A systematic review of health economic evaluation quality assessment instruments for medical devices
Bibliographic record
Abstract
OBJECTIVES: Health economic evaluations are important for healthcare resource allocation. Reviews of health economic evaluations for medical devices have highlighted concerns about the quality of these studies. The complexity of medical devices, including learning curve effects, organizational impact, dynamic pricing, low evidence, and incremental innovation presents unique challenges compared with pharmaceuticals. To support developing a methodological quality assessment instrument for medical device economic evaluations, we conducted a systematic review to identify and evaluate existing economic evaluation quality assessment instruments for suitability in medical device evaluations. METHODS: A comprehensive search of databases (MEDLINE, EMBASE, EconLit, CINAHL, and Web of Science) and grey literature was conducted. Two reviewers screened titles and abstracts. Full-text, peer-reviewed primary studies introducing original instruments were included. Only methodological quality assessment instruments were considered for data extraction. Each item was assessed for its suitability in evaluating medical device economic evaluations and inclusion of medical device-specific features. RESULTS: The search identified 4203 citations and 77 grey literature sources. Fifteen results underwent full-text assessment, with five relevant instruments identified. A previous systematic review identified 10 additional instruments, which we also considered. Of these 25 articles, 13 were included in the review. These instruments lack specificity for medical devices, particularly in addressing features like learning curve effects, organizational impact, and incremental innovation. Instruments should include items specific to these unique characteristics. CONCLUSIONS: Existing instruments contain general items related to health economic evaluation studies, highlighting the need for an instrument specifically tailored to evaluate the methodological quality of medical device economic evaluation studies.
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 | 0.106 | 0.451 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.019 |
| Bibliometrics | 0.027 | 0.025 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.004 | 0.004 |
| 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; 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".