Pharmacist‐led transitions of care between hospitals, primary care clinics, and community pharmacies
Bibliographic record
Abstract
BACKGROUND: Pharmacist-led transitions of care (TOC) interventions have been described as some of the most promising interventions to reduce medication-related harm (MRH) in older adults. This study analyzed the feasibility of pharmacist-led TOC interventions between hospitals, multidisciplinary primary care clinics (PCC), and community pharmacies. METHODS: Adults aged 65 years and older at risk of MRH in three regions of Quebec, Canada, with contrasting contexts of care based on university affiliation were recruited in this multicenter, single arm, and prospective intervention cohort. The hospital pharmacist developed the pharmaceutical care plan in collaboration with the hospital physician and transferred this plan with the hospitalization summary, at hospital discharge, to the PCC family physician and to the community and PCC pharmacists. A consultation with the community pharmacist was scheduled within seven days of hospital discharge and with the PCC pharmacist when appropriate. Feasibility outcomes included the time to complete the interventions and their location. RESULTS: The 123 eligible patients had a mean age of 78.5 years, and 63.4% were females. The most frequent inclusion criterion was 10 medications or more, including one high-risk medication for 90 patients (73%). Recruitment in one region was stopped after three months due to unsuccessful recruitment of key PCC. The hospital pharmacist interventions took a median of 165 min. The first consultations of the PCC and community pharmacists took a median of 15 and 50 min. Among the 96 patients with a post-discharge pharmacist follow-up, 23 (24.0%) had a consultation with a PCC pharmacist, with 65.2% of the consultations conducted at the PCC. The community pharmacists conducted a consultation with 88 patients (93%), with more than 70% of consultations conducted by phone. CONCLUSION: Our study showed the feasibility of pharmacist-led TOC interventions between hospitals, PCC, and community pharmacies and detailed the novel role that PCC pharmacists played in optimizing TOC interventions.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".