Cost Effectiveness of Natural Health Products: A Systematic Review of Randomized Clinical Trials
Bibliographic record
Abstract
Health care spending in North America is consuming an ever-increasing share of Gross Domestic Product (GDP). A large proportion of alternative health care is consumed in the form of natural health products (NHPs). The question of whether or not NHPs may provide a cost-effective choice in the treatment of disease is important for patients, physicians and policy makers. The objective of this study was to conduct a systematic review of the literature in order to find, appraise and summarize high-quality studies that explore the cost effectiveness of NHPs as compared to conventional medicine. The following databases were searched independently in duplicate from inception to January 1, 2006: EMBASE, MEDLINE, CINAHL, BioethicsLine, Wilson General Science abstracts, EconLit, Cochrane Library, ABI/Inform and SciSearch. To be included in the review, trials had to be randomized, assessed for some measure of cost effectiveness and include the use of NHPs as defined by the Natural Health Products Directorate. Studies dealing with diseases due to malnutrition were excluded from appraisal. The pooled searches unveiled nine articles that fit the inclusion/exclusion criteria. The conditions assessed by the studies included three on postoperative complications, two on cardiovascular disease, two on gastrointestinal disorders, one on critically ill patients and one on urinary tract infections. Heterogeneity between the studies was too great to allow for meta-analysis of the results. The use of NHPs shows evidence of cost effectiveness in relation to postoperative surgery but not with respect to the other conditions assessed. In conclusion, NHPs may be of use in preventing complications associated with surgery. The cost effectiveness of some NHPs is encouraging in certain areas but needs confirmation from further research.
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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 | 0.038 | 0.127 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.017 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".