Specialized nursing practice for chronic disease management in the primary care setting: an evidence-based analysis.
Bibliographic record
Abstract
BACKGROUND: In response to the increasing demand for better chronic disease management and improved health care efficiency in Ontario, nursing roles have expanded in the primary health care setting. OBJECTIVES: To determine the effectiveness of specialized nurses who have a clinical role in patient care in optimizing chronic disease management among adults in the primary health care setting. DATA SOURCES AND REVIEW METHODS: A literature search was performed using OVID MEDLINE, OVID MEDLINE In-Process and Other Non-Indexed Citations, OVID EMBASE, EBSCO Cumulative Index to Nursing & Allied Health Literature (CINAHL), the Wiley Cochrane Library, and the Centre for Reviews and Dissemination database. Results were limited to randomized controlled trials and systematic reviews and were divided into 2 models: Model 1 (nurse alone versus physician alone) and Model 2 (nurse and physician versus physician alone). Effectiveness was determined by comparable outcomes between groups in Model 1, or improved outcomes or efficiency in Model 2. RESULTS: Six studies were included. In Model 1, there were no significant differences in health resource use, disease-specific measures, quality of life, or patient satisfaction. In Model 2, there was a reduction in hospitalizations and improved management of blood pressure and lipids among patients with coronary artery disease. Among patients with diabetes, there was a reduction in hemoglobin A1c but no difference in other disease-specific measures. There was a trend toward improved process measures, including medication prescribing and clinical assessments. Results related to quality of life were inconsistent, but patient satisfaction with the nurse-physician team was improved. Overall, there were more and longer visits to the nurse, and physician workload did not change. LIMITATIONS: There was heterogeneity across patient populations, and in the titles, roles, and scope of practice of the specialized nurses. CONCLUSIONS: Specialized nurses with an autonomous role in patient care had comparable outcomes to physicians alone (Model 1) based on moderate quality evidence, with consistent results among a subgroup analysis of patients with diabetes based on low quality evidence. Model 2 showed an overall improvement in appropriate process measures, disease-specific measures, and patient satisfaction based on low to moderate quality evidence. There was low quality evidence that nurses working under Model 2 may reduce hospitalizations for patients with coronary artery disease. The specific role of the nurse in supplementing or substituting physician care was unclear, making it difficult to determine the impact on efficiency. PLAIN LANGUAGE SUMMARY: Nurses with additional skills, training, or scope of practice may help improve the primary care of patients with chronic diseases. This review found that specialized nurses working on their own could achieve health outcomes that were similar to those of doctors. It also found that specialized nurses who worked with doctors could reduce hospital visits and improve certain patient outcomes related to diabetes, coronary artery disease, or heart failure. Patients who had nurse-led care were more satisfied and tended to receive more tests and medications. It is unclear whether specialized nurses improve quality of life or doctor workload.
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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 | 0.018 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.012 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".