What is the name of your organization?
Fundación Valle del Lili (FVL, for its acronym in Spanish).
What is the name of your solution?
Preeclapp
Provide a one-line summary or tagline for your solution.
AI-based clinical decision support for obstetric emergencies
In what city, town, or region is your solution team headquartered?
Cali, Valle del Cauca, Colombia
In what country is your solution team headquartered?
Colombia
What type of organization is your solution team?
Nonprofit
Film your elevator pitch.
What specific problem are you solving?
In 2023, around 260,000 women died globally from pregnancy-related causes, according to the The World Health Organization (WHO). In Colombia, maternal mortality remains a significant public health challenge. The Maternal Mortality Ratio is high compared to OECD countries, with 83 deaths per 100,000 live births in 2017, versus 18 deaths per 100,000 in other OECD nations. The WHO estimates that, without substantial intervention, Colombia will only reduce this rate to 35 by 2030. Obstetric complications such as postpartum hemorrhage (PPH) are the leading cause of maternal death. Most of these deaths are preventable with timely and effective care.
The Hospital Padrino Strategy, implemented by the FVL, has significantly reduced maternal mortality in Colombia´s Pacific region, from 78.8 to 12.0 deaths per 100,000 live births in Valle del Cauca department between 2021 and 2022. However, care gaps persist in low-HDI regions due to access barriers.
Despite evidence-based recommendations, the late detection of complications such as PPH continues to hinder the timely initiation of life-saving treatments. Our efforts focus on reducing preventable maternal deaths by improving early detection and response to obstetric emergencies, through equitable access to care.
What is your solution?
Preeclapp is a mobile application based on expert systems, validated and currently in use for the timely diagnosis and management of preeclampsia. It uses artificial intelligence to provide personalized clinical recommendations and assist healthcare professionals in making quick and accurate decisions during obstetric emergencies. Also, this application will be scaled to address PPH, incorporating new features such as predictive models for complications, real-time monitoring, clinical data management, and automated alerts, as well as predictive models to identify at-risk patients and georeferencing to optimize patient referral to the most suitable healthcare centers in real-time. Scaling Preeclapp brings AI obstetric care to underserved LATAM.
The application employs standardized clinical decision algorithms that analyze clinical, paraclinical, and obstetric history data, generating alerts and management recommendations based on the specific situation of each patient. It uses advanced technologies such as predictive artificial intelligence and geolocation, enabling hospitals to improve care efficiency and reduce the risk of severe complications. Preeclapp will initially be implemented in selected hospitals for validation in PPH management, with the goal of expanding its reach and optimizing obstetric care in Colombia.
Here is a link to a video about the app:
https://clias.iecs.org.ar/proyectos/inteligencia-artificial-diagnostico-preeclampsia-colombia/
Who does your solution serve, and in what ways will the solution impact their lives?
Our solution is aimed at hospitals with limited resources in remote areas of Colombia, specifically those that are part of the HPS. These hospitals face significant challenges due to a lack of specialized personnel and insufficient biomedical equipment, which hinders the effective management of high-risk obstetric emergencies such as preeclampsia and PPH. These resource limitations lead to delays in care and errors in diagnosis and management, increasing maternal and neonatal mortality in these regions.
The solution is designed to strengthen the capabilities of healthcare personnel in these beneficiary hospitals, enabling them to standardize and efficiently manage high-risk pregnant women through Preeclapp, a mobile application that helps identify high-risk patients and provides them with personalized management pathways based on each patient's clinical condition. Additionally, when necessary, it guides healthcare staff in efficiently referring patients to the most appropriate healthcare centers for specialized care.
By enhancing the capabilities of these hospitals, we aim to optimize the speed and accuracy of clinical decision-making, reducing delays in care and the risks associated with late diagnoses. This will directly improve maternal and neonatal health outcomes, reduce maternal and neonatal mortality, and strengthen the healthcare system’s response in underserved areas of Colombia.
