The impact of graduate-prepared nurse practitioners and clinical nurse specialists on patient, provider and health system outcomes
Bibliographic record
Abstract
Background: Many studies have examined the effectiveness of nurse practitioners (NPs) and clinical nurse specialists (CNSs). The lack of clear role definitions and inconsistent educational preparation for these roles limit the generalizability of research findings across countries. Objective: The review is to evaluate and synthesize systematic reviews of the effectiveness of formally trained post-baccalaureate or graduate NPs and graduate-prepared CNSs internationally with respect to patient, provider and health system outcomes. Methods: An overview of systematic reviews to describe the effectiveness of formally trained post-baccalaureate or graduate NPs and graduate-prepared CNSs is underway. Eleven electronic databases and grey literature were searched. All relevant published and unpublished systematic reviews reported from 1990 to June 2013 with no restrictions on jurisdiction or language were included. Participants included patients of any age, groups or communities receiving all types of NP or CNS care. Two reviewers independently screened studies and extracted study data using a structured tool. The quality of each review will be assessed by two reviewers using AMSTAR. Results: We screened 415 titles and abstracts and retained seven systematic reviews. Data analysis is underway. Fifteen reviews were excluded late in the review process because the NP and CNS roles, and the educational preparation were not clearly articulated. A narrative synthesis of the findings will be compiled. Discussion: Clear role definitions for NPs and CNSs are particularly important in the context of comparing these roles internationally. Five of the seven studies in our review of systematic reviews that clearly identified formal NP training or graduate-level preparation were published after 2011 and appear to indicate a growing recognition of the importance of graduate preparation for NPs and CNSs. Conclusion: This appears to be the first review of systematic review to examine the effectiveness of formally trained post-baccalaureate or graduate-prepared NPs and graduate-prepared CNSs. The results of the review of systematic reviews will inform recommendations related to practice, policy, education, and research for NPs and CNSs internationally.
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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 | 0.041 | 0.223 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".