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A scoping review of de-implementation frameworks and models.

Callie Walsh-Bailey1, Edward Tsai2, Rachel G Tabak3

  • 1Prevention Research Center, Brown School, Washington University in St. Louis, One Brookings Drive, Campus Box 1196, St. Louis, MO, 63130, USA. callie.w@wustl.edu.

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Summary

This scoping review identified 27 frameworks and models (FM) for studying de-implementation in healthcare and public health. Researchers should utilize existing FM rather than developing new ones to advance de-implementation science.

Keywords:
De-adoptionDe-implementationDisinvestmentFrameworkHealthLow-valueModelObsolescenceScoping review

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Area of Science:

  • Healthcare Management
  • Public Health Policy
  • Implementation Science

Background:

  • Effective resource allocation necessitates reducing or eliminating inappropriate, ineffective, or harmful healthcare services and public health programs.
  • Frameworks and models (FM) are crucial for conceptualizing and guiding the study of de-implementation.
  • This scoping review aimed to identify and characterize FM applicable to de-implementation research and highlight literature gaps.

Purpose of the Study:

  • To identify and characterize frameworks and models (FM) for studying de-implementation.
  • To identify gaps in the literature regarding FM for de-implementation.
  • To inform future model development and application in de-implementation research.

Main Methods:

  • A comprehensive search of nine databases and eleven journals across multiple disciplines was conducted.
  • Studies published between 1990 and June 2020 were screened by two independent raters.
  • Data extraction focused on setting, discipline, study design, methodology, and FM characteristics.

Main Results:

  • Twenty-seven unique frameworks and models (FM) were identified from 27 articles.
  • Most FM (n=21) were applicable to multiple levels of the Socio-Ecological Framework, with organizational-level constructs being most common (n=18).
  • Eighteen FM depicted linear relationships, while fewer showed complex structures; 13 FM were used in empirical studies, and 14 were commentary or review papers.

Conclusions:

  • De-implementation is studied across disciplines, but implementation science has limited integration of cross-disciplinary learnings.
  • This review provides an overview of visual representations of FM for implementation researchers and practitioners.
  • Further research is needed to test and refine existing FM and assess their applicability across different contexts; building upon existing FM is recommended over creating novel ones.