Document Type

Article

Publication Date

8-4-2019

Abstract

Purpose: To improve practices in rapidly changing environments, it is helpful to learn from relevant innovators. This article describes a well-defined and adaptable method for discovering innovative cases that inform best practices or positive/negative deviant research. Methods: As part of a national study of innovation in primary care settings, we developed a three-step method for identifying exemplar practices and applied that method to finding a sample of relevant innovators for in-depth case studies from which to draw transportable lessons about improving primary care practice. Results: Relevant, information-rich cases are uncovered using cycles of identification, sampling, and assessment. This cycle is repeated at each step of the defined three-step method. Step 1, a scan of the published literature, assesses both the state-of-the-art and the baseline characteristics of relevant cases; Step 2, a scan of practice settings, draws upon the expert knowledge of key informants to identify additional potentially relevant cases; and Step 3, sample refinement, evaluates potential cases for eligibility, purposeful diversity, and information-rich expressions of defined key domains. Using this three-step method, we identified a national cohort of primary care practice innovators. We found the method to be feasible, practical, and highly successful at identifying information-rich practices from which to draw transportable lessons about practice innovation. Conclusions: The three-step method outlines an effective sampling strategy for identifying innovation exemplars and information-rich cases that exceed measures of central tendency. By leveraging the collective knowledge of innovators, this method can support dynamic research and foster rapid cycle learning.

Keywords

practice innovation, primary care, qualitative methods, sampling strategy, workforce innovations

Language

English

Publication Title

International Journal of Qualitative Methods

Grant

68461

Rights

© The Author(s) 2019. This is an open access work distributed under the terms of the Creative Commons Attribution-Non-Commercial (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Creative Commons License

Creative Commons Attribution-NonCommercial 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

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