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Bevan Exemplar Cohort 9 projects

Risk Assessment Tool: Enhancing Safety and Optimizing Childbirth Outcomes for Women with Pre-Existing Conditions

Pooja Chawla

Digital Health and Care Wales

The Welsh Government aims to provide safe, personalized, and effective maternity care. Managing high-risk pregnancies is challenging, especially for women with pre-existing conditions who face higher risks during childbirth. In today’s rapidly evolving digital landscape, there’s a need for a digital tool that offers accurate, personalized risk assessments to improve care.

Project Overview:

We aim to create a Digital Risk Assessment Tool using machine learning. This tool will help predict risks during childbirth by providing detailed, personalized risk profiles. The tool can work with the Digital Maternity Cymru system to offer better guidance for managing both high-risk and low-risk pregnancies, ensuring consistent care across Wales. The project will prioritize ethical practices, inclusivity, and reducing bias, ensuring the tool meets the needs of all women, including marginalized groups.

How You Will Do This:

  • We plan to use anonymized datasets from Digital Health and Care Wales to build a solid data foundation.
  • The integrated dataset will be used to develop machine learning models that assess the risk of childbirth complications and create personalized risk scores for each patient. These models will be rigorously tested for accuracy.
  • We will involve users in the process by collecting feedback on early versions of the tool to support shared decision-making and improve autonomy.
  • The tool will then be introduced to healthcare providers along with training on its use.
  • Continuous feedback will be gathered to enhance the tool’s functionality and usability, ensuring it remains effective and user-friendly.

Anticipated Benefits:

  • Better decision-making for healthcare providers.
  • Fewer complications during childbirth.
  • Improved health outcomes for mothers and babies.
  • Greater confidence and preparation for expectant mothers with pre-existing conditions.