A systematic review of research evidence on : (a) 24-hour registered nurse availability in long-term care, and (b) the relationship between nurse staffing and quality in long-term care
Bibliographic record
Abstract
BACKGROUND: Long term care (LTC) facilities offer care for people requiring the availability of 24-hour nursing. Staff in LTC facilities include licensed nursing staff: registered nurses (RNs) registered psychiatric nurses (RPNs), and licensed practical nurses (LPNs), as well as unregulated nurse/care aides. RN/RPNs and LPNs are trained to assess residents and provide nursing care to promote health and prevent illness. The work presented in this report includes: • a review of existing nurse staffing regulations relating to 24-hour nurse staffing in LTC facilities (Chapter 2), • literature review relating to the 24-hour RN cover question (Chapter 3), and • the review of broader nurse staffing literature (Chapter 4). NURSE STAFFING REGULATIONS: In Canada, six provinces require all LTC facilities, regardless of size, to have an RN on duty 24 hours a day; 7 days per week (24/7). Alberta requires an RN to be on-call, if not on duty, 24/7, and two provinces (New Brunswick, Nova Scotia) require an RN to be on duty 24/7 in larger facilities only (i.e. exceptions made for LTC facilities with less than 30 beds). British Columbia is the only province that does not have a regulatory requirement for an RN on duty 24/7. Policy alternatives to the 24/7 on-duty RN/RPN in LTC (taken from existing arrangements in place in Canada or the US) include: • General guidelines for ‗sufficient‘ staffing to meet resident needs, but no specific staffing levels or occupations; • A minimum of on-call RN/RPN staffing, if an RN/RPN is not on duty; • Licensed nurse staffing that varies depending upon the number of residents or beds in the LTC facility; • Nurse staffing that allows for exceptions or waivers to the requirement for RN/RPN staffing; and • 24 hours/7 days per week RN, RPN or LPN staffing (current US Federal Policy). REVIEW OF LITERATURE on 24/7 RN/RPN REQUIREMENT: The policy question addressed by the review was: ―What are the policy alternatives to 24-hour availability (on-call and/or on-site) of RNs/RPNs in special care homes, and what are the implications of each alternative in terms of care quality and resident outcomes?‖ An exhaustive search was undertaken (involving review of the titles/abstracts of 5,707 empirical research articles and 657 reviews) that revealed a distinct paucity of research on the 24-hr RN/RPN question. No directly relevant studies were found. BROADER NURSE STAFFING LITERATURE: The paucity of literature on the 24-hour RN question necessitated the expansion of the scope of the project to include broader literature on nurse staffing in LTC settings. The research evidence on the mix of RN staff to other nursing staff in LTC settings is itself ‘mixed‘. Some studies indicate that reducing the RN ratio (i.e. fewer RNs relative to other nursing staff) would have negative consequences on quality and outcomes. However, other studies do not find such associations, indicating no quality reductions through such changes in the make-up of the nursing staff complement. High quality studies that have explored the relationship between quality/outcomes and RN staffing levels predominantly indicate a positive relationship: higher levels of RN staffing are associated with better outcomes. The majority of the literature has explored the RN level question and fewer studies have looked at the LPN level and its link to quality and outcomes. The policy conclusions from the LPN literature suggest positive relationships (more LPNs associated with better outcomes) for some resident outcomes but negative relationships for other outcomes, even controlling for the number of RN staff. To be clear, a negative relationship indicates poorer outcomes associated with higher numbers of LPN staff. POLICY AND RESEARCH IMPLICATIONS: The policy challenge in the Saskatchewan context is whether to move away from the current 24-hour RN requirement. There is no empirical research work to inform a policy switch but it should also be emphasised that there is no empirical work that supports the current regulatory requirement. The only literature that discussed the question explicitly is expert panel reports in the US, all of which recommended 24-hour RN cover in nursing homes. None of the high quality research on nurse staffing mix and levels in LTC settings was undertaken in Canada; the vast majority of the research work cited in this report is from the US. Given the very different nurse training levels seen in Canada compared to the US, and the variability in resident populations in LTC settings between the two countries, the lack of Canadian research on this issue is surprising. Future Canadian research exploring the relationship between nurse staffing and outcomes in LTC settings is an urgent priority.
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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 | 0.030 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.007 |
| 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; both teacher heads agree on what is shown here.
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".