Association between registered nurse staffing and management outcomes of patients with type 2 diabetes within primary care: a cross-sectional linkage study
Bibliographic record
Abstract
BACKGROUND: As the organization of primary care continues to evolve toward more interdisciplinary team structures, demonstrating effectiveness of care delivery is becoming important, particularly for nonphysician providers. Nurses are the most common nonphysician provider within primary care. The purpose of this study was to examine the relation between primary care delivery models that incorporate registered nurses and clinical outcomes of patients with type 2 diabetes. METHODS: Patient data from the Canadian Primary Care Sentinel Surveillance Network were matched with survey data from 15 Family Health Team practices in southeastern Ontario. Included patients were adults with type 2 diabetes mellitus who had at least 1 primary care encounter at a Family Health Team practice that completed the organizational survey between Apr. 1, 2013, and Mar. 31, 2014. The clinical outcomes explored included hemoglobin A1c, fasting plasma glucose, blood pressure, low-density lipoprotein cholesterol and urine albumin:creatinine ratio. RESULTS: Of the 15 practices, 13 (86.7%) had at least 1 registered nurse. The presence of 1 or more registered nurses in the practice was associated with increased odds of patients' having their hemoglobin A1c, fasting plasma glucose, blood pressure and low-density lipoprotein cholesterol values meet recommended targets. Practices with the lowest ratios of patients with diabetes to registered nurse had a significantly greater proportion of patients with hemoglobin A1c and fasting plasma glucose values on target than did practices with the highest ratios of patients to registered nurse (p < 0.01 and p = 0.03, respectively). INTERPRETATION: The findings suggest that registered nurse staffing within primary care practice teams contributes to better diabetic care, as measured by diabetes management indicators. This study sets the groundwork for further exploration of nursing and organizational contributions to patient care in the primary care setting.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".