Perceived Utility of Genomic Sequencing: Qualitative Analysis and Synthesis of a Conceptual Model to Inform Patient-Centered Instrument Development.

BACKGROUND AND OBJECTIVES: Successful clinical integration of genomic sequencing (GS) requires evidence of its utility. While GS potentially has benefits (utilities) or harms (disutilities) across multiple domains of life for both patients and their families, there is as yet no empirically informed conceptual model of these effects. Our objective was to develop an empirically informed conceptual model of perceived utility of GS that captures utilities and disutilities for patients and their families across diverse backgrounds. METHODS: We took a patient-centered approach, in which we began with a review of existing literature followed by collection of primary interview data. We conducted semi-structured interviews to explore types of utility in a clinically and sociopolitically diverse sample of 60 adults from seven Clinical Sequencing Evidence-Generating Research (CSER) consortium projects. Interviewees had either personally received, or were parents of a child who had received, GS results. Qualitative data were analyzed using thematic analysis. Findings from interviews were integrated with existing literature on clinical and personal utility to form the basis of an initial conceptual model that was refined based on expert review and feedback. RESULTS: Five key utility types that have been previously identified in qualitative literature held up as primary domains of utility and disutility in our diverse sample. Interview data were used to specify and organize subdomains of an initial conceptual model. After expert refinement, the five primary domains included in the final model are clinical, emotional, behavioral, cognitive, and social, and several subdomains are specified within each. CONCLUSION: We present an empirically informed conceptual model of perceived utility of GS. This model can be used to guide development of instruments for patient-centered outcome measurement that capture the range of relevant utilities and disutilities and inform clinical implementation of GS.

Network Engagement in Action: Stakeholder Engagement Activities to Enhance Patient-centeredness of Research.

BACKGROUND: Stakeholders (ie, patients, policymakers, clinicians, advocacy groups, health system leaders, payers, and others) offer critical input at various stages in the research continuum, and their contributions are increasingly recognized as an important component of effective translational research. Natural experiments, in particular, may benefit from stakeholder feedback in addressing real-world issues and providing insight into future policy decisions, though best practices for the engagement of stakeholders in observational studies are limited in the literature. METHODS: The Natural Experiments for Translation in Diabetes 2.0 (NEXT-D2) network utilizes rigorous methods to evaluate natural experiments in health policy and program delivery with a focus on diabetes-related outcomes. Each of the 8 partnering institutions incorporates stakeholder engagement throughout multiple study phases to enhance the patient-centeredness of results. NEXT-D2 dedicates a committee to Engagement for resource sharing, enhancing engagement approaches, and advancing network-wide engagement activities. Key stakeholder engagement activities include Study Meetings, Proposal Development, Trainings & Educational Opportunities, Data Analysis, and Results Dissemination. Network-wide patient-centered resources and multimedia have also been developed through the broad expertise of each site's stakeholder group. CONCLUSIONS: This collaboration has created a continuous feedback loop wherein site-level engagement approaches are informed via the network and network-level engagement efforts are shaped by individual sites. Emerging best practices include: incorporating stakeholders in multiple ways throughout the research, building on previous relationships with stakeholders, enhancing capacity through stakeholder and investigator training, involving stakeholders in refining outcome choices and understanding the meaning of variables, and recognizing the power of stakeholders in maximizing dissemination.

A Tale of 2 Constituencies: Exploring Patient and Clinician Perspectives in the Age of Big Data.

BACKGROUND: Patient and clinician stakeholders are inadequately engaged in key aspects of research, particularly regarding use of Big Data to study and improve patient-centered outcomes. Little is known about the attitudes, interests, and concerns of stakeholders regarding such data. RESEARCH DESIGN: The New York City Clinical Data Research Network (NYC-CDRN), a collaboration of research, clinical, and community leaders built a deidentified dataset containing electronic health records from millions of New Yorkers. Guided by a patient-clinician advisory board, we developed a question guide to explore patient and clinician experiences and ideas about research using large datasets. Trained facilitators led discussions during preexisting patient, community, and clinician group meetings. The research team coded meeting notes and identified themes. RESULTS: Fully 272 individuals participated in 19 listening sessions (139 patients/advocates, 133 clinicians) at 6 medical centers with diverse NYC communities: 76% were female and 63% were nonwhite. Clinicians and patients agreed on all major themes including the central role of clinicians in introducing patients to research and the need for public campaigns to inform stakeholders about Big Data. Stakeholders were interested in using granular data to compare the care and clinical outcomes of their neighborhoods with others across NYC, but were also concerned that data could not truly be deidentified. CONCLUSIONS: Clinicians and patients agree on potential benefits of stakeholder-engaged Big Data research and provided suggestions for further research and building stakeholder research capacity. This evaluation demonstrated the potential of brief meetings with existing patient and clinical groups to explore barriers and facilitators to patient and clinician engagement.

Accelerators: Sparking Innovation and Transdisciplinary Team Science in Disparities Research.

Development and implementation of effective, sustainable, and scalable interventions that advance equity could be propelled by innovative and inclusive partnerships. Readied catalytic frameworks that foster communication, collaboration, a shared vision, and transformative translational research across scientific and non-scientific divides are needed to foster rapid generation of novel solutions to address and ultimately eliminate disparities. To achieve this, we transformed and expanded a community-academic board into a translational science board with members from public, academic and private sectors. Rooted in team science, diverse board experts formed topic-specific "accelerators", tasked with collaborating to rapidly generate new ideas, questions, approaches, and projects comprising patients, advocates, clinicians, researchers, funders, public health and industry leaders. We began with four accelerators-digital health, big data, genomics and environmental health-and were rapidly able to respond to funding opportunities, transform new ideas into clinical and community programs, generate new, accessible, actionable data, and more efficiently and effectively conduct research. This innovative model has the power to maximize research quality and efficiency, improve patient care and engagement, optimize data democratization and dissemination among target populations, contribute to policy, and lead to systems changes needed to address the root causes of disparities.

Community capacity building: a collaborative approach to designing a training and education model.

BACKGROUND: Successful community-academic research partnerships require building the capacity of both community-based organizations (CBOs) and academics to conduct collaborative research of mutual interest and benefit. Yet, information about the needs and goals of research-interested CBOs is lacking. Our partnership aimed to conduct a community research needs assessment and to use results to develop future capacity-building programs for CBOs. METHODS: Based on our review of the literature, informal interviews with research-interested CBOs and community-engaged research groups locally and nationally, we developed a needs assessment survey. Key domains of this survey included history and experience with research collaboration, interest in specific research topics, and preference for learning format and structure. We trained community health workers (CHWs) to recruit senior leaders from CBOs in New York City (NYC) and encourage them to complete an on-line survey. RESULTS: Fully 54% (33/61) of CBOs completed the needs assessment. Most (69%) reported involvement with research or evaluation in the last 2 years and 33% had some funding for research. Although 75% had collaborated with academic institutions in the past, 58% did not rate this experience well. The four areas respondents prioritized for skills building were program evaluation, developing needs assessments, building surveys, and understanding statistical analyses. They were less interested in learning to build collaborations with academics. CONCLUSIONS: A formal needs assessment of research training and educational needs of CBOs revealed that most had experience, albeit negative, with academic collaborations. CBO leaders wanted to build skills to conduct and analyze assessments and program evaluations. Our community-academic partnership is using these findings to develop a research capacity-building course. Other partnerships should consider conducting such assessments to transform the capacity of CBOs to be active research partners and leaders.