Biotroniks – Readiness of patients and clinicians to rely on AI and other algorithms to make decisions on medical management

Opportunity

Background AI and automated algorithms are increasingly being used to improve efficiency and quality in healthcare, but their application in medical management—especially for automating treatment decisions—remains limited. Most progress has been made in areas like diagnosis and risk prediction, while treatment decisions still rely heavily on clinicians. In heart failure management, despite strong evidence supporting guideline-directed medical therapy (GDMT), real-world uptake and titration to target doses are poor due to therapy complexity, lack of structured follow-up, workforce limitations, and low patient engagement.

There is a recognised need for strategies that promote the effective adoption of algorithms and AI-powered GDMT. However, it is essential to understand the acceptability and readiness of these technologies among patients and clinicians. Equally important is assessing the preparedness of the Australian healthcare market for digital solutions, taking into account evolving models of care, regulatory frameworks, and funding structures.

Project Objectives

The project team will systematically assess the readiness and perceptions of patients and clinicians regarding the use of AI and automated algorithms in medical management, with a particular focus on cardiovascular care. This assessment will explore comfort levels, uncertainties, and perceived utility of AI-driven decision-making across a range of clinical scenarios, such as medication titration in heart failure, anticoagulation management, and atrial fibrillation recurrence.

To achieve this, the team will employ a combination of qualitative and quantitative research methods, including interviews, focus groups, surveys, and literature reviews, to identify the clinical and contextual factors that influence acceptance of algorithm-driven care. Insights from this study will inform the development of a practical framework to guide the co-design of AI-enabled clinical management solutions, ensuring these tools are tailored to real-world needs and are acceptable to end-users.

Additionally, the team will evaluate the Australian market’s readiness for adopting AI-driven medical management tools, considering regulatory, economic, and operational requirements. The outcomes will include a detailed analysis of patient and clinician readiness, as well as a framework to support the development and implementation of such solutions in future clinical practice.