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The group organization score: a pragmatic tool for organizational assessment, monitoring, and improvement in implementation practice

Nicholas A. Rattray, Edward J. Miech, Dawn M. Bravata, Sean A. Baird, Teresa M. Damush

Frontiers in Health Services · 2026-11-04 · 6

DOI: 10.3389/frhs.2026.1978632 ↗
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Implementation science has generated a wide range of theories, models, and frameworks to explain implementation processes, yet comparatively fewer pragmatic tools are available to assess how multidisciplinary teams organize, coordinate, and evolve over time. In practice, investigators often develop low-burden approaches to monitor implementation progress, support decision-making, and facilitate organizational learning, but these tools are rarely described in detail or disseminated beyond individual projects. We present the Group Organization (GO) Score, a pragmatic, structured assessment method designed to evaluate the extent to which teams function as coordinated, facility-level units during implementation and quality improvement efforts. The GO Score captures organizational coordination, team cohesion, and the development of shared structures and processes, complementing approaches that focus on individual attitudes or discrete implementation activities. We describe the development, structure, scoring procedures, and iterative refinement of the GO Score across multiple implementation applications within the US Department of Veterans Affairs. Drawing on three illustrative cases, we demonstrate how the tool was used to characterize organizational development, monitor implementation progress, assess the normalization of new care models, and support continuous organizational improvement through audit and feedback. Across these applications, the GO Score evolved from a framework for describing organizational development into a pragmatic implementation tool that enabled longitudinal assessment, cross-site comparison, and learning health system activities. This manuscript documents how the GO Score functions in practice, outlines contexts in which it appears most useful, provides three applied examples and discusses its strengths and limitations as a low-burden, context-sensitive method.

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