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A logic model for precision medicine implementation informed by stakeholder views and implementation science

Abstract

Purpose

Precision medicine promises to improve patient outcomes, but much is unknown about its adoption within health-care systems. A comprehensive implementation plan is needed to realize its benefits.

Methods

We convened 80 stakeholders for agenda setting to inform precision medicine policy, delivery, and research. Conference proceedings were audio-recorded, transcribed, and thematically analyzed. We mapped themes representing opportunities, challenges, and implementation strategies to a logic model, and two implementation science frameworks provided context.

Results

The logic model components included inputs: precision medicine infrastructure (clinical, research, and information technology), big data (from data sources to analytics), and resources (e.g., workforce and funding); activities: precision medicine research, practice, and education; outputs: precision medicine diagnosis; outcomes: personal utility, clinical utility, and health-care utilization; and impacts: precision medicine value, equity and access, and economic indicators. Precision medicine implementation challenges include evidence gaps demonstrating precision medicine utility, an unprepared workforce, the need to improve precision medicine access and reduce variation, and uncertain impacts on health-care utilization. Opportunities include integrated health-care systems, partnerships, and data analytics to support clinical decisions. Examples of implementation strategies to promote precision medicine are: changing record systems, data warehousing techniques, centralized technical assistance, and engaging consumers.

Conclusion

We developed a theory-based, context-specific logic model that can be used by health-care organizations to facilitate precision medicine implementation.

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ACKNOWLEDGEMENTS

Funding was provided by the Veterans Affairs Health Services Research and Development Service for the field-based meeting “Defining Outcomes and Metrics for Precision Medicine” (44497/BIS 2753). C.C.-C. was supported by the Veterans Affairs Office of Academic Affiliations through the Advanced Fellowship in HSR&D. C.I.V. was supported by a Research Career Scientist Award from the Health Services Research and Development service of the Department of Veterans Affairs (RCS 14-443). E.M.Y. was funded by a Veterans Affairs HSR&D Senior Research Career Scientist Award (project number RCS 05-195). We thank the conference participants and VHA staff who provided logistical support.

Author information

Correspondence to Maren T. Scheuner MD, MPH.

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DISCLOSURE

The authors declare no conflicts of interest.

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Key words

  • precision medicine
  • logic model
  • implementation
Fig. 1: Flow chart summarizing the coding and analysis of the conference proceedings.
Fig. 2: Logic model for precision medicine implementation informed by key stakeholders.
Fig. 3: Number of participants contributing to the logic model concepts by stakeholder group.