Advancing home health nursing competencies in Canada to reflect a dynamic care environment and complex population health needs: a modified eDelphi study
Bibliographic record
Abstract
BACKGROUND: Home health nursing competencies outline the knowledge, skills and attributes home health nurses need for safe and ethical practice. Since the Canadian Home Health Nursing Competencies were first developed in 2010, several important contextual changes have occurred. To ensure competencies reflect current practice contexts, this study aimed to update Canada's home health nursing competencies. METHODS: A four-phase modified eDelphi study was conducted using online surveys, consensus meetings and feedback forms. An environmental scan was conducted to identify home health competencies emerging since 2010, to create a comprehensive set of preexisting competencies to serve as the starting point for a 3-round modified eDelphi process. The eDelphi was conducted with a panel of home health nurses (n = 43) to identify core competencies relevant to current home health nursing practice environments. Broader consultations with home health nurses (n = 41) and interdisciplinary home care team members (n = 12) were held to validate eDelphi findings. An advisory working group (n = 24) of home health nursing leaders provided guidance on study decision-making and final recommendations. RESULTS: Three hundred fifty-nine preexisting competencies were consolidated into 96 unique home health nursing competencies. In Round 1 of the eDelphi, home health nurses reached consensus (agreement ≥ 75%) that 94 competencies were relevant to current practice environments and suggested five new competencies. Subsequent eDelphi rounds resulted in 93 competencies being brought forward as both relevant and essential for current home health nursing practice. Further consultations refined recommendations, resulting in a final set of 79 competencies. Qualitative feedback provided insights into the relevance and importance of competencies, opportunities for comprehension improvements, and implementation considerations. CONCLUSIONS: The home health nursing competency set generated through this study incorporates core concepts in home health nursing practice, such as evidence-informed practice and interdisciplinary collaboration, along with several new concepts, such as trauma-informed care, data-driven decision-making, and provision of culturally safe care. This updated competency set can be used to inform prelicensure education and professional development opportunities to enhance home health workforce capacity. Future work exploring strategies to support competency uptake in education and home and community care organizations is needed.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".