Attaining pharmacist recognition in the United States
Bibliographic record
Abstract
In this issue of AJHP, Yuksel et al.1 describe pharmacist prescribing in Alberta. In the United States, the journey toward recognition of pharmacists by public and private payers started with the modernization of state practice acts that allowed collaborative See also page 2126. drug therapy management (CDTM) agreements between pharmacists and prescribers. CDTM is a team approach to health care delivery, and it establishes written guidelines and protocols that authorize the pharmacist to initiate, modify, or continue drug therapy for a specific patient. Forty-five states allow pharmacists to manage a patient’s medication therapy.2 This includes adjusting, discontinuing, and, in some cases, initiating therapy. After states updated their individual practice acts, the journey for pharmacist recognition began on the national level. Through the 2004 Medicare Modernization Act, coverage of prescription drugs was enacted under Medicare Part D. Medicare Part D has been a positive step toward recognizing pharmacists as providers because an element of Part D coverage includes medication therapy management (MTM) services.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.038 | 0.021 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".