IMIA Accreditation of Biomedical and Health Informatics Education: Current State and Future Directions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Summary Objectives: The educational activities initiated by the International Medical Informatics Association (IMIA) have had global impacts and influenced national societies and local academic programs in the field of Biomedical and Health Informatics (BMHI). After the successful publication and dissemination of its educational recommendations, IMIA launched an accreditation procedure for educational programs in BMHI. The accreditation procedure was pilot tested by several BMHI academic programs in different countries and continents to obtain a global perspective. Methods: This paper presents an overview of IMIA quality assurance and accreditation procedures along with feedback on issues and problems which emerged during the pilot. Results: It appears that IMIA quality assurance and procedures worked quite well in different countries of Europe, the Middle East, South America, and Asia. These first experiences provided adequate information for adapting, modifying, and optimizing the procedures and finally for the planning of future activities. Conclusions: IMIA accreditation framework comprises a single set of standards that apply at various levels to both academic and professional BMHI programs. The pilot phase confirmed the robustness and generalizability of quality assurance standards and associated procedures on which IMIA accreditation is based at an international level.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it