The advanced practice nurse–nephrologist care model: Effect on patient outcomes and hemodialysis unit team satisfaction
Bibliographic record
Abstract
The tertiary care nurse practitioner/clinical nurse specialist (NP/CNS) is an advanced practice nurse with a relatively new role within the health-care system. It is stated that care provided by the NP/CNS is cost-effective and of high quality but little research exists to document these outcomes in an acute-care setting. The clinical coverage pattern by nephrologists and NP/CNS of a hemodialysis unit in a large academic center allowed such a study. Two NP/CNS plus a nephrologist followed two of three hemodialysis treatment shifts per day; only a nephrologist followed the third shift. The influence of this care pattern of patients was examined using a cross-sectional review of outcomes such as adequacy of delivered dialysis, anemia management, phosphate control, hospitalizations, etc. In addition, the level of satisfaction of the dialysis team and perceptions of care delivered with the care models was assessed. The care model staff-to-patient-number ratio was similar in both groups (1:27 for NP/CNS plus nephrologist; 1:29 for nephrologist alone). Patient demographics were similar in both groups but the NP/CNS-nephrologist group had patients with more comorbidities. No statistically significant (p < 0.05) differences existed between the groups in patient laboratory data, adherence to standards, medications, inter- and intradialytic blood pressure, achievement of target postdialysis weights, and hospitalizations or emergency room visits. Significantly more adjustments were made to target weights and medications and more investigations were ordered by the NP/CNS-nephrologist team. Team satisfaction and perceptions of care delivery were higher with the NP/CNS-nephrologist model. It is concluded that the NP/CNS-nephrologist care model may increase the efficiency of the care provided by nephrologists to chronic hemodialysis patients. The model may also be a solution to the problem of providing nephrologic care to an ever-growing hemodialysis population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".