Four System Enablers of Large‐System Transformation in Health Care: A Mixed Methods Realist Evaluation.

Policy PointsThe implementation of large‐scale health care interventions relies on a shared vision, commitment to change, coordination across sites, and a spanning of siloed knowledge.Enablers of the system should include building an authorizing environment; providing relevant, meaningful, transpare...

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Published in:Milbank Quarterly Vol. 102; no. 1; pp. 183 - 212
Main Authors: FRANCIS‐AUTON, EMILIE, LONG, JANET C., SARKIES, MITCHELL, ROBERTS, NATALIE, WESTBROOK, JOHANNA, LEVESQUE, JEAN‐FREDERIC, WATSON, DIANE E., HARDWICK, REBECCA, HIBBERT, PETER, POMARE, CHIARA, BRAITHWAITE, JEFFREY
Format: Article
Published: Wiley-Blackwell Mar2024
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Online Access:View this record in EBSCOhost
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      dt: Mar2024
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        10.1111/1468-0009.12684
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        atl: Four System Enablers of Large‐System Transformation in Health Care: A Mixed Methods Realist Evaluation.
      aug:
        au:
          FRANCIS‐AUTON, EMILIE
          LONG, JANET C.
          SARKIES, MITCHELL
          ROBERTS, NATALIE
          WESTBROOK, JOHANNA
          LEVESQUE, JEAN‐FREDERIC
          WATSON, DIANE E.
          HARDWICK, REBECCA
          HIBBERT, PETER
          POMARE, CHIARA
          BRAITHWAITE, JEFFREY
        affil:
          Australian Institute of Health Innovation, Macquarie University
          Centre for Primary Health Care and Equity, University of New South Wales
          Bureau of Health Information, St. Leonards
          Peninsula Medical School, University of Plymouth
      su:
        New South Wales
        Corporate culture
        Patient safety
        Diffusion of innovations
        Leadership
        Interviewing
        Decision making
        Learning
        Uncertainty
        Organizational effectiveness
        Communication
        Organizational change
        Health facilities
        Authority
        Employee retention
        Public hospitals
        Research funding
        Value-based healthcare
        Descriptive statistics
        Health care reform
        Research methodology
        Quality assurance
      sug:
        subj:
          Corporate culture
          Patient safety
          Diffusion of innovations
          Leadership
          Interviewing
          Decision making
          Learning
          Uncertainty
          Organizational effectiveness
          Communication
          Organizational change
          Health facilities
          Authority
          New South Wales
          All Other Outpatient Care Centers
          General Medical and Surgical Hospitals
          Employee retention
          Public hospitals
          Research funding
          Value-based healthcare
          Descriptive statistics
          Health care reform
          Research methodology
          Quality assurance
      keyword:
        complex adaptive systems
        enablers of transformative change
        health care reform
        implementation science
        innovation
        organizational change
        realist evaluation
        complex adaptive systems
        enablers of transformative change
        health care reform
        implementation science
        innovation
        organizational change
        realist evaluation
      ab: Policy PointsThe implementation of large‐scale health care interventions relies on a shared vision, commitment to change, coordination across sites, and a spanning of siloed knowledge.Enablers of the system should include building an authorizing environment; providing relevant, meaningful, transparent, and timely data; designating and distributing leadership and decision making; and fostering the emergence of a learning culture.Attention to these four enablers can set up a positive feedback loop to foster positive change that can protect against the loss of key staff, the presence of lone disruptors, and the enervating effects of uncertainty. 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. Semistructured 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.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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