Making prognostic algorithms useful in shared decision-making: Patients and clinicians’ requirements for the Predict:Breast Cancer interface

Objectives To develop a new interface for the widely used prognostic breast cancer tool: PREDICT. To facilitate shared decision-making around post-surgery breast cancer treatments. To derive insights into communicating the outputs of prognostic models to patients and their clinicians. Method We applied user-centred design principles in developing a new interface for PREDICT. The research involved online surveys, focus groups, meetings, and usability testing with patients, clinicians and the public. Results The new interface has been launched and delivers around 30,000 sessions per month. We identified several principles that are useful when communicating the output of prognostic models, including multiple presentation formats, and contextualising statistics. A programme of future work based on patient and clinician feedback has been developed, including the provision of quantitative data on the adverse effects of adjuvant breast cancer treatments. Conclusions For prognostic algorithms to fulfil their potential to assist with shared decision-making they need carefully designed interfaces. User-centred design puts patients and clinicians needs at the forefront, allowing them to derive the maximum benefit from prognostic models.