Designing Software for Genomics Medicine Service Leaders to Engage Stakeholders

Background: Stakeholder engagement can be challenging yet is critically important for the success of a new genomic medicine service or genetic test offering. Services may include ordering, analysis, interpretation, and counseling associated with using a patient's genetic information to make decisions about medical choices. Objective: The aim of this study was to use a human-centered design (HCD) approach to design software for genomic medicine service leaders seeking to engage stakeholders. Of particular interest were stakeholders that could be partners to champion a new genetic test offering. Methods: Our HCD process was driven by a modified design sprint methodology involving participatory design sessions and semi-structured interviews with experts. Subsequently, we created a low-fidelity prototype aiming to facilitate early engagement with potential genomic medicine service partners. The prototype was used to test the design with current genomic medicine service leaders. To guide our evaluation, we developed a set of design considerations for the software application that reflected common strategies used by programs successfully implementing genetic test offerings in diverse settings. Results: We analyzed notes collected from interview sessions with seven genomic medicine service leaders. We identified ten sub-themes, synthesized corresponding notes, and focused our interpretations around three design considerations: #1-identify potential genomic medicine service partners to champion a new genetic test offering; #2-train and educate stakeholders; and #3-obtain and use genomic medicine partner feedback. The top three ranked sub-themes were: 1 - add new information, 2 - general approval, and 3 - add/change functionality. Conclusion: Our findings suggest that genomic medicine service leaders approve of our software design and process to facilitate key stakeholders’ review and endorsement of a new genetic test offering. We also demonstrated an evaluation strategy that draws from lessons of successful genomic medicine programs to identify and prioritize areas to improve the software in future design iterations.