A Systematic Review of the Cost-Effectiveness of Clinical Nurse Specialists and Nurse Practitioners in Inpatient Roles.
Bibliographic record
Abstract
The objective of this systematic review was to synthesize the evidence of the effectiveness and cost-effectiveness of clinical nurse specialists (CNSs) and nurse practitioners (NPs) working in alternative or complementary roles in inpatient settings. Those in alternative roles substitute for another provider and deliver similar services. Those in complementary roles deliver additional services to meet patient health needs. We searched 10 electronic databases, reference lists, pertinent journals and websites from 1980 to July 2012 with no language, publication or geographical restrictions. Study identification and assessment were completed independently by two-member teams. Internal validity was assessed using the Cochrane Risk of Bias tool. The quality of the economic analysis was evaluated using the Quality of Health Economic Studies (QHES) instrument. The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system was used to assess outcome-specific quality of evidence. Three dated trials evaluated CNS and NP inpatient roles; they were conducted in North America and included 488 adults and 821 neonates. In one study, CNSs in complementary provider roles, when compared with usual care, were equally effective with equal resource use (very low-quality evidence). In two studies, NPs in alternative roles, when compared with physicians, were equally effective with equal-to-more resource use and equal costs (low- to moderate-quality evidence). The quality of the economic analyses was poor. Only three dated studies were identified. More research is needed to determine cost-effectiveness and inform policies and decisions related to the implementation of CNSs and NPs working exclusively in inpatient roles.
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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 | 0.017 | 0.091 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.013 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".