Costs and Consequences of Direct-to-Consumer Advertising for Clopidogrel in Medicaid
Bibliographic record
Abstract
BACKGROUND: Direct-to-consumer advertising (DTCA) is assumed to be a major driver of rising pharmaceutical costs. Yet, research on how it affects costs is limited. Therefore, we studied clopidogrel, a commonly used and heavily marketed antiplatelet agent, which was first sold in 1998 and first direct-to-consumer advertised in 2001. METHODS: We examined pharmacy data from 27 Medicaid programs from 1999 through 2005. We used interrupted time series analysis to analyze changes in the number of units dispensed, cost per unit dispensed, and total pharmacy expenditures after DTCA initiation. RESULTS: In 1999 and 2000, there was no DTCA for clopidogrel; from 2001 through 2005, DTCA spending exceeded $350 million. Direct-to-consumer advertising did not change the preexisting trend in the number of clopidogrel units dispensed per 1000 enrollees (P = .10). However, there was a sudden and sustained increase in cost per unit of $0.40 after DTCA initiation (95% confidence interval, $0.31-$0.49; P < .001), leading to an additional $40.58 of pharmacy costs per 1000 enrollees per quarter thereafter (95% confidence interval, $22.61-$58.56; P < .001). Overall, this change resulted in an additional $207 million in total pharmacy expenditures. CONCLUSIONS: Direct-to-consumer advertising was not associated with an increase in clopidogrel use over and above preexisting trends. However, Medicaid pharmacy expenditures increased substantially after the initiation of DTCA because of a concomitant increase in the cost per unit. If drug price increases after DTCA initiation are common, there are important implications for payers and for policy makers in the United States and elsewhere.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".