Developing a Birth Plan With Confidence

UT Health Austin maternal-fetal medicine specialist uses computational medicine to help inform patient decision-making

Reviewed by: Radek Bukowski, MD, PhD, and Emily Worland (Patient)
Written by: Lauryn Gerard

A newborn baby holds a woman's thumb in their hand.

Many expectant mothers develop a birth plan that outlines their preferences for bringing their new baby into the world. These plans often include decisions related to the delivery location, designated support persons, pain management, labor and delivery preferences, feeding and care post-delivery, and more. Patients then work together with their providers to determine the best plan of delivery based on general risk factors and characteristics. While these plans are always helpful, it can be difficult to predict everything that could occur for each individual patient once labor begins, and plans often change when something unexpected arises.

When developing a birth plan, the benefit of using personalized data and information to determine the safest delivery option can help ensure the best possible outcome for both mother and baby while also avoiding unexpected complications. Having access to patient-specific information can reduce anxiety surrounding labor and delivery for moms and families, empower patients to create a birth plan they feel confident in, and arm clinical teams with the tools they need to ensure things go according to that plan.

For expecting mother Emily Worland, a patient cared for by UT Health Austin obstetrician-gynecologist Denise Johnson, MD, through Women’s Health, a clinical partnership between Ascension Seton and UT Health Austin, was able to feel confident in her birth plan and was able to work with her providers to achieve the delivery experience she desired because of the services offered through the Individualized Computational Care Clinic within Women’s Health. This specialized clinic, led by UT Health Austin maternal-fetal medicine specialist Radek Bukowski, MD, PhD, uses computational medicine to define the safest possible delivery option for pregnant patients using computational models and decision-making tools.

“When I got pregnant in the fall of 2020, I knew I wanted my care to be delivered at an academic medical center because of the opportunity to be treated by some of the most advanced physicians using the most cutting-edge approaches to medicine. When I called UT Health Austin, I was connected with Dr. Johnson for my obstetrical care and really connected with her right away. Around 11 weeks into my pregnancy, she asked if I was interested in seeing her colleague Dr. Bukowski participate in a study that determined the safest delivery option for mothers and their babies, and I said, ‘Of course,’ because I thought it would be interesting,” explains Emily.

As someone with an extensive background in law and who was actually studying to complete her Master of Laws (LLM) at The University of Texas at Austin during her pregnancy, Emily is no stranger to how data can impact strategy and inform decision-making. For her, the meetings with Dr. Bukowski provided clarity surrounding her own personal risk factors and characteristics, reinforcing her decision to move forward with a birth plan involving an elective C-section.

“Based on my own family history, I had always leaned toward having an elective C-section, which I know is not the traditional approach to labor and delivery,” says Emily. “My mother had a traumatic vaginal birth, and I knew that was something I wanted to avoid. When I met with Dr. Bukowski at the beginning of my pregnancy, he walked me through how the supercomputer analyzes my data to deliver potential outcomes specific to me and my pregnancy. Using my family history, my risk factors, and other personal variables, the model was able to tell me that an elective C-section was, in fact, the safest path to delivery for me.”

Dr. Bukowski creates a unique digital profile for each of his patients that can be updated throughout their pregnancy to ensure the best individual prediction as new information arises. The model he uses has been validated in over 16 million pregnancies, showing nearly perfect agreement between the predicted and the observed outcomes. This knowledge empowers patients to take control of their care and make individual optimal decisions while fully aware of their risks and options. It is important to note that the Individualized Computational Care Clinic focuses only on the safest mode of delivery for each individual patient, and while in Emily’s case that happened to be a C-section, which is what she was wanting, this type of counseling may even decrease C-section rates by advising vaginal delivery in patients who may be contemplating C-sections.

Emily Worland holds her baby Montgomery at a park.
Emily and baby Montgomery

Toward the end of her pregnancy, Emily completed her LLM and moved back to Dallas. She was able to easily transition her care and use the personalized data Dr. Bukowski provided to bring her new providers up to speed on her birth plan.

“Initially, I thought it was going to be an uphill battle, but I felt confident that with statistics to back me up, this was an informed choice, and I could be vocal about it and advocate for myself,” says Emily. “Thankfully, my providers were supportive of my decision and impressed by the data I had from Dr. Bukowski’s study. In June 2021, I delivered a healthy baby boy via C-section, and it was exactly the experience I had hoped and planned for.”

Emily’s experience using computational care to inform her labor and delivery decision-making is just one of many successful instances in which computational medicine has helped improve outcomes for patients facing complex decisions regarding their health. The unique services offered through the Individualized Computational Care Clinic within Women’s Health are made possible through a cross-campus collaboration involving 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.

To learn more about how computational medicine is being used to enhance patient care, visit here.

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.

About the Partnership Between UT Health Austin and Ascension Seton

The collaboration between UT Health Austin and Ascension brings together medical professionals, medical school learners, and researchers who are all part of the integrated mission of transforming healthcare delivery and redesigning the academic health environment to better serve society. This collaboration allows highly specialized providers who are at the forefront of the latest research, diagnostic, and technological developments to build an integrated system of care that is a collaborative resource for clinicians and their patients.

About UT Health Austin

UT Health Austin is the clinical practice of the Dell Medical School at The University of Texas at Austin. We collaborate with our colleagues at the Dell Medical School and The University of Texas at Austin to utilize the latest research, diagnostic, and treatment techniques, allowing us to provide patients with an unparalleled quality of care. Our experienced healthcare professionals deliver personalized, whole-person care of uncompromising quality and treat each patient as an individual with unique circumstances, priorities, and beliefs. Working directly with you, your care team creates an individualized care plan to help you reach the goals that matter most to you — in the care room and beyond. For more information, call us at 1-833-UT-CARES or request an appointment here.