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

Area of Science:

• Health Services Research
• Health Care Management
• Public Health Policy

Background:

• Large-scale health care initiatives aim to enhance quality, efficiency, and safety.
• Implementing and sustaining such initiatives is complex and challenging.
• This study identifies critical system enablers for guiding large-scale health care transformation.

Purpose of the Study:

• To identify and define system enablers for successful large-scale health care transformation.
• To provide a nuanced understanding of factors influencing the success of health care interventions.
• To develop an empirical basis for an implementation model of value-based health care initiatives.

Main Methods:

• A realist study was conducted on a value-based health care program in New South Wales, Australia (2017-2021).
• Data sources included literature reviews, document analysis, stakeholder discussions, and semi-structured interviews (n=56).
• Context-Mechanism-Outcome (CMO) statements were developed, refined, and validated with expert panels (n=51).

Main Results:

• Forty-two CMO statements were refined, leading to the identification of four overarching system enablers.
• The four key enablers are: building an authorizing environment, providing authentic and timely data, designating and distributing leadership, and fostering a learning culture.
• These enablers offer insights into the conditions under which large-system transformation is effective.

Conclusions:

• System enablers provide crucial guidance for implementing large-scale health care interventions.
• The identified enablers are potentially transferable to similar health care contexts.
• Application of these findings can lead to higher quality, higher value, and safer health care delivery.