Experiences of Using Cochrane Systematic Reviews by Local HTA Units
Bibliographic record
Abstract
This study evaluated the use of Cochrane systematic reviews (CSRs) by Quebec's local health technology assessment (HTA) units to promote efficiency in hospital decision-making. An online survey was conducted to examine: Characteristics of the HTA units; Knowledge about works and services from the Cochrane Collaboration; Level of satisfaction about the use of CSRs; Facilitating factors and barriers to the implementation of CSRs evidence in a local context; Suggestions to improve the use of CSRs. Data accuracy was checked by 2 independent evaluators. Ten HTA units participated. From their implementation a total of 321 HTA reports were published (49.8% included a SR). Works and services provided by the Cochrane collaboration were very well-known and HTA units were highly satisfied with CSRs (80%-100%). As regards to applicability in HTA and use of CSRs, major strengths were as follow: Useful as resource for search terms and background material; May reduce the workload (eg, brief review instead of full SR); Use to update a current review. Major weaknesses were: Limited use since no CSRs were available for many HTA projects; Difficulty to apply findings to local context; Focused only on efficacy and innocuity; Cannot be used as a substitute to a full HTA report. This study provided a unique context of assessment with a familiar group of producers, users and disseminators of CSRs in hospital setting. Since they generally used other articles from the literature or produce an original SR in complement with CSRs, this led to suggestions to improve their use of CSRs. However, the main limit for the use of CRS in local HTA will remain its lack of contextualisation. As such, this study reinforces the need to consider the notion of complementarity of experimental data informing us about causality and contextual data, allowing decision-making adapted to local issues.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.308 | 0.538 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.011 | 0.016 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.005 | 0.020 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".