Development and Application of a Novel Framework for Clinician Stakeholder Engagement in Real-world Data (RWD) Studies
Author(s)
Lisa Herms, PhD1, Jennifer Frytak, PhD1, Paul Conkling, MD1, Jessica Paulus, ScD2;
1Ontada, Boston, MA, USA, 2Ontada, Senior Director, Boston, MA, USA
1Ontada, Boston, MA, USA, 2Ontada, Senior Director, Boston, MA, USA
Presentation Documents
OBJECTIVES: The relevance of effective stakeholder engagement to the integrity of RWD-based research has been recognized, with several frameworks published by PCORI, ISPOR/ISPE and others. Most of these guidance statements focus on the role of the patient stakeholder, yet clinicians play an especially important role in the generation and interpretation of RWD, given their proximity to the point-of-care where the data originates and role in understanding fitness-for-purpose. We therefore developed a conceptual framework for the integration of clinician stakeholder feedback into RWD investigations and report on three applied examples.
METHODS: Literature review identified multiple frameworks and best practices for stakeholder engagement, with an emphasis on patient perspectives. The applicability of these to the engagement of physicians in RWD-based studies were discussed with subject-matter experts. Leveraging these resources, we developed a framework for systematically integrating clinical stakeholder feedback into RWD-based research and applied it to the design of three RWD studies.
RESULTS: We identified three major categories of opportunities to integrate clinician feedback in RWD-based research investigations: 1) engaging qualitative clinician insights to interpret quantitative findings or tools, 2) engaging clinicians to set an agenda for a RWD investigation, and 3) establishing an iterative feedback loop between quantitative findings and qualitative practitioner insights and clinical priorities. Clinician feedback is particularly critical for protocol design, including conceptual and operational definitions of variables, design of data abstraction tools, interpretation of analytic output, and consideration of internal and external validity. More detailed results from applying this tool to three RWD oncology studies will be presented.
CONCLUSIONS: We developed a novel framework to improve the translational potential of RWD studies through engagement of clinician stakeholders. Integration of clinician perspectives has important implications for accelerating the impact of RWD-based research, including improvements in care quality, shared decision making and promoting clinical validity of novel methods such as generative artificial intelligence.
METHODS: Literature review identified multiple frameworks and best practices for stakeholder engagement, with an emphasis on patient perspectives. The applicability of these to the engagement of physicians in RWD-based studies were discussed with subject-matter experts. Leveraging these resources, we developed a framework for systematically integrating clinical stakeholder feedback into RWD-based research and applied it to the design of three RWD studies.
RESULTS: We identified three major categories of opportunities to integrate clinician feedback in RWD-based research investigations: 1) engaging qualitative clinician insights to interpret quantitative findings or tools, 2) engaging clinicians to set an agenda for a RWD investigation, and 3) establishing an iterative feedback loop between quantitative findings and qualitative practitioner insights and clinical priorities. Clinician feedback is particularly critical for protocol design, including conceptual and operational definitions of variables, design of data abstraction tools, interpretation of analytic output, and consideration of internal and external validity. More detailed results from applying this tool to three RWD oncology studies will be presented.
CONCLUSIONS: We developed a novel framework to improve the translational potential of RWD studies through engagement of clinician stakeholders. Integration of clinician perspectives has important implications for accelerating the impact of RWD-based research, including improvements in care quality, shared decision making and promoting clinical validity of novel methods such as generative artificial intelligence.
Conference/Value in Health Info
2025-05, ISPOR 2025, Montréal, Quebec, CA
Value in Health, Volume 28, Issue S1
Code
RWD49
Topic
Real World Data & Information Systems
Disease
SDC: Oncology