UT Health Austin Delivers Personalized Data-Driven Care to Pregnant Patients
Computational medicine helps combat pregnancy complications and maternal mortality in expecting patients
Reviewed by: Radek Bukowski, MD, PhD
Written by: Lauryn Gerard
Over the past few decades, big data, artificial intelligence, and computational science have revolutionized the healthcare industry, changing the way diseases are understood, diagnosed, and treated. Today, clinicians can capitalize on the wealth of available data and computational resources to develop detailed models to predict health status to inform patient care, leading to enhanced outcomes, fewer errors, reduced costs, and stronger clinician-patient relationships. This data and computational model informed care is known as computational medicine.
Faculty from across The University of Texas at Austin, including those from the Dell Medical School, Texas Advanced Computer Center (TACC), McCombs School of Business, Department of Mathematics, Department of Statistics and Data Sciences, and the Oden Institute for Computational Engineering and Sciences, have come together to form Computational Health and Medicine, a group dedicated to developing new tools and techniques to improve health outcomes for patients and communities. Members of this team include experts in areas of computational modeling, high-performance computing, human-computer interaction, data visualization, data architecture, statistics, risk communication, medicine, and healthcare delivery.
The goal of Computational Health and Medicine is to utilize advanced computing, including TACC’s new supercomputer, Frontera, to analyze diverse types of data, including confidential and protected data, to improve medical care and outcomes for patients across Texas. This group’s work in computational medicine is currently being used to enhance patient care through Women’s Health, a clinical partnership between UT Health Austin and Ascension Seton.
Approximately 700 women die each year in the U.S. as a result of pregnancy or delivery complications, a national average that is higher than other comparable countries. To combat pregnancy complications and maternal mortality, UT Health Austin maternal-fetal medicine specialist Radek Bukowski, MD, PhD, who sees patients through Women’s Health, leverages computational models of risk factors and patient characteristics using data at a national scale to inform individualized pregnancy care.
“Through the use of computational models and decision-making tools, we are able to answer one of the most important questions in pregnancy, ‘What is the safest delivery method for the individual patient and her baby?’” explains Dr. Bukowski. “We enter a variety of risk factors and protective characteristics that are unique to each patient and our model is able to accurately predict if going into labor or elective cesarean section (C-section) before labor begins would lead to the best possible outcome for both patients, the mother and baby.”
“Even a few risk factors and protective characteristics create a vast number of combinations unique to that patient,” continues Dr. Bukowski. “Some of the combinations are more impactful and others less, but there are no two identical individuals. Accounting for this multitude of unique combinations has only recently become possible with the advancements in computing.”
The Individualized Computational Care Clinic at UT Health Austin provides referral-based consultations to pregnant patients and their providers. Dr. Bukowski visits with the patient and their provider twice during pregnancy, once in the beginning of the pregnancy and once again at the end, three to four weeks before the patient’s due date. For each patient, a unique digital profile is created that can be updated throughout the pregnancy to ensure the best individual prediction as new information arises.
“The model has been validated in over 16 million pregnancies, showing nearly perfect agreement between the predicted and the observed outcomes,” says Dr. Bukowski. “While the prediction and decision making are just a starting point, this knowledge empowers patients to take control of their care and make the individually optimal decision while fully aware of their risks and options.”
As more patients experience success through the Individualized Computational Care Clinic, Dr. Bukowski hopes to make computational care more widely available to the obstetrical community in Austin and across rural areas of Texas where he believes computational care could become very beneficial. While computational health and medicine requires access to a supercomputer, such as TACC’s Fontera, Computational Health and Medicine at UT Austin hopes to serve as a leading model for other organizations looking to develop computational medicine research and provide this type of care in the future.
“The response from our patients and their providers has been overwhelmingly positive and has widely exceeded our expectations,” says Dr. Bukowski. “Pregnancy is complex, and we’ve found that by providing patients with this type of individual information, it allows them to feel more in control and more at ease about their pregnancy and delivery. This work is very near and dear to my heart, and we are excited to be working on subsequent models that we hope to implement soon.”
The Individualized Computational Care Clinic is currently available to patients by referral only. To learn more about services available through Women’s Health, visit here.
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