Seeking Value in Pharmaceutical Care: Balancing Quality, Access and Efficiency
Bibliographic record
Abstract
Healthcare remains a dominant issue for Canadians. Central to the debate is the dynamic tension among the value, accessibility and affordability of drugs. Simply put, innovative drugs improve health and economic outcomes for individuals and populations. As a result, providers and patients increasingly demand, and expect, these benefits; utilization and expenditures increase. The management challenge is finding the best balance of quality, access and costs. Supply-side strategies, such as restricting access with the intention of controlling isolated costs of drug budgets, are not optimal from a population health view because they have the adverse impact of limiting the system benefits of innovative drugs. Management strategies emphasizing the demand side of the market are more empowering to providers and patients and, given the increasing knowledge and accountability of these stakeholders, are increasingly feasible. Population health outcomes and efficient resource use may be better served by a combination of strategies. The partnership-measurement model of disease management is a practical example of this approach at the community level; timely and repeated feedback of real-world practices, as well as provider and patient education, drive accountable, cost-efficient and continuously improved outcomes. As we seek the optimal societal strategy for innovative drug therapy, resource allocation decisions have to be made. Widening the debate and informing the debaters will enhance the chances of making choices that achieve the best health for the most people at the best cost.
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 | 0.022 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.009 | 0.028 |
| Scholarly communication | 0.022 | 0.010 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".