A developmental evaluation of an intraprofessional Pharmacy Communication Partnership (PROMPT) to improve transitions in care from hospital to community: A mixed-methods study
Bibliographic record
Abstract
BACKGROUND: People transitioning from hospital- to community-based care are at increased risk of experiencing medication problems that can lead to adverse drug events and poor health outcomes. Community pharmacists provide medication expertise and support during care transitions yet are not routinely included in communications between hospitals and other primary health care providers. The PhaRmacy COMmunication ParTnership (PROMPT) intervention facilitates medication management by optimizing information sharing between pharmacists across care settings. This developmental evaluation sought to assess the feasibility and acceptability of implementing the PROMPT intervention, and to explore how contextual factors influenced its implementation. METHODS: PROMPT was implemented for 14 weeks (January-April, 2018) in the general internal medicine units at two teaching hospitals in Toronto, Canada. PROMPT featured two contact points between hospital and community pharmacists around patient discharge: (1) faxing an enhanced discharge prescription and discharge summary to a patient's community pharmacy and (2) a follow-up phone call from the hospital pharmacist to the community pharmacist. Our mixed-method evaluation involved electronic patient records, process measures using tracking forms, telephone surveys and semi-structured interviews with participating community and hospital pharmacists. RESULTS: The intervention involved 45 patients with communication between 12 hospital and 45 community pharmacists. Overall, the intervention had challenges with feasibility. Issues with fidelity included challenges with the medical discharge summary being available at the time of faxing and hospital pharmacists' difficulties with incorporating novel elements of the program into their existing practices. However, both community and hospital pharmacists recognized the potential benefits to patient care that PROMPT offered, and both groups proposed recommendations for further improvements. Suggestions included enhancing hospital staffing and resources. CONCLUSION: Improving intraprofessional collaboration, through interventions such as PROMPT, positions pharmacists as leaders of medication management services across care settings and has the potential to improve patient care; however, more co-design work is needed to enhance the intervention and its fidelity.
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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 | 0.033 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".