Attitudes of Slovene general practitioners towards generic drug prescribing and comparison with international studies
Bibliographic record
Abstract
BACKGROUND: Over the recent years there has been a steady 7% yearly increase in prescribing costs, which accounts for 17% of the Slovene national health care budget. Substitution of branded products by generic equivalents can offer savings. General practitioners (GPs) are often concerned about the quality of generic products and possible legal liabilities associated with their use. OBJECTIVE: We wanted to examine the attitudes of GPs in Slovenia towards generic drug prescribing. METHODS: We conducted a postal survey of a random sample of 200 out of 800 GPs in Slovenia from the National Health Insurance Institute database. GPs were asked 21 questions regarding their knowledge on generic drugs, awareness of prescribing costs, prices of generic drugs relative to brand name drugs and their attitude towards use of generic drugs. RESULTS: The 117 (58.5%) replies we received represent 15% of the GP population in Slovenia. 66.1% of GPs considered rising costs of medicines to be a serious problem for the health care budget. Each week, over 50% of GPs experienced demands from patients for specific drugs and the majority of GPs usually met their patients' demands or requests from hospital consultants for branded products. 38.3% of GPs did not take price into consideration when prescribing drugs. The majority of GPs (88.9%) perceived generics to have the same effectiveness as branded drugs. One quarter of GPs would prescribe more generics if additional clinical trials were presented. 37.3% would follow advice of academic detailers and 30.3% expected the generics to be even cheaper than they were. Independent detailing was welcomed by 63.8% of GPs because of the big influence of the pharmaceutical industry on the prescribing habits. 15.5% thought that the industry had a tremendous impact on their prescribing patterns. CONCLUSIONS: Slovene GPs are aware of the cost of prescribed drugs. They are willing to accept independent academic detailing to improve their prescribing and are willing to increase generic drugs under certain conditions.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".