Physical assessment in pharmacy practice: Perspectives from pharmacists, nonpharmacist health care providers and the public
Bibliographic record
Abstract
BACKGROUND: Physical assessment in pharmacy practice is not a new concept, yet the idea is still unfamiliar to many people. Canadian pharmacy graduates are expected to be trained in physical examination as it relates to drug therapy. However, standard delivery of course content in this area has not been clearly established, and previous publications have reported low uptake of this practice despite formal training. To aid the future development of a physical assessment course for pharmacists that is relevant to practice and will contribute to patient care, it is important to gather insight from practising pharmacists, health care providers and the public. OBJECTIVE: To determine the type of physical assessment skills that would be of value to pharmacy practice and the benefits and barriers of these skills in practice from the perspectives of pharmacists, health care providers and the public. METHODS: This was a cross-sectional online survey of pharmacists, nonpharmacist health care providers and the public. Descriptive statistics and thematic analysis were used to describe data. RESULTS: A total of 348 respondents (98 pharmacists, 154 nonpharmacist health care providers, 96 public) completed the survey. Most (64%) nonpharmacist providers were physiotherapists or occupational therapists (only 6.5% physicians). Most respondents felt that performing basic vital signs was relevant to pharmacy practice (79% pharmacists, 69% other providers, 79% public) and felt confident and comfortable about pharmacists using these skills. Palpation, percussion and auscultation were rated less favourably (<50% for most respondents). Nonpharmacist providers tended to be less favourable than pharmacist and public respondents. Seven themes related to benefits and 13 themes related to disadvantages of pharmacists performing physical assessment were identified. CONCLUSION: 2021;154: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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| 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".