Ambulatory Surgical Centers: Improving Quality of Operative Spine Care?
Bibliographic record
Abstract
STUDY DESIGN: Narrative review with commentary. OBJECTIVE: Present healthcare reform focuses on cost-optimization and quality improvement. Spine surgery has garnered particular attention; owing to its costly nature. Ambulatory Surgical Centers (ASC) present a potential avenue for expenditure reduction. While the economic advantage of ASCs is being defined, cost saving should not come at the expense of quality or safety. METHODS: This narrative review focuses on current definitions, regulations, and recent medical literature pertinent to spinal surgery in the ASC setting. RESULTS: The past decade witnessed a substantial rise in the proportion of certain spinal surgeries performed at ASCs. This setting is attractive from the payer perspective as remuneration rates are generally less than for equivalent hospital-based procedures. Opportunity for physician ownership and increased surgeon productivity afforded by more specialized centers make ASCs attractive from the provider perspective as well. These factors serve as extrinsic motivators which may optimize and improve quality of surgical care. Much data supports the safety of spine surgery in the ASC setting. However, health care providers and policy makers must recognize that current regulations regarding safety and quality are less than comprehensive and the data is predominately from selected case-series or comparative cohorts with inherent biases, along with ambiguities in the definition of "outpatient." CONCLUSIONS: ASCs hold promise for providing safe and efficient surgical management of spinal conditions; however, as more procedures shift from the hospital to the ASC rigorous quality and safety data collection is needed to define patient appropriateness and track variability in quality-related outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.105 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".