The Impact of Electronic Prescribing on the Professionalization of Community Pharmacists: A Qualitative Study of Pharmacists’ Perception
Bibliographic record
Abstract
PURPOSE: To understand how the technology of electronic prescription (e Rx) can transform the community pharmacist's role through its effects on professionalization. We define professionalization as a pharmaceutical practice centred on clinical activities and made possible by the establishment of professional pharmaceutical services. METHODS: We asked 12 community pharmacists who had participated in an e Rx pilot project in the Canadian province of Quebec to fill out a qualitative survey on their experience. We then analyzed the pharmacists' perceptions of this new technology using a conceptual framework based on the Davenport typology that presents an exhaustive list of mechanisms, specific to Information Technologies, and thus e-Rx, that can potentially modify information management process and then the role of pharmacists. RESULTS: The pharmacists identified five main mechanisms by which e Rx could affect the professionalization of community pharmacists: analytical capabilities of the pharmacist and physician, dissemination of knowledge, integration of process tasks, process automation and elimination of intermediaries. These mechanisms can assist pharmacists in exercising their professional judgement by improving the quality of available information and facilitate the execution of prescriptions by improving the quality of orders. E Rx technology can also strengthen pharmacists' credibility as medication specialists in the eyes of both patients and physicians. Thus, e Rx can become a collaborative technology to the extent that it improves collaboration between community pharmacists and prescribing physicians. However, the potential benefits of this technology would appear to depend on its characteristics and how prescribing physicians use it. CONCLUSIONS: E-Rx proposes ways of working and communicating that were previously unimaginable. These new possibilities pave the way for transformations that can significantly increase the professionalization of community pharmacists. The results of this study indicate that community pharmacists have a favourable opinion of e Rx, believing it can be an ally in their professionalization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".