Table 1
Barriers to a continuum of competency-based health professions education and root causes that align with Meadows’ leverage points*.
| BARRIER | EXPLANATION OF BARRIER | ROOT CAUSE/DRIVER | LEVERAGE POINT GROUPING | SPECIFIC LEVERAGE POINTS |
|---|---|---|---|---|
| Siloing across HPE continuum levels | Lack of alignment among undergraduate/ graduate/ continuing education, with abrupt, disruptive transitions; leadership & governance structures remain separate and distinct. | Historical development of independent systems, separate program leaders, jurisdictional (governing authorities, regulatory bodies) control differences | Design Intent | Rules (governance structures), Goals (competing priorities across stages) |
| Siloing within HPE continuum levels | Schools, postgraduate education programs, and continuing professional development lack alignment even within the same stage/country, with inconsistent standards and approaches. | Decentralized control, institutional autonomy, lack of coordinating mechanisms | Design Intent | Rules (accreditation standards), Goals (institutional/program/department vs. system priorities) |
| Time-based structures | Fixed training durations, inflexible transition points (graduation, match), clinical service needs requiring uninterrupted coverage | Legacy systems prioritizing predictability, service delivery requirements, administrative efficiency. | Parameters Design | Rules (regulatory requirements), Parameters (duration requirements) |
| Siloed assessment systems | Non-integrated data platforms, technology disparities, privacy/fairness concerns about cross-stage information sharing, competition for limited specialist positions forces normative judgments | Technical infrastructure limitations, privacy regulations, institutional competition | Feedback Design | Feedback flows (assessment data), Rules (privacy regulations) |
| Resource constraints and scarcity | Limited training positions creating competition, insufficient faculty time for individualized approaches, inadequate funding for integrated systems and personalized progression | Finite resources (positions, faculty, funding), growing demand with program expansions, economic pressures, competing priorities for resource allocation | Parameters Design | Parameters (resource allocation), Rules (funding distribution), Goals (efficiency vs. individualization) |
| Faculty development fragmentation | Few educators are prepared to teach/assess longitudinally across the continuum; training focuses narrowly on a single stage; continuing professional development is often separate from faculty educator development. | Specialized expertise model, limited career incentives for cross-continuum work | Design Intent | Goals (faculty development priorities), Rules (promotion criteria) |
| Limited individualized learning and progression capacity | Faculty workload, clinical demands, scheduling constraints preventing accommodation of variable-rate learners | Resource constraints, efficiency pressures, traditional batch-processing model | Parameters Design | Parameters (resource allocation), Rules (scheduling systems) |
| Misaligned accountabilities and outcomes | Short-term performance priorities (graduate on time, match success), lack of longitudinal competence tracking, unclear readiness definitions | External pressure for immediate outcomes, measurement challenges, stakeholder expectations | Intent Feedbacks | Goals (accountability metrics), Feedback flows (outcome measurement) |
| High-stakes examination requirements | National board/licensing exams and maintenance of certification requirements anchor programs to time-based, summative judgments rather than longitudinal competence assessment | Regulatory gatekeeping function, standardization needs, public protection mandate | Design Intent | Rules (licensing requirements), Goals (standardization vs. individualization) |
| Time-based funding models | Government/institutional funding structured by credit hours, tuition by semester/year rather than competence achievement | Financial system architecture, budgeting predictability, administrative simplicity | Parameters Design | Parameters (funding formulas), Rules (financial regulations) |
| Learner mindset and understanding | Performance vs. growth orientation, fear of high-stakes transitions, inconsistent CBHPE implementation creating confusion | Assessment culture, high-stakes environment, implementation variability | Intent Feedbacks | Intent (learning culture), Feedback flows (assessment approaches) |
| Cultural resistance and identity | Adherence to tradition, educator/program identities focused on single stages, fear of unintended consequences. | Historical precedent, professional identity formation, risk aversion, change management challenges | Intent | Intent (fundamental beliefs about education), Goals (preservation vs. innovation) |
[i] *Meadows D. Leverage Points: Places to Intervene in a System. The Donella Meadows Project. 1999. https://donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/ (accessed 1 December 2025).
Table 2
Meadows’ 12 Leverage Points* Applied to Health Professions Education.
