Determinants of venous thromboembolic event rates after hip arthroplasty -international comparison
Bibliographic record
Abstract
Background International comparisons of indicators of healthcare performance, quality and safety provide an important opportunity to explore reasons for their variations in order to find ways to improve both the indicators and the quality of care. We aimed to compare rates of hospital adverse events internationally and to investigate possible clinical and health system determinants of their variations. Methods We used hospital discharge diagnoses to measure rates of symptomatic venous thromboembolic events (VTE) in patients hospitalized for hip arthroplasty in Canada, France, New-Zealand, Switzerland and the USA. We used these coded diagnoses to measure VTE rates using an existing algorithm (AHRQ Patient Safety Indicator 12). We examined associations between VTE and gender, age, length of stay (LOS), number of discharge diagnoses recorded (Ndiag), and performance of ultrasonography before discharge (US). Results VTE rates were 0.84% in Canada, 1.41% in France, 0.84% in New-Zealand, 0.37% in Switzerland, 0.66% in the USA. Age, gender, LOS, Ndiag and US could have influenced VTE rates. For instance, France, where the highest VTE rate was observed, was also the only country with routine reported use of US before discharge (>17% vs <1% in other countries), which was even more frequent in private hospitals. The mean value of Ndiag was close to 7 in the USA, and varied between 2 and 3 in the other countries. Conclusions VTE rates varied across countries. These differences could be linked to differences in coding practices, as well as differences in clinical and health systems determinants (e.g., higher systematic US assessment in France and probable increased number of asymptomatