International Master's Program in health technology assessment and management: Assessment of the first edition (2001–2003)
Bibliographic record
Abstract
BACKGROUND: Despite a clear call for greater input from health technology assessment (HTA) in the areas of clinical practice and policy making, there are currently very few formal training programs. The objectives of our Consortium were to (i) develop a master's level program in HTA, (ii) test its content with a group of Canadian and European students, and (iii) evaluate the Program's strengths and weaknesses. OBJECTIVES: This study presents the results of our evaluation of the first edition of the Master's Program (2001--2003). METHODS: The evaluation relied on (i) a self-administered student questionnaire for each course (n = 142), (ii) interviews with students (n = 10), and (iii) interviews with internship supervisors (n = 5). RESULTS: A vast majority of students were satisfied with the course content and particularly appreciated the exercises and materials presented in an intensive format. However, they needed more systematic feedback from faculty members and recommended increasing the methodology content. The six key characteristics of the program are (i) flexible format adapted to the needs of skilled professionals, (ii) continuous interaction between HTA users and producers, (iii) international academic and professional collaboration, (iv) partnership with HTA agencies, (v) global approach to evidence-based methods and practices, and (vi) multidisciplinary approach. CONCLUSIONS: Despite the numerous organizational barriers inherent to creating an international program and several areas for improvement in the Program itself, the Ulysses Project was successful in attaining its objectives. Because there is a growing need for human resources with special training in HTA, further efforts need to be devoted to strengthening the international research capacity in HTA.
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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 | 0.014 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".