| MEADOWS’ LEVERAGE POINTS | DEFINITION SPECIFIC TO HEALTH PROFESSIONS EDUCATION | EXAMPLES FOR HEALTH PROFESSIONS EDUCATION |
|---|---|---|
| Parameters: numbers, metrics. Easiest to change but least effective leverage points. | ||
| 12. Constants, parameters, numbers | - Quantifiable aspects of the system that affect its performance but rarely transform its structure or goals. - Focus on numbers like budgets, staffing, or resource allocation. | - Number of trainees and teachers. - Number of clinical rotations. - Time spent on a rotation. - Amount of protected teaching time. - Annual budget for education. - Standardized test scores. - Per trainee funding. - Number of continuing professional development credits. |
| 11. Sizes of buffers (something that cushions the impact of something else) | - Resource capacity to absorb disruptions in HPE without diminishing quality or outcomes. Too-small buffers increase risk; too-large buffers create inefficiencies. | - Having enough teaching faculty - Clinical site availability - Flexible room booking systems for teaching and clinical care. - Sufficient patients for trainees in different seasons |
| 10. Structure of material stocks and flows and nodes of intersection (physical layout of the system and interconnections within the system) | - Physical and organizational infrastructure for HPE. | - Educational system covering undergraduate, graduate/postgraduate (or in some health professions, a single education phase) and continuing professional development phases. - Design and capacity of buildings (e.g., hospitals, clinics, universities). - Competing interests like patient care, education, and research. - Continuing professional development occurring off-site in conferences rather than directly within the work environment. |
| Feedback: interactions within the CBHPE system, including positive and negative feedback loops. | ||
| 9. Lengths of delays relative to rate of system change | - Timing mismatches between curricular or other education actions and observable results. Long delays prevent timely correction; short delays improve adaptability. | - Long delays between trainee performance and feedback (e.g., exam results weeks later). - Real-time dashboards for EPAs reduce lags. - Curriculum updates and subsequent change in trainee performance - Timely workplace-based assessments support immediate feedback for trainees. - Residency programs shortening promotion timelines after competency achievement. - Faculty feedback review and action plans reviewed at time of promotion rather than continuously. |
| 8. Strength of negative feedback loops | - Balancing loops that self-correct the system. Weak loops fail to stabilize; strong loops promote individual and system resilience. | - Formative assessments guide trainee correction before summative failures. - Structured mentorship programs provide self-corrective mechanisms. - Accreditation requirements lead to program improvements - Remediation programs stabilize trainee progression. - Simulation case debriefs allow guided reflection and feedback. |
| 7. Gain around positive feedback loops | - Reinforcing loops amplify growth or improvements in learners and programs. | - Awards, leadership roles, or scholarships support trainee growth. - Teaching awards motivate faculty teachers. - “Fast track” programs for high-performing trainees/residents. - Scholarly productivity leading to program reputational strength or trainees securing desired matches and faculty positions |
| Design: structure and social structure of the CBHPE system. | ||
| 6. Structure of information flows | - Changing access to information (feedback, performance data) transforms system behavior. Transparency, timely feedback, and distributed decision-making improve a competency-based education system. | - Transparent dashboards for EPAs, milestone progression, and competency tracking. - Real-time feedback from patients and clinical encounters shared with trainees. - Learning analytics tools identify struggling trainees early. - Peer-to-peer formative assessments. - Sharing performance data across sites to reduce siloed feedback. - Faculty teaching evaluations used in advancement decisions. |
| 5. Rules of the system (incentives, constraints, policies) | - Policies, accreditation standards, advancement criteria, and financial incentives define what is possible in the system. Changing rules reshapes system behavior. | - Residency selection based on competency progression rather than fixed timelines. - Programmatic assessment policies including EPA entrustment rules. - Policy revisions to support remediation as part of learning and progression. - Protected time policies for preceptors and coaches. - Admissions reforms to reduce structural bias and foster inclusion. - Licensing exam policies. |
| 4. Power to add, change, or self-organize system structure | - Ability of the system to evolve by creating new substructures, relationships, or novel components. Enables adaptive change and resilience. | - Trainees co-developing assessment rubrics and curricular content. - Development of distributed leadership teams in educational governance. - Emergence of longitudinal coaching roles. - Interprofessional faculty dyads and grassroots curriculum innovations. - Introduction of assessment tools and data analytics that use artificial intelligence (AI) |
| Intent: underlying values and goals of the CBHPE system. Deepest, most impactful leverage points. | ||
| 3. Goals | - The primary goal of the system is to improve health and healthcare, which determines its behavior and outcomes. | - Preparing trainees for team-based, patient-centered care. - Preparing trainees for AI-enriched clinical practice. - Supporting lifelong learning and adaptive expertise. - Encouraging trainees to practice in areas of societal need |
| 2. Mindsets out of which system arises | - Fundamental beliefs, values, and assumptions that define system goals, structure, and rules. Changing mindsets requires letting go of traditions and old ways of thinking. | - Fixed vs growth mindset for trainees and educators. - Value placed on individual progress versus time-based progression. - Prioritization of interprofessional team-based care - Teacher as facilitator of learning rather than expert imparting knowledge (constructivist paradigm). |
| 1. Power to transcend paradigms | - Ability to step outside prevailing paradigms and adopt new ways of thinking and operating. Challenges deeply held beliefs and fosters transformative change. | - Outcomes-based (vs. time-based) education. - Questioning the role of standardized exams and uses of scores. - Transforming the role of technology in education and health care - Quality and safety movements reshaping HPE. |
[i] *Meadows D. Leverage Points: Places to Intervene in a System. The Donella Meadows Project. 1999. https://donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/ (accessed 1 December 2025).