Exploration of home care nurse’s experiences in deprescribing of medications: a qualitative descriptive study
Bibliographic record
Abstract
OBJECTIVES: The aim of this study is to explore the barriers and enablers of deprescribing from the perspectives of home care nurses, as well as to conduct a scalability assessment of an educational plan to address the learning needs of home care nurses about deprescribing. METHODS: This study employed an exploratory qualitative descriptive research design, using scalability assessment from two focus groups with a total of 11 home care nurses in Ontario, Canada. Thematic analysis was used to derive themes about home care nurse's perspectives about barriers and enablers of deprescribing, as well as learning needs in relation to deprescribing approaches. RESULTS: Home care nurse's identified challenges for managing polypharmacy in older adults in home care settings, including a lack of open communication and inconsistent medication reconciliation practices. Additionally, inadequate partnership and ineffective collaboration between interprofessional healthcare providers were identified as major barriers to safe deprescribing. Furthermore, home care nurses highlighted the importance of raising awareness about deprescribing in the community, and they emphasised the need for a consistent and standardised approach in educating healthcare providers, informal caregivers and older adults about the best practices of safe deprescribing. CONCLUSION: Targeted deprescribing approaches are important in home care for optimising medication management and reducing polypharmacy in older adults. Nurses in home care play a vital role in medication management and, therefore, educational programmes must be developed to support their awareness and understanding of deprescribing. Study findings highlighted the need for the future improvement of existing programmes about safer medication management through the development of a supportive and collaborative relationship among the home care team, frail older adults and their informal caregivers.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".