Nurses’ and Nursing Assistants’ Experiences With Teleconsultation in Small Rural Long-Term Care Facilities: Semistructured Interview Pilot Study
Bibliographic record
Abstract
BACKGROUND: In Quebec, the shortage of nurses during night shifts compromises the safety and quality of resident care, particularly in small residential and long-term care centers ("Centres d'hébergement et de soins de longue durée"; CHSLDs) located in rural areas. The need to ensure the continuous presence of nurses 24 hours a day in CHSLDs has become more pressing, forcing some facilities to implement exceptional measures such as on-call telephone services to ensure access to a nurse. In light of these challenging circumstances, the Direction nationale des soins et des services infirmiers of Quebec's Ministère de la Santé et des Services sociaux has rolled out a teleconsultation pilot project. OBJECTIVE: This study aims to explore nurses' and nursing assistants' experience of integrating teleconsultation during night shifts in rural CHSLDs with ≤50 residents. METHODS: The 6-month pilot project was rolled out sequentially in 3 rural CHSLDs located in 2 administrative regions of Quebec between July 2022 and March 2023. A total of 18 semistructured interviews were conducted with 9 nurses and nursing assistants between February and July 2023. RESULTS: Participants' experiences revealed that teleconsultation provided significant added value by improving clinical, administrative, and organizational practices. Some practices remained unchanged, indicating stable workflows. Workflow optimization through an expanded scope of practice ensured efficient and safe continuity of care. Enhanced collaboration between nurses and nursing assistants led to improved care coordination and communication. The leadership played a significant role in clarifying professionals' roles and in supporting effective adaptation to teleconsultation. CONCLUSIONS: This pilot project represents a significant step forward in improving care for CHSLD residents in Quebec. Teleconsultation not only makes it possible to overcome recruitment challenges and ensure the continuous presence of nurses during night shifts but also optimizes professional practices while ensuring the safety and quality of care provided to residents.
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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 | 0.000 | 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 | 0.000 |
| 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".