Design-based Data-Driven Decision-support Tools: Producing Improved Cancer Outcomes Through User-Centred Research

Patients with cancer often have to make complex decisions about treatment, with the options varying in risk profiles and effects on survival and quality of life.

Data-driven decision-support tools (DSTs) have the potential to empower patients, support personalized care, improve health outcomes, and promote health equity (optimal decisions also for underserved groups).

However, DSTs currently seldom consider quality of life or individual preferences, and their use in clinical practice remains limited.To address these challenges, the 4D PICTURE consortium will further develop a promising methodology, MetroMapping, to redesign care paths that include novel DSTs.

We will better predict treatment outcomes by developing innovative algorithms and incorporating patient experiences, values and preferences, using AI-based models.

In co-creation with patients and other stakeholders, we will develop data-driven DSTs for patients with breast cancer, prostate cancer and melanoma.

We will evaluate these DSTs as part of MetroMapping as well as stand-alone, to ensure their sustainability as well as addressing social and ethical issues.

We will explore the generalizability of MetroMapping and the DSTs to other types of cancer and across other EU member states.Improved care paths integrating comprehensive DSTs will empower patients, their significant others and health care providers in decision making, and strengthen care at the system level by improving resilience and efficiency.

Whereas the 4D PICTURE consortium includes leaders in modelling, AI, decision making, citizen science, service design, ethics, risk communication, and policy making, this project will impact clinical practice and science across Europe and beyond.