Brand Loyalty, Generic Entry and Price Competition in Pharmaceuticals in the Quarter Century After the 1984 Waxman-Hatch Legislation
Bibliographic record
Abstract
The landmark Waxman-Hatch Act of 1984 represented a "grand compromise" legislation that sought to balance incentives for innovation by establishing finite periods of market exclusivity yet simultaneously providing access to lower cost generics expeditiously following patent expiration. Here we examine trends in the first quarter century since passage of the legislation, building on earlier work by Grabowski and Vernon [1992,1996] and Cook [1998]. The generic share of retail prescriptions in the U.S. has grown from 18.6% in 1984 to 74.5% in 2009, with a notable acceleration in recent years. This increase reflects increases in both the share of the total market potentially accessible by generics, and the generic efficiency rate -the latter frequently approaching 100%. Whereas in 1994, the generic price index fell from 100 to 80 in the 12 months following initial generic entry and by 24 months to 65, in 2009 the comparable generic price indexes are 68 and 27, respectively. Recent studies sponsored by the American Association of Retired Persons focus only on brand prices and ignore substitution to lower priced options following loss of patent protection. For the prescription drugs most commonly used by beneficiaries in Medicare Part D, the average price per prescription declined by 21.3% from 2006 to 2009, rather than increasing by 25-28% as reported by the AARP. Finally, we quantify changes over time in the average daily cost of pharmaceutical treatment in nine major therapy areas, encompassing the entire set of molecules within each therapy class, not simply the molecule whose patent has expired. Across all nine therapeutic areas, at 24 months post-generic entry, the weighted mean reduction in pharmaceutical treatment cost per patient is 35.1%.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".