Adherence of Health Economic Evaluations to Country Specific Guidelines: A Protocol for Systematic Review
Bibliographic record
Abstract
Background & Objectives: Over the years, an increasing number of developed and developing countries have formulated guidelines for conduct of economic evaluations. However their relevance to the analyst has rarely been evaluated. It is unclear whether the analysts adopt a particular set of guidelines while undertaking economic evaluation, and if yes to what extent. We propose to undertake a systematic review to assess the adherence of the published economic evaluations to existing country specific guidelines for three countries. Depending on the availability of a published guideline in English language we randomly selected one country each in the high income, upper middle income and lower middle income group namely Canada, South Africa and Egypt Methodology: A systematic literature search will be undertaken in three databases which include PubMed, EmBase and York CRD databases to identify health economic evaluations pertaining to Canada, South Africa and Egypt. Two reviewers will independently undertake a title and abstract screening followed by full text screening to identify studies that are full economic evaluation pertaining to the health sector and published one year after the publication of the country specific guideline. Data will be extracted on key principles of economic evaluation. Adherence to the recommendation made in the country specific guidelines will be scored equally to calculate mean adherence scores. Quality will be assessed using Drummond’s checklist. Conclusion: The findings of this review will help to assess mean adherence to guidelines. Also, we will be able to identify individual factors showing poor adherence and factors responsible. Ultimately the findings will aid revision of existing guidelines and development of new guidelines.
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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 | 0.266 | 0.326 |
| Meta-epidemiology (narrow) | 0.006 | 0.008 |
| Meta-epidemiology (broad) | 0.019 | 0.019 |
| Bibliometrics | 0.020 | 0.024 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.052 | 0.012 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".