A web-based personalized decision support tool for patients diagnosed with ductal carcinoma in situ: development, content evaluation, and usability testing

PURPOSE: Patients diagnosed with ductal carcinoma in situ (DCIS) face trade-offs when deciding among different treatments, including surgery, radiation, and endocrine therapy. A less chosen option is active monitoring. While evidence from clinical trials is not yet available, observational studies show comparable results for active monitoring and immediate treatment on cancer outcomes in select subgroups of patients. We developed and tested a web-based decision support tool (DST) to help patients explore current knowledge about DCIS and make an informed choice. METHODS: The DST, an interactive web application, was informed by literature reviews and formative work with patients, breast surgeons, and health communication experts. We conducted iterative interviews to evaluate the DST content among women with and without a history of breast cancer, as well as breast cancer experts. For usability testing, we conducted an online survey among women with and without a history of breast cancer. RESULTS: For content evaluation, 5 women with and 10 women without a history of DCIS were interviewed. The sample included 11 White and 4 non-White women, with a mean age of 64 years. The expert sample consisted of 5 attendings and a physician assistant. The feedback was used to add, clarify, or reorganize information in the DST. For usability testing, 22 participants with a mean age of 61 years were recruited including 15 White and 7 Black women and 6 women with a history of DCIS. The mean usability score was 3.7 out of 5. Most participants (86%) found that the DST provided unbiased information about treatments. To improve usability, we reduced the per-page content and added navigation cues. CONCLUSION: Content and usability evaluation showed that the DST helps patients explore trade-offs of active monitoring and immediate treatment. By adopting a personalized approach, the tool will enable informed decisions aligned with patients’ values and expectations.