Redevelopment of the Predict: Breast Cancer website and recommendations for developing interfaces to support decision-making

TLDR: In this paper, the authors developed a new interface for the widely used prognostic breast cancer tool: Predict: Breast Cancer, to facilitate decision-making around post-surgery breast cancer treatments and derive recommendations for communicating the outputs of prognostic models to patients and their clinicians.

Abstract: OBJECTIVES To develop a new interface for the widely used prognostic breast cancer tool: Predict: Breast Cancer. To facilitate decision-making around post-surgery breast cancer treatments. To derive recommendations for communicating the outputs of prognostic models to patients and their clinicians. METHOD We employed a user-centred design process comprised of background research and iterative testing of prototypes with clinicians and patients. Methods included surveys, focus groups and usability testing. RESULTS The updated interface now caters to the needs of a wider audience through the addition of new visualisations, instantaneous updating of results, enhanced explanatory information and the addition of new predictors and outputs. A programme of future research was identified and is now underway, including the provision of quantitative data on the adverse effects of adjuvant breast cancer treatments. Based on our user-centred design process, we identify six recommendations for communicating the outputs of prognostic models including the need to contextualise statistics, identify and address gaps in knowledge, and the critical importance of engaging with prospective users when designing communications. CONCLUSIONS For prognostic algorithms to fulfil their potential to assist with 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.