Pharmacist-led interventions during transitions of care of older adults admitted to short term geriatric units: Current practices and perceived barriers
Bibliographic record
Abstract
Background: During transitions of care, older adults are at risk of adverse drug events which could lead to avoidable hospital visits. Pharmacists are increasingly involved in care teams at various stages of the continuum of care. The types and frequency of clinical interventions performed by pharmacists in the geriatric practice setting remain poorly documented. Objectives: This study aimed to describe the current integration of pharmacist interventions during transitions of care of older adults admitted in short-term geriatric units (STGUs) and to explore barriers and facilitators to their implementation in clinical practice. The secondary objective was to explore associations between certain patient characteristics and pharmacist-led interventions during transitional care. Methods: A mixed methods study was conducted with pharmacists practicing in STGUs in the Montreal area, Canada. The application of 8 pharmaceutical interventions was assessed using a self-administered questionnaire, along with as a retrospective chart review. Four semi-structured group interviews were conducted in order to identify perceived barriers and facilitators. Results: Thirteen pharmacists participated in the study. In the questionnaire, medication reconciliation on admission and at discharge was reported as being performed at least half the time by 12 (92%) and 7 (54%) pharmacists, respectively. The retrospective chart review revealed that these interventions were documented in 95 (98%) and 25 (26%) files, respectively. While 35% of patients had a documented pharmaceutical care plan on admission, none was documented at discharge. Several barriers to implementing clinical interventions were identified such as lack of time, technical support, communication and standardization. Conclusions: Pharmacists are involved at different periods of transitional care; however, certain barriers should be addressed in order to expand their role in discharge planning. Providing guidelines on what is expected at discharge and post-discharge, and having a practice focused on delegation and collaboration would help pharmacists increase their role throughout the transition of care of older adults.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".