Comparison of the assessment of five new interventional procedures in different countries
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to identify and compare health technology assessments of the same new interventional procedures produced in different countries. METHODS: We selected five new interventional procedures and studied related assessments produced in different countries. RESULTS: There were twenty assessments (range, 3-5 per procedure) from nine countries--fourteen from Australia, Canada, and United Kingdom. The number of primary RCTs cited by the assessments ranged from 0 to 13. In the assessment reports, "headline" statements about the strength of evidence for efficacy (73 percent) were made more frequently than for safety (53 percent). These statements were scored for their apparent judgment of the strength of the evidence--1 (poor) to 5 (strong)--and received scores of 3 or less in all but four cases. Recommendations about additional research were included in 55 percent of the assessments. Statements in assessments about other aspects of use of the procedures were included more infrequently--in 35 percent for patient selection, in 20 percent for consent issues, and in 15 percent for types of clinical teams. Recommendations about appropriate healthcare settings, or about operator training, were included only in assessments produced by a single organization. CONCLUSION: There was a only small number of assessments world-wide, for a range of new procedures with potentially high impact. Where available, assessments were produced on a relatively poor evidence base. International collaboration in evidence appraisal and review, and in the gathering of new data through research or registers, could improve the advice available to healthcare systems worldwide about the adoption of new interventional procedures.
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 | 0.077 | 0.243 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.017 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".