Evaluating healthcare resource utilization and outcomes for surgical hip dislocation and hip arthroscopy for femoroacetabular impingement
Bibliographic record
Abstract
PURPOSE: Surgical hip dislocation (SHD) and hip arthroscopy are surgical methods used to correct deformity associated with femoroacetabular impingement (FAI). Though both of these approaches appear to benefit patients, no studies exist comparing healthcare resource utilization of the two surgical approaches. This systematic review examines the literature and the records of two surgeons to evaluate the resource utilization associated with treating symptomatic FAI via these two methods. METHODS: EMBASE, MEDLINE and PubMed were searched for relevant articles. The articles were systematically screened, and data was abstracted in duplicate. To further supplement resource utilization data, a retrospective chart review of two surgeon's patient data (one using SHD and another using an arthroscopic approach) was completed. Experts in pharmacy, physiotherapy, radiology, anaesthesia, physiatry and the local hospital finance department were also consulted. RESULTS: There were 52 studies included with a total of 460 patients (535 hips) and 3886 patients (4147 hips) who underwent SHD and arthroscopic surgery for FAI, respectively. Regardless of approach, most patients treated for symptomatic FAI improved across various outcomes measures with low complication rates. Surgical time across all approaches was similar, averaging 118 ± 2 min. On a per patient basis, hip arthroscopy ($10,976) uses approximately 41 % of the resources of SHD ($24,379). CONCLUSION: There were no significant differences in outcomes for FAI treated with SHD or arthroscopy. However, with regard to healthcare resource utilization based on the OHIP healthcare system, hip arthroscopy uses substantially less resources than SHD within the first post-operative year. LEVEL OF EVIDENCE: Systematic Review of Level IV Studies, Level IV.
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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 | 0.007 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.011 | 0.015 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 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".