geographically, and economically diverse patient populations and use advanced computational approaches to ensure equitable model performance. Delfina Care uniquely helps bridge the maternal health gap by standardizing access to quality care so that birthing people and babies can have better outcomes, while also reducing healthcare costs.

Delfina has received awards from the NICHD for a novel approach to predicting hypertensive disorders of pregnancy. Using this approach, we will be able to identify potential risks in pregnancy earlier to enable effective interventions by the care team and to achieve our ultimate goal - to foster safe, healthy, and supported journeys for every pregnancy.

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