Defining Standards for Hepatopancreatobiliary Cancer Surgery in Ontario, Canada: A Population-Based Cohort Study of Clinical Outcomes
Bibliographic record
Abstract
BACKGROUND: In 2006, Cancer Care Ontario created Surgical Oncology Standards for the delivery of hepatopancreatobiliary (HPB) surgery including hepatectomy and pancreaticoduodenectomy (PD). Our objective was to identify the impact of standardization on outcomes after HPB surgery in Ontario, Canada. STUDY DESIGN: This study was a population-level analysis of patients undergoing hepatectomy or PD (2003 to 2019). Logistic regression models were used to compare 30- and 90-day mortality and length of stay (LOS) before (2003 to 2006), during (2007 to 2011), and after (2012 to 2019) standardization. Interrupted time series models were used to co-analyze secular trends. RESULTS: A total of 7,904 hepatectomies and 5,238 PDs were performed. More than 80% of all cases were performed at a designated center (DC) before standardization. This increased to >98% in the poststandardization era. Median volumes at DCs increased from 55 to 67 hepatectomies/year and from 22 to 50 PDs/year over time. In addition, 30-day mortality after hepatectomy was 2.6% before standardization and 2.3% after standardization (p = 0.9); 30-day mortality after PD was 3.6% before standardization and 2.4% after standardization (p = 0.1). Multivariable analyses revealed a significant difference in 90-day mortality following PD poststandardization (4.3% vs 6.3%; adjusted odds ratio, 0.7; p = 0.03). Median LOS was shorter for hepatectomy (6 days vs 8 days) and PD (9 days vs 14 days; p < 0.0001) after standardization. Immediate and late effects on mortality and LOS were likely attributable to secular trends, which predated standardization. CONCLUSIONS: Standardization was associated with a higher volume of hepatectomy and PDs with further concentration of care at DCs. Pre-existing quality initiatives may have attenuated the effect of standardization on quality outcomes. Our data highlight the merits of a multifaceted provincial system for enabling consistent access to high quality HPB care throughout a region of 15 million people over a 16-year 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".