The Economic Consequences of Generic Substitution for Antiepileptic Drugs in a Public Payer Setting: The Case of Lamotrigine
Bibliographic record
Abstract
Generic substitution of antiepileptic drugs (AEDs) may increase pharmacy utilization, thus counterbalancing per-pill savings. The purpose of our study was to analyze the economic impact of government-mandated switching from branded to generic lamotrigine. Patients in a Canadian public pharmacy claims database using branded lamotrigine (Lamictal GlaxoSmithKline, UK) in 2002 converted to generic lamotrigine in 2003 and were observed from July 2002 to March 2006. Patients used branded lamotrigine for >or=90 days pre-generic entry and had >or=1 claim for generic lamotrigine post-generic entry. For the generic period, observed per-patient monthly drug costs were calculated as the sum of costs for lamotrigine, other AEDs, and non-AEDs. Expected per-patient drug costs were estimated assuming lamotrigine dose and other prescription drug utilization in the generic period were identical to those observed during the brand period. Differences between observed and expected costs were compared. Among 1,142 branded lamotrigine users, overall average monthly drug costs per person were expected to decrease by $30.55 due to lower pill costs. Instead, they fell by $11.98 from the brand to the generic periods (p < 0.001). Because of dosage changes, lamotrigine costs decreased by $29.92 instead of the anticipated $33.87 (p < 0.001). Increased pharmacy utilization caused other AED costs to rise by $6.29 versus the expected $0.36 (p < 0.001), while non-AED drug cost increased by $11.64 rather than by $2.95 (p < 0.001). We concluded that conversion to generic lamotrigine resulted in lower than expected cost savings. Further research is necessary to determine whether this is due to reduced effectiveness and/or tolerability. Payers may weigh smaller-than-expected cost reductions against a possible decrease in effectiveness to assess the relevance of mandatory generic switching of lamotrigine.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".