Understanding the relationship between the sustainability of the Professional Nurse Advocate Role, Organisational Culture and Quality Improvement Strategies in Healthcare: An Integrative Review
Bibliographic record
Abstract
Aim: To understand the relationship between organisational culture and quality improvement strategies (QI) in healthcare and how this applies to the sustainability of the Professional Nurse Advocate (PNA) role. Background: In response to nurse burn-out experienced throughout and following the coronavirus pandemic, NHS England launched the PNA role to support nurses through the Advocating and Educating for Quality ImProvement (A-EQUIP) model (NHS England, 2021). Uptake of the role has been disparate, and organisational culture may be one factor contributing to this. However, as the PNA role is relatively new, there is limited research in this field. Therefore, organisational culture was explored in relation to QI strategies more widely to understand if there are findings transferable to the PNA role and its sustainability. Method: Following ethical approval, The Toronto (2020) six-phase integrative review method was followed. CINAHL, Medline, Embase, Emcare, HMIC and grey literature databases were systematically searched. 799 articles were retrieved and screened, with 20 articles being included in the review, displayed via Preferred Reporting Items for Systematic reviews and Meta Analysis (PRISMA) and critically appraised. Qualitative literature was analysed using thematic analysis, whilst mixed method and quantitative literature were synthesised narratively. Findings: 6 key themes were identified relating to organisational culture and implementation of QI strategies: 3 facilitators (Leadership, collective action and shared ideology) and 3 barriers (Leadership, disconnection and external influences). An association between collective action and the uptake of QI was identified that could link to PNA implementation and sustainability. However, discussion of sustainability in relation to implementation was lacking and warrants further research. Implications for practice: There is a clear link between cultures that allow collective action and successful implementation efforts. However, this review highlights the need for further research on the relationship between collective action and sustainability of initiatives such as the PNA role.
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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 | 0.019 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".