Organizational facilitators and barriers to optimal APRN practice: An integrative review
Bibliographic record
Abstract
BACKGROUND: The organizational environment can foster or impede full deployment of advance practice registered nurses (APRNs), affecting the quality of care and patient outcomes. Given the critical role APRNs play in health care, it is important to understand organizational factors that promote or hinder APRN practice to maximize the potential of this workforce in health care systems. PURPOSE: The aim of this study was to synthesize evidence about APRN practice environments, identify organizational facilitators and barriers, and make recommendations for better APRN utilization. METHODS: A literature search was conducted in CINAHL, PubMed, and PsychInfo, yielding 366 studies. No time or geographic limitations were applied. Study quality was appraised using the National Institutes of Health National Heart, Lung, and Blood Institute Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies and The Joanna Briggs Institute Critical Appraisal Checklist for Qualitative Studies. RESULTS: Thirty studies conducted in the United States, Canada, and the Netherlands met inclusion criteria. The majority of the studies involved nurse practitioners. Facilitators to optimal practice environment were autonomy/independent practice and positive physician/APRN relations. Barriers included policy restrictions on practice, poor physician relations, poor administrator relations, and others' lack of understanding of the APRN role. Barriers correlate with job dissatisfaction and increased intent to leave job. PRACTICE IMPLICATIONS: The review highlights the importance of physician and administration relations, organizational-level policies, and colleagues' understanding of the APRN role in promoting effective practice environments. Organizations should align policy reform efforts with factors that foster positive APRN practice environments to efficiently and effectively utilize this increasingly vital workforce. Future research is warranted.
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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 | 0.011 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".