Regulation of medical diagnostics and medical devices in the East African community partner states
Bibliographic record
Abstract
BACKGROUND: Medical devices and in vitro diagnostic tests (IVD) are vital components of health delivery systems but access to these important tools is often limited in Africa. The regulation of health commodities by National Regulatory Authorities is intended to ensure their safety and quality whilst ensuring timely access to beneficial new products. Streamlining and harmonizing regulatory processes may reduce delays and unnecessary expense and improve access to new products. Whereas pharmaceutical products are widely regulated less attention has been placed on the regulation of other health products. A study was undertaken to assess regulation of medical diagnostics and medical devices across Partner States of the East African Community (EAC). METHODS: Data was collected during October 2012 through desk based review of documents and field research, including face to face interviews with the assistance of a structured questionnaire with closed and open ended questions. Key areas addressed were (i) existence and role of National Regulatory Authorities; (ii) policy and legal framework for regulation; (iii) premarket control; (iv) marketing controls; (v) post-marketing control and vigilance; (vi) country capacity for regulation; (vii) country capacity for evaluation studies for IVD and (viii) priorities and capacity building for harmonization in EAC Partner States. RESULTS: Control of medical devices and IVDs in EAC Partner States is largely confined to national disease programmes such as tuberculosis, HIV and malaria. National Regulatory Authorities for pharmaceutical products do not have the capacity to regulate medical devices and in some countries laboratory based organisations are mandated to ensure quality of products used. Some activities to evaluate IVDs are performed in research laboratories but post market surveillance is rare. Training in key areas is considered essential to strengthening regulatory capacity for IVDs and other medical devices. CONCLUSIONS: Regulation of medical devices and in vitro diagnostics has been neglected in EAC Partner States. Regulation is weak across the region, and although the majority of States have a legal mandate to regulate medical devices there is limited capacity to do so. Streamlining regulation in the EAC is seen as a positive aspiration with diagnostic tests considered a priority area for harmonisation.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".