A Randomized Controlled Trial of the Implementation of BREASTChoice , a Multilevel Breast Reconstruction Decision Support Tool With Personalized Risk Prediction

Abstract

Objective: To implement the BREASTChoice decision tool into the electronic health record and evaluate its effectiveness.

Background: BREASTChoice , is a multilevel decision tool that: 1) educates patients about breast reconstruction; 2) estimates personalized risk of complications; 3) clarifies patient preferences; and 4) informs clinicians about patients' risk and preferences.

Methods: A multisite randomized controlled trial enrolled adult women with stage 0-III breast malignancy undergoing mastectomy. Participants were randomized to BREASTChoice or a control website. A survey assessed knowledge, preferences, decisional conflict, shared decision-making, preferred treatment, and usability. We conducted intent-to-treat (ITT), per-protocol (PP) analyses (those randomized to BREASTChoice who accessed the tool), and stratified analyses.

Results: 23/25 eligible clinicians enrolled. 369/761 (48%) contacted patients enrolled and were randomized. Patients' average age was 51 years; 15% were older than 65. BREASTChoice participants had higher knowledge than control participants (ITT: mean 70.6 vs. 67.4, P =0.08; PP: mean 71.4 vs. 67.4, P =0.03), especially when stratified by site (ITT: P =0.04, PP: P =0.01), age (ITT: P =0.04, PP: P =0.02), and race (ITT: P =0.04, PP: P =0.01). BREASTChoice did not improve decisional conflict, match between preferences and treatment, or shared decision-making. In PP analyses, fewer high-risk patients using BREASTChoice chose reconstruction. BREASTChoice had high usability.

Conclusions: BREASTChoice is a novel decision tool incorporating risk prediction, patient education, and clinician engagement. Patients using BREASTChoice had higher knowledge; older adults and those from racially minoritized backgrounds especially benefitted. There was no impact on other decision outcomes. Future studies should overcome implementation barriers and specifically examine decision outcomes among high-risk patients.