Cost savings of outpatient versus standard inpatient total knee arthroplasty
Bibliographic record
Abstract
BACKGROUND: With diminishing reimbursement rates and strained public payer budgets, a high-volume inpatient procedure, such as total knee arthroplasty (TKA), is a common target for improving cost efficiencies. METHODS: This prospective case-control study compared the cost-minimization of same day discharge (SDD) versus inpatient TKA. We examined if and where cost savings can be realized and the magnitude of savings that can be achieved without compromising quality of care. Outcome variables, including detailed case costs, return to hospital rates and complications, were documented and compared between the first 20 SDD cases and 20 matched inpatient controls. RESULTS: In every case-control match, the SDD TKA was less costly than the inpatient procedure and yielded a median cost savings of approximately 30%. The savings came primarily from costs associated with the inpatient encounter, such as surgical ward, pharmacy and patient meal costs. At 1 year, there were no major complications and no return to hospital or readmission encounters for either group. CONCLUSION: Our results are consistent with previously published data on the cost savings associated with short stay or outpatient TKA. We have gone further by documenting where those savings were in a matched cohort design. Furthermore, we determined where cost savings could be realized during the patient encounter and to what degree. In carefully selected patients, outpatient TKA is a feasible alternative to traditional inpatient TKA and is significantly less costly. Furthermore, it was deemed to be safe in the perioperative period.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".