As healthy individuals increasingly can receive genomic testing results that indicate their risk for poor outcomes (e.g. diseases or adverse drug reactions), healthcare providers will need to ensure that the results are handled prudently, by addressing the receipt of the results, the workflow challenges, and liability issues. Given that clinical genomic tests can be initiated outside of the clinical setting (e.g., in a research study), from the clinician?s perspective, they can be characterized as unsolicited genomic results (UGR). Clinical decision support (CDS) has great potential to ease the adoption of UGR by providing clinicians with recommendations and patient-related information presented at particular times to enhance clinical care. Deploying CDS for UGR in a healthcare setting in a scalable way, however, will depend on our capacity to leverage local institutional policy and oversight structures to approve of CDS guidance and strategies for UGR. The specific objective of this research program is to develop and evaluate the Evidence-based Decision support Implementation over Time (EDIT) model for prioritizing and revising deployed CDS for UGR. The EDIT model will empower local oversight committees such as Pharmacy & Therapeutics committees to have a role in the CDS review and deployment processes within existing institutional social systems using accepted organizational processes. The direct benefits of this work will be an EDIT dashboard that can be used by oversight committees to prioritize new and to revise deployed CDS, and infrastructure to close the loop of the learning health system by transferring CDS revisions approved by oversight committee members into deployed CDS for UGR. EDIT model implementation will be informed by mixed methods research strategies: Strategy 1, we will conduct focus groups with oversight committee members in order to understand current roles, tasks and goals of the committee, as well as to capture opinions about the best processes to prioritize, review and approve of new and revised CDS for UGR as part of committee meeting activities. Research Strategy 2, we will conduct a survey study with patients to assess preferences for the return of UGR with CDS and usability studies with oversight committee members to gather feedback on the EDIT dashboard design. Strategy 3, we will conduct time-motion observations of local oversight committee meetings prior to and after deploying the EDIT model in order to plan a future, multi-institution, time-motion study with statistical power to detect differences between oversight committees that use the EDIT dashboard and those that do not. The hypothesis is that time spent prioritizing new and revised CDS will be shorter with use of the EDIT dashboard. Overall, the EDIT model establishes processes that lower barriers to implementing robust genomic medicine programs that can be followed by others. The Genomic Innovator Award will enable me to study, in team-science projects, how the EDIT model can accelerate the institutional review and approval process of CDS for UGR. The broader impact of this work is being able to study rate of UGR adoption by healthcare providers for deployed CDS for UGR.
Being able to customize healthcare based on each person?s unique genetic makeup could enable an era of genomic medicine that would improve prevention, diagnosis and treatment for many types of health conditions. Achieving this vision requires developing computerized tools that help doctors and patients make sense of individual genomic data to show them how to use that data to make better healthcare decisions. Relevant to NHGRI?s interest in the clinical deployment of genomics, the focus of the proposed research program is in the area of implementation science, and will help to address the challenge of adopting unsolicited genomic results.
