Enriched core competencies for health services and policy research—An update
Bibliographic record
Abstract
Objective: Doctoral and postdoctoral training in health services and policy research (HSPR) needs to evolve to address changing career trajectories, emerging health system challenges, and the advancement of learning health systems. This changing landscape necessitates examination of the core competencies that underpin training. This study presents a refreshed set of core competencies for HSPR to guide the modernization of training and considerations for implementation. Methods: Qualitative methods and an iterative development process with extensive community engagement throughout were used. Data were obtained from multiple sources, including literature reviews, surveys, key informant interviews, focus groups, Task Force meetings, a consensus workshop, and a validation process (Fall 2022 to May 2024). The study setting is Canada. Results: The refreshed core competencies include nine essential domains that maintain an emphasis on rigorous scholarly preparation and prioritize leadership and other professional skills deemed essential to contribute to evidence-informed system improvement and learning health systems. Additionally, the framework features two new transversal domains: Equity, Diversity, Inclusion, Accessibility, and Anti-Oppression; and Indigenous Cultural Safety and Humility. These domains are considered fundamental principles to be embedded into all aspects of HSPR competencies and training, fostering more inclusive and equitable leaders and health systems. Conclusions: As health systems continuously evolve, so too should the questions researchers address, the methods they use, and the skills needed to maximize contributions to evidence-informed health system improvement and learning health systems. The refreshed core competencies for HSPR maintain important continuity with the inaugural competency framework while also including several important additions. The framework allows for flexibility in its implementation and us; it can be used to guide the enhancement of existing training programs, the development of new ones, and the growth and development of a HSPR workforce with the skills to lead and contribute within learning health systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.054 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".