OP33 Expectations, Needs And Challenges Of Setting Up An International Collaboration On Horizon Scanning For Medical Devices
Bibliographic record
Abstract
Introduction International collaboration on horizon scanning for medical devices is seen as desirable, because the development of medical devices is not limited to the national level, and horizon scanning for medical devices on a country-level can be challenging due to scarcity and diversity of information. The International Horizon Scanning Initiative Medical Devices Working Group (IHSI MDWG) was set up in June 2021. The objective of this study was to research the expectations and experiences of the participants of this initiative, in order to reflect on the possibilities and challenges of governing innovative medical technologies. Methods A questionnaire was sent out to 10 purposively selected representatives of the IHSI MDWG participating counties: Austria, Belgium, Canada, Denmark, Italy, Luxembourg, Netherlands, Norway, Portugal, and Sweden. The survey covered individual countries’ respective purposes for an international horizon scanning system as well as questions related to the desired scope and perceived challenges of such a system. The questionnaire was supplemented with online, semi-structured, in-depth interviews with the same representatives from each participating country. These interviews provided for diving deeper into the survey topics as well as discussing the relation between horizon scanning and health technology assessment, the relation to other international horizon scanning collaborations, and the relation between an international versus a national horizon scanning system. In addition, participant observations were conducted at the Dutch National Health Care Institute and during IHSI MDWG working group meetings. Results Preliminary results are discussed first with participants after which we will draw our final conclusions and recommendations for practice. Our analysis focuses on exploring participants’ expectations and experiences with international horizon scanning through triangulating the three sources of data in our analysis. Conclusions The study will report on the expectations, needs and challenges of setting up an international collaboration for horizon scanning of medical devices and reflect on the regulation and governance of innovative medical technologies across several countries in Europe and Canada.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".