Bibliographic record
Abstract
OBJECTIVES: To explore and make recommendations to implement direct billing and reimbursement models for nursing care in the United States. BACKGROUND: Nurses make up the largest group of healthcare professionals and within hospitals, nurses represent approximately a quarter of all resources and associated costs of patient care. This care is mostly hidden in daily room and board charges. METHODS: The authors surveyed the recent and historical literature related to costing and billing for nursing care. These results were synthesized and led to the recommendation of several new models to cost, bill, and pay for nursing care provided by nurses who are not currently billing for their services. RESULTS: Two basic billing models are proposed: the 1st is to remove nursing care out of the current daily room or facility-based charges and allocate nursing care time provided to each patient during each day of stay. The 2nd is to expand existing Current Procedural Terminology codes to bill for specific activities and interventions by nurses in all settings where nursing care is delivered. CONCLUSIONS: It is feasible to implement the proposed methods to identify patient-level nursing intensity, cost, services, and interventions provided by individual nurses in all healthcare settings.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".