Systematic review of expanded practice in rural community pharmacy
Bibliographic record
Abstract
Abstract Aim The aim of this study was to identify published evidence to inform the development of expanded practice services in rural community pharmacies. Data sources The search strategy was applied to the following electronic databases: MEDLINE, CINAHL, Emcare, Cochrane and Google Scholar. Study selection In all, 508 studies were evaluated against inclusion and exclusion criteria, with 29 eligible studies finally included in the review. Services provided needed to meet the described definition of ‘expanded practice’ and be applied in a rural community pharmacy setting. Expanded services were evaluated against at least one of the following: effectiveness, enablers, barriers and feasibility. Results The studies included in this review were conducted in the US (n = 15), Australia (n = 8), Canada (n = 2), New Zealand (n = 1), England (n = 1), Croatia (n = 1) and Ghana (n = 1). All studies were conducted within the past 22 years, with 11 published since 2015. Cardiovascular disease (n = 7), diabetes/metabolic syndrome (n = 4), respiratory disease (n = 6) and vaccinations (n = 5) were the most common diseases or health service targeted in the interventions. Study design varied, reflected in the methodological quality, which included experimental studies (n = 27) and retrospective observational cohort studies (n = 2). Expanded pharmacy services identified included delivery of immunisations and the screening and management of chronic and infectious diseases, such as osteoporosis, asthma, chronic obstructive pulmonary disease, malaria, diabetes and cardiovascular and kidney disease. Conclusions Pharmacists providing these services have an opportunity to improve health outcomes for rural populations.
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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 | 0.020 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".