A stakeholder co-design approach for developing a community pharmacy service to enhance screening and management of atrial fibrillation
Bibliographic record
Abstract
BACKGROUND: Community pharmacies provide a suitable setting to promote self-screening programs aimed at enhancing the early detection of atrial fibrillation (AF). Developing and implementing novel community pharmacy services (CPSs) is a complex and acknowledged challenge, which requires comprehensive planning and the participation of relevant stakeholders. Co-design processes are participatory research approaches that can enhance the development, evaluation and implementation of health services. The aim of this study was to co-design a pharmacist-led CPS aimed at enhancing self-monitoring/screening of AF. METHODS: A 3-step co-design process was conducted using qualitative methods: (1) interviews and focus group with potential service users (n = 8) to identify key needs and concerns; (2) focus group with a mixed group of stakeholders (n = 8) to generate a preliminary model of the service; and (3) focus group with community pharmacy owners and managers (n = 4) to explore the feasibility and appropriateness of the model. Data were analysed qualitatively to identify themes and intersections between themes. The JeMa2 model to conceptualize pharmacy-based health programs was used to build a theoretical model of the service. RESULTS: Stakeholders delineated: a clear target population (i.e., individuals ≥65 years old, with hypertension, with or without previous AF or stroke); the components of the service (i.e., patient education; self-monitoring at home; results evaluation, referral and follow-up); and a set of circumstances that may influence the implementation of the service (e.g., quality of the service, competency of the pharmacist, inter-professional relationships, etc.). A number of strategies were recommended to enable implementation (e.g.,. endorsement by leading cardiovascular organizations, appropriate communication methods and channels between the pharmacy and the general medical practice settings, etc.). CONCLUSION: A novel and preliminary model of a CPS aimed at enhancing the management of AF was generated from this participatory process. This model can be used to inform decision making processes aimed at adopting and piloting of the service. It is expected the co-designed service has been adapted to suit existing needs of patients and current care practices, which, in turn, may increase the feasibility and acceptance of the service when it is implemented into a real setting.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".