Pregnancy Care Reimagined

Pregnancy is one of the most important windows for improving lifelong health. Complications during pregnancy can reveal underlying maternal cardiometabolic, renal, and mental health risks, while conditions such as fetal growth restriction and diabetes in pregnancy influence the long-term health of children, contributing to chronic disease, disability and premature mortality. Yet maternity systems are facing escalating pressures. Workforce shortages, rising healthcare costs, increasing clinical complexity, and persistent health inequities threaten the sustainability of pregnancy care globally. In Australia alone, maternity care costs approximately $9 billion annually, with costs rising despite little improvement in outcomes. At the same time, women are entering pregnancy with increasingly complex health profiles, including higher maternal age, obesity, and improved survival from chronic diseases such as congenital heart disease and cancer. Digital technologies offer enormous potential to address these challenges. Telehealth, mobile health platforms, wearable monitoring and artificial intelligence (AI) are rapidly transforming healthcare, within a global digital health market valued at over USD $430 billion. However, much of the innovation in pregnancy care technology is driven by industry rather than clinicians or consumers. Many digital tools lack clinical oversight, evidence-based design, or rigorous evaluation. A recent review of pregnancy apps found that only 7% involved health professionals in development and fewer than 5% had been formally evaluated. This PhD will contribute to Care Reimagined, an ambitious research program designed to transform maternity care through the responsible integration of artificial intelligence and digital health. Care Reimagined will function as an implementation pathway to safely evaluate and embed AI into real-world maternity care. Using maternity care as a proof of concept, the pathway will enable: • Machine learning–guided care models to allocate the right care to the right person at the right time through dynamic risk prediction across pregnancy • AI-supported health system redesign, using automated reasoning to model and simulate optimal maternity care pathways before clinical implementation • Agentic AI tools to improve patient engagement, personalise information for clinicians, and streamline health service workflows • Real-world validation through “silent trials” and implementation evaluation to ensure safety, equity, cost-effectiveness, and improved clinical outcomes The program will be implemented at Monash Health, one of Australia’s largest healthcare services and Victoria’s largest maternity provider, with strong partnerships across national maternity networks to support broader implementation and impact.