Catalyst Awardee

Project Description

Digital Solutions to Reduce Maternal Morbidity and Mortality in Refugee Women

Gunisha Kaur, MD, MA | Weill Cornell Medicine; Stephen Yale-Loehr, JD | Cornell University; Richard Boyer, MD PhD | Weill Cornell Medicine
Competition Sponsor: US National Academy of Medicine
Awardee Year: 2023

 

Pregnant refugee women have an elevated risk for uncontrolled hypertension, which increases gestational complications including preeclampsia, eclampsia, and maternal mortality. Gestational hypertension and preeclampsia also substantially increase the incidence of cardiovascular disease later in life, and pose significant risk to the fetus. Our research demonstrates several barriers that prevent refugees from accessing in-person healthcare. However, we have found that digital approaches are a pragmatic means to overcome these challenges, and that >90% of refugees have personal smartphones compatible with digital health applications. We have created a customized digital refugee health system, which includes a wearable device plus a customized app, for early risk stratification and identification of gestational hypertension, cardiovascular and preeclampsia risk, and related biomarkers using predictive machine learning, ecological momentary assessments, and remote digital data. In this research, we will clinically train and validate this digital system. Our hypothesis is that our digital system can detect gestational hypertension and preeclampsia in pregnant refugee women with >85% sensitivity as compared to the gold standard, a clinic diagnosis. We have over a decade of experience in refugee health research, including with digital tools, and are based at one of the only federally funded refugee research centers in the U.S. Increasing the diagnosis of hypertension and preeclampsia risk in pregnant refugees enables targeted interventions that can positively alter health outcomes. This project has the potential to improve the healthy longevity of this vulnerable and understudied population for generations, and can be scaled for use across global humanitarian emergency settings.

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