The Effect of Introducing Rebate Contracts to Promote Generic Drug Substitution, on Doctors’ Prescribing Practices
Bibliographic record
Abstract
BACKGROUND: As of 1 April 2007, pharmacists in Germany filling prescriptions covered by the statutory health insurance system (Gesetzliche Krankenversicherung, GKV) are required, whenever possible, to dispense a preparation that contains the same active substance and for which a rebate contract is in effect. The physician can block drug substitution by crossing out "aut idem" ("or the like") on the prescription form. The latter option has existed since 2002. We studied the possible effect of the introduction of rebate contracts on the use of the no-substitution option. METHODS: Three independent random samples were taken from the routine data of the Gmünder ErsatzKasse (GEK, a statutory health insurance carrier). The samples consisted of 0.5% of the insured adult population in the month of October in the years 2006, 2007, and 2008 (n = 6195; n = 6300; n = 6845). Within these sample groups, all medication orders in which the physician could potentially have exercised a no-substitution option were selected, and the corresponding prescriptions were examined. RESULTS: The percentage of no-substitution prescriptions rose from October 2006 to October 2007, and then rose still further to October 2008 (14.4%, 18.4%, 19.0%; p for trend < 0.0001). Considerable differences were seen between physicians belonging to different regional Associations of Statutory Health Insurance Physicians (Kassenärztliche Vereinigungen). In about one-quarter of the no-substitution prescriptions for 2007 and 2008 (25.1%, 25.7%), the prescribed medication was itself included in a rebate contract. CONCLUSIONS: The use of the no-substitution option is not uniform across Germany at present. Rebate contracts and the no-substitution option require further evaluation. Moreover, the dispensing of medications urgently needs a more stable regulatory framework.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".