Effectiveness of registered nurses on patient outcomes in primary care: a systematic review
Bibliographic record
Abstract
BACKGROUND: Globally, registered nurses (RNs) are increasingly working in primary care interdisciplinary teams. Although existing literature provides some information about the contributions of RNs towards outcomes of care, further evidence on RN workforce contributions, specifically towards patient-level outcomes, is needed. This study synthesized evidence regarding the effectiveness of RNs on patient outcomes in primary care. METHODS: A systematic review was conducted in accordance with Joanna Briggs Institute methodology. A comprehensive search of databases (CINAHL, MEDLINE Complete, PsycINFO, Embase) was performed using applicable subject headings and keywords. Additional literature was identified through grey literature searches (ProQuest Dissertations and Theses, MedNar, Google Scholar, websites, reference lists of included articles). Quantitative studies measuring the effectiveness of a RN-led intervention (i.e., any care/activity performed by a primary care RN) that reported related outcomes were included. Articles were screened independently by two researchers and assessed for bias using the Integrated Quality Criteria for Review of Multiple Study Designs tool. A narrative synthesis was undertaken due to the heterogeneity in study designs, RN-led interventions, and outcome measures across included studies. RESULTS: Forty-six patient outcomes were identified across 23 studies. Outcomes were categorized in accordance with the PaRIS Conceptual Framework (patient-reported experience measures, patient-reported outcome measures, health behaviours) and an additional category added by the research team (biomarkers). Primary care RN-led interventions resulted in improvements within each outcome category, specifically with respect to weight loss, pelvic floor muscle strength and endurance, blood pressure and glycemic control, exercise self-efficacy, social activity, improved diet and physical activity levels, and reduced tobacco use. Patients reported high levels of satisfaction with RN-led care. CONCLUSIONS: This review provides evidence regarding the effectiveness of RNs on patient outcomes in primary care, specifically with respect to satisfaction, enablement, quality of life, self-efficacy, and improvements in health behaviours. Ongoing evaluation that accounts for primary care RNs' unique scope of practice and emphasizes the patient experience is necessary to optimize the delivery of patient-centered primary care. PROTOCOL REGISTRATION ID: PROSPERO: International Prospective Register of Systematic Reviews. 2018. ID=CRD42 018090767 .
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".