Quality circles for pharmacotherapy to modify general practitioners' prescribing behaviour for generic drugs
Bibliographic record
Abstract
RATIONALE, AIMS AND OBJECTIVES: In Austria, the participation of general practitioners (GPs) in so-called 'quality circles for pharmacotherapy' (QCPs) was taken as a special approach to increase the use of generics and possibly, to improve the quality and efficiency of prescribing patterns in primary care. This study aimes at exploring GPs' perception of QCPs whether they think that taking part has helped to change their prescribing habits, their opinions on generics in general and the issues that arise for them in attempting to promote their use. METHODS: Qualitative analysis was used to evaluate QCP protocols for their potential to evoke discussion in the group and for their relevance to our study questions. RESULTS: Of the 821 self-employed GPs in Vienna under contract with the Vienna District Health Insurance Fund 445 took part at least once in the study period. Seven main topics, which provide insight into various aspects of patient care in primary care, were identified: QCPs work, generic drug prescription, problems related to the sale of generics, patient counselling and education, therapy adherence, coordination of care, competence and medical education. From all prescribed drugs for which generics were available in the fourth quarter of the year 2003 GPs prescribed 33.91% generics, in the fourth quarter of 2004 43.97%, in the fourth quarter of 2005 46.31%, and in the fourth quarter of 2006 49.88%. CONCLUSIONS: Peer review groups can be an important method of quality improvement in GPs' prescribing behaviour in favour of generics. QCPs also facilitate the exchange between GPs on problems encountered and provide feedback to policy makers.
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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 | 0.034 | 0.102 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".