Barriers to a full scope of pharmacy practice in primary care: A systematic review of pharmacists’ access to laboratory testing
Bibliographic record
Abstract
Objectives: To describe primary care pharmacists’ current scope of practice in relation to laboratory testing. Method: A 2-tiered search of key databases (PubMed, EMBASE, MEDLINE) and grey literature with the following MeSH headings: prescribing, pharmacist/pharmacy, laboratory test, collaborative practice, protocols/guidelines. We focused on Canada, the United States, the United Kingdom, New Zealand and Australia for this review. Results: There is limited literature exploring primary care pharmacists’ scope of practice in relation to laboratory testing. The majority of literature is from the United States and Canada, with some from the United Kingdom and New Zealand and none from Australia. Overall, there is a difference in regulations between and within these countries, with the key difference being whether pharmacists access and/or order laboratory testing dependently or independently. Canadian pharmacists can access and/or order laboratory tests independently or dependently, depending on the province they practise in. US pharmacists can access and/or order laboratory tests dependently within collaborative practice agreements. In the United Kingdom, laboratory testing can be performed by independent prescribing pharmacists or dependently by supplementary prescribing pharmacists. New Zealand prescribing pharmacists can order laboratory testing independently. Most publications do not report on the types of laboratory tests used by pharmacists, but those that do predominantly resulted in positive patient outcomes. Discussion/Conclusion: Primary care pharmacists’ scope of practice in laboratory testing is presently limited to certain jurisdictions and is often performed in a dependent fashion. As such, a full scope of pharmacy services is almost entirely unavailable to patients in the United States, the United Kingdom, New Zealand and Australia. Just as in the case for pharmacists prescribing, evidence indicates better patient outcomes when pharmacists can access/order laboratory tests, but more research needs to be done alongside the implementation of local guidelines and practice standards for pharmacists who practise in that realm. Patients around the world deserve to receive a full scope of pharmacists’ practice, and lack of access to laboratory testing is one of the major obstacles to this. Can Pharm J (Ott) 2019;152:xx-xx.
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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 | 0.021 | 0.110 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.009 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".