Economic evaluation of clinical quality registries: a systematic review
Bibliographic record
Abstract
OBJECTIVES: The objective of this systematic review was to examine the existing evidence base for the cost-effectiveness or cost-benefit of clinical quality registries (CQRs). DESIGN: Systematic review and narrative synthesis. DATA SOURCES: Nine electronic bibliographic databases, including MEDLINE, EMBASE and CENTRAL, in the period from January 2000 to August 2019. ELIGIBILITY CRITERIA: Any peer-reviewed published study or grey literature in English which had reported on an economic evaluation of one or more CQRs. DATA EXTRACTION AND SYNTHESIS: Data were screened, extracted and appraised by two independent reviewers. A narrative synthesis was performed around key attributes of each CQR and on key patient outcomes or changes to healthcare processes or utilisation. A narrative synthesis of the cost-effectiveness associated with CQRs was also conducted. The primary outcome was cost-effectiveness, in terms of the estimated incremental cost-effectiveness ratio (ICER), cost savings or return-on-investment (ROI) attributed to CQR implementation. RESULTS: Three studies and one government report met the inclusion criteria for the review. A study of the National Surgical Quality Improvement Programme (NSQIP) in the USA found that the cost-effectiveness of this registry improved over time, based on an ICER of US$8312 per postoperative event avoided. A separate study in Canada estimated the ROI to be US$3.43 per US$1.00 invested in the NSQIP. An evaluation of a post-splenectomy CQR in Australia estimated that registry cost-effectiveness improved from US$234 329 to US$18 358 per life year gained when considering the benefits accrued over the lifetime of the population. The government report evaluating five Australian CQRs estimated an overall return of 1.6-5.5 times the cost of investment. CONCLUSIONS: Available data indicate that CQRs can be cost-effective and can lead to significant returns on investment. It is clear that further studies that evaluate the economic and clinical impacts of CQRs are necessary. PROSPERO REGISTRATION NUMBER: CRD42018116807.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.395 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.024 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.021 |
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; both teacher heads 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".