A Primary Care Nursing Perspective on Chronic Disease Prevention and Management
Bibliographic record
Abstract
According to the American Academy of Ambulatory Care Nursing (AAACN), Ambulatory care nursing is a unique realm of specialized nursing practice. RNs in the ambulatory setting are leaders in their practice settings and are uniquely qualified to influence organizational standards related to patient safety and care delivery in the outpatient setting.5 RNs in the inpatient setting are highly regarded as critical thinkers often implementing and providing care utilizing the steps of the nursing process which promote excellent quality care. As more and more patients transition from inpatient to outpatient settings, there is a greater demand for professional nursing services in the outpatient settings. RNs can utilize the same steps of the nursing process, which include assessment, nursing diagnosis, planning, implementing, and evaluation in caring for individuals in the outpatient setting. Tools used to provide care are order sets, protocols, and care plans. Primary Care offices can utilize registered nurses in day to day patient care delivery, education, self-management support, chronic disease care management and care coordination of services, and oversight and collaboration of panels of individuals. Providing these services will make a positive impact on patient outcomes and will prevent chronic diseases. In Canada, payment models have recently been implemented in primary care to address the increasing burden that patients with chronic diseases place on the Canadian healthcare system.4
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".