Four system enablers of large-system transformation in health care: a mixed methods realist evaluation

Emilie Francis-Auton, Janet C. Long*, Mitchell Sarkies, Natalie Roberts, Johanna Westbrook, Jean Frederic Levesque, Diane E. Watson, Rebecca Hardwick, Peter Hibbert, Chiara Pomare, Jeffrey Braithwaite

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
104 Downloads (Pure)

Abstract

Context: Large-scale transformative initiatives have the potential to improve the quality, efficiency, and safety of health care. However, change is expensive, complex, and difficult to implement and sustain. This paper advances system enablers, which will help to guide large-scale transformation in health care systems. Methods: A realist study of the implementation of a value-based health care program between 2017 and 2021 was undertaken in every public hospital (n = 221) in New South Wales (NSW), Australia. Four data sources were used to elucidate initial program theories beginning with a set of literature reviews, a program document review, and informal discussions with key stakeholders. Semi-structured interviews were then conducted with 56 stakeholders to confirm, refute, or refine the theories. A retroductive analysis produced a series of context-mechanism-outcome (CMO) statements. Next, the CMOs were validated with three health care quality expert panels (n = 51). Synthesized data were interrogated to distill the overarching system enablers. Findings: Forty-two CMO statements from the eight initial program theory areas were developed, refined, and validated. Four system enablers were identified: (1) build an authorizing environment; (2) provide relevant, authentic, timely, and meaningful data; (3) designate and distribute leadership and decision making; and (4) support the emergence of a learning culture. The system enablers provide a nuanced understanding of large-system transformation that illustrates when, for whom, and in what circumstances large-system transformation worked well or worked poorly. Conclusions: System enablers offer nuanced guidance for the implementation of large-scale health care interventions. The four enablers may be portable to similar contexts and provide the empirical basis for an implementation model of large-system value-based health care initiatives. With concerted application, these findings can pave the way not just for a better understanding of greater or lesser success in intervening in health care settings but ultimately to contribute higher quality, higher value, and safer care.

Original languageEnglish
Pages (from-to)183-211
Number of pages29
JournalMilbank Quarterly
Volume102
Issue number1
Early online date25 Dec 2023
DOIs
Publication statusPublished - Mar 2024

Bibliographical note

Copyright the Author(s) 2023. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • complex adaptive systems
  • enablers of transformative change
  • health care reform
  • implementation science
  • innovation
  • organizational change
  • realist evaluation

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