Table 3.

T-CaST high ranking frameworks and assessment

Framework number and name	2	6	8	10	11
	THENet framework	EPIS framework	Learning Health System	Realist framework of social accountability in health services	Realist framework of the relationship between communities and medical education
Average score (total score/number of characteristics)	1.75	1.63	1.63	1.75	1.81
Average adjusted score (adjusted score/number of characteristics)	1.67	1.67	1.67	1.83	1.75
How will you apply the information from this tool? (e.g., Which TMF(s) did you select? What is your rationale for selecting the TMF(s)?	Strengths: Familiar to medical education stakeholders, in particular northern and rural stakeholders Helpful, explicit implementation guide (processes and outcome measures) and logic model Pilot tested, refined, revised Challenges: Unclear of how to embed continuous learning and ongoing monitoring and improvement Research study oriented, would prefer nimble and embedded approach Adapt and combine: An explicit implementation plan, with metrics and processes to collect data, are important to align with final framework. This framework has international recognition, and the collaboration includes Northern Ontario School of Medicine. Requires more explicit, precise description of responsiveness, and more emphasis on accountability processes.	Strengths: Well- established implementation framework with empirical evidence Provides significant resources to design, implement, and evaluate theory and process in public sector settings Challenges: Implementation framework does not specifically consider learning outcomes or formalized educational processes Adapt and combine: This implementation framework intends to support researchers and practitioners in implementing evidence-based innovations. It will be helpful to examine how specific social accountability interventions or innovations are implemented, and how that might affect outcomes for different stakeholders (at different levels).	Strengths: Familiar language of “learning health system” in academic medicine and health services Identifies values, processes, outcomes that are key for continuously improving health system Challenges: Does not consider education or training of health professionals in processes or outcomes Need to examine how/if values of social accountability and shared accountability compare Smallest unit of analysis is organization (not individual) Adapt and combine: This conceptual framework explicitly describes the structures, processes, and outcomes to enable and embed continuous improvement in health systems, and offers ways to align distinct “eco-systems” to bring value to health systems and people. This framework offers insight to optimize organizational and system learning, wish an emphasis on creating and sharing evidence. There is no explicit consideration of health professional education or training.	Strengths: Realist framework provides underlying theory of change to support improvements Includes individual-level Challenges: Particularly developed in low-income health services settings Does not include an element about medical education Adapt and combine: This framework describes the steps of accountability, which none of the other frameworks have considered. This is helpful for categorizing social accountability activities and intervention, and understanding the “object of change.” Focus is mainly on relationships between communities and health service providers at the organization-level.	Strengths: Realist framework provides underlying theory of change to support improvements Lists specific outcomes relevant to medical education, “communities”, and other stakeholders Highlights importance of defining “communities”, relationships, and understanding power dynamics Developed by Northern Ontario leaders Challenges: Complex network analysis might be challenging to align with outcomes and measure Role of organization or system learning not explicitly captured Adapt and combine: The network diagram depicts relationships between actors and activities, which describes the multiple levels of context. The description of mechanisms for different actors will help understand why certain outcome patterns occurred. How to monitor and rapidly learn in this network is not clear according to this model.