The impact on health outcome measures of switching to generic medicines consequent to reference pricing: the case of olanzapine in New Zealand
Bibliographic record
Abstract
INTRODUCTION: New Zealand's Pharmaceutical Management Agency (PHARMAC) manages the list of medicines available for prescribing with government subsidy, within a fixed annual medicines budget. PHARMAC achieves this through a mix of pricing strategies including reference pricing. In 2011, PHARMAC applied generic reference pricing to olanzapine tablets. AIM: This study sought to evaluate change in outcome measures of patients switching from originator to generic olanzapine consequent to the introduction of the policy. METHODS: A retrospective study using national health data collections was conducted. Outcome measures included medicines indicators (change in dosage, concomitant therapy and treatment cessation), health care service indicators (use of emergency departments, hospitals and specialist services), surveillance reports of adverse events, and mortality. RESULTS: Subsequent to the removal of funding for originator brand olanzapine tablets, 99.7% of patients meeting the inclusion criteria switched to using generic olanzapine. Limited case reports of suspected therapeutic loss were received in the study time period. No increase in use of additional oral or injectable antipsychotic medication was observed after switching, nor any increase in other unique, non-antipsychotic prescription items. However, a high incidence of multiple switching between available brands was found. No net impact of switching brands on health service utilisation or mortality was found. DISCUSSION: The study shows that a switch can be made safely from originator olanzapine to a generic brand, and suggests that switching to generics should generally be viewed more positively. Generic reference pricing achieves considerable savings and, as a pricing policy, could be applied more widely.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".