Assessing the Economic Benefits of Enhanced Recovery After Surgery (ERAS) Protocols in Adult Cervical Deformity Patients
Bibliographic record
Abstract
OBJECTIVE: To assess the financial impact of Enhanced Recovery After Surgery (ERAS) protocols and cost-effectiveness in cervical deformity corrective surgery. STUDY DESIGN: Retrospective review of prospective CD database. BACKGROUND: Enhanced Recovery After Surgery (ERAS) can help accelerate patient recovery and assist hospitals in maximizing the incentives of bundled payment models while maintaining high-quality patient care. However, the economic benefit of ERAS protocols, nor the heterogeneous components that make up such protocols, has not been established. METHODS: Operative CD patients ≥18 y with complete pre-(BL) and up to 2-year(2Y) postop radiographic/HRQL data were stratified by enrollment in Standard-of-Care ERAS beginning in 2020. Differences in demographics, clinical outcomes, radiographic alignment targets, perioperative factors, and complication rates were assessed through means comparison analysis. Costs were calculated using PearlDiver database estimates from Medicare pay scales. QALY was calculated using NDI mapped to SF6D using validated methodology with a 3% discount rate to account for a residual decline in life expectancy. RESULTS: In all, 127 patients were included (59.07±11.16 y, 54% female, 29.08±6.43 kg/m 2 ) in the analysis. Of these patients, 54 (20.0%) received the ERAS protocol. Per cost analysis, ERAS+ patients reported a lower mean total 2Y cost of 35049 USD compared with ERAS- patients at 37553 ( P <0.001). Furthermore, ERAS+ patients demonstrated lower cost of reoperation by 2Y ( P <0.001). Controlling for age, surgical invasiveness, and deformity per BL TS-CL, ERAS+ patients below 70 years old were significantly more likely to achieve a cost-effective outcome by 2Y compared with their ERAS- counterparts (OR: 1.011 [1.001-1.999, P =0.048]. CONCLUSIONS: Patients undergoing ERAS protocols experience improved cost-effectiveness and reduced total cost by 2Y post-operatively. Due to the potential economic benefit of ERAS for patients incorporation of ERAS into practice for eligible patients should be considered.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".