Developing a Policy and Procedure Framework and Manual for a National Comprehensive Implantable Medical Device Registry in Saudi Arabia
Bibliographic record
Abstract
Policy and procedure manuals provide guidance on the operation and governance of medical device registries. In Saudi Arabia, the Saudi Food and Drug Authority (SFDA) has been developing and implementing a comprehensive national registry for implantable medical devices to facilitate the monitoring of device outcomes through post-market surveillance studies. To help guide the operations of this registry, the SFDA developed a policy and procedure manual. This paper reports on the design of the framework used to develop that manual over the course of one year (2015-2016), using a variety of literature sources, and working with medical device registry and health systems experts. The policy and procedure manual included five key principal level categories, which led to the subsequent creation of seven policies and 28 relevant procedures. The five principal categories were: Staff Engagement, Information Governance, Quality and Auditing, Research, and Reporting. The results of this work could be used to guide the development of policies and procedures for other implantable medical device registries.
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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 | 0.311 | 0.197 |
| Meta-epidemiology (narrow) | 0.001 | 0.003 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.017 | 0.010 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.017 | 0.016 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.013 | 0.007 |
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".