The Impact of a Skilled Nursing Facility on the Cost of Surgical Treatment of Major Head and Neck Tumors
Bibliographic record
Abstract
BACKGROUND: The finite resources available for health care and the proliferation of managed care in the United States have forced the head and neck surgeon to critically evaluate the cost of tumor treatment. OBJECTIVE: To determine whether the cost of treating patients with head and neck tumors would be reduced if the patients were to spend a portion of what would otherwise be acute care hospital days in a hospital-based skilled nursing facility (HB/SNF). DESIGN: Retrospective cost-benefit analysis. SETTING: Tertiary referral center. PATIENTS: Twenty-four consecutive hospital admissions for definitive surgical treatment of head and neck tumors were retrospectively reviewed. The postoperative day on which the patient theoretically could have been transferred to the HB/SNF was determined. The charges and cost of each patient's actual hospital stay were compared with the theoretical counterparts had the patient been transferred to the HB/SNF on the determined day. MAIN OUTCOME MEASURE: Cost savings. RESULTS: The total hospital stay for the 24 patients was 524 days. One hundred eighty-two of those days could have been spent in the HB/SNF. The total charge and cost savings with the use of an HB/SNF were $201,045 and $84,238, respectively (15% of the total charge and cost). This represents an average charge and cost savings of $8377 and $3510, respectively, per patient. The difference was statistically significant (P<.005). CONCLUSION: An HB/SNF could reduce the cost of head and neck tumor treatment without compromising patient care.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| 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".