The Supply of Complementary and Alternative Medicine in Swiss Hospitals
Bibliographic record
Abstract
OBJECTIVES: Over the past few years, a considerable increase in complementary and alternative medicine (CAM) has been observed, particularly in primary care. In contrast little is known about the supply of CAM in Swiss hospitals. This study aims at the investigation of amount and structure of CAM activities of Swiss hospitals. MATERIALS AND METHODS: We designed a cross-sectional survey using a 2-step, questionnaire- based approach acquiring overview information form hospital managers in a first questionnaire leading to detailed information on CAM usage at medical department level (head of department). This second questionnaire provides data of physician-based and non-physician-based CAM supply. RESULTS: The size of hospitals was significantly associated with the provision of CAM. 33% of the hospital managers indicated 1 or more medical doctor (MD) using CAM in their hospital compared to 37% of confirmation on department level (Kappa value 0.5). Mostly different CAM methods were applied. Acupuncture was used most frequently. However only 13 hospitals (11%) occupied more than 3 CAM MDs and only 5 hospitals had more than 2 full-time equivalents for MDs. Furthermore, 74.7% of these personnel resources were dedicated for outpatient care. In terms of CAM methods anthroposophic medicine accounted for more than half of the total personnel costs. On the other hand usage of non-physician based CAM accounted for 41% according to hospital managers compared to 64% of CAM usage according to medical departments (Kappa values 0.31). Reflexology of the foot was used most frequently. CONCLUSION: Total supply of CAM in Swiss hospitals is low and concentrates on few hospitals. Acupuncture is the widest spread discipline but anthroposophic medicine spends the most resources. The study shows that a high patient demand for CAM faces low supply in hospitals.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".