Pharmacists' Perspectives on Providing Chronic Disease Management Services in the Community — Part I: Current Practice Environment
Bibliographic record
Abstract
Background: Several practice models have been developed to support pharmacists in providing chronic disease management. However, most of these models have not been readily accepted by pharmacists, which has led to low uptake and short-term change. Methods: Pharmacists were recruited to participate in focus groups held in Alberta and British Columbia. Qualitative methodologies involving a phenomenological approach with content analysis were used to gather and analyze information. Results: In total, 36 pharmacists participated in 8 focus groups. Analysis of their discussions revealed 4 main themes: the current practice environment and the need for education about, remuneration for and a plan for the implementation of chronic disease management services. Participants cited several challenges to the provision of this type of care, as experienced in the current practice environment: time constraints; relationships with physicians, patients and employers; limited access to clinical information; and absence of a model for chronic disease management in pharmacy practice. However, these perceptions were not universal, and pharmacists with experience in this area described some of these commonly cited “challenges” (e.g., relationships with physicians) as enablers in their own practices. In addition, staff pharmacists, regional managers and owners often had differing opinions about the key challenges and the role of remuneration. Conclusion: Some of the perceived challenges to providing chronic disease management described by staff pharmacists were not consistently supported by employers or those with experience in this practice area. This observation suggests that the greatest challenge to developing a successful model of chronic disease management for pharmacists lies in pharmacists' own perceptions about their relationships with other health care providers and their own role as health care professionals. These issues must be addressed if the practice of pharmacy is to move forward.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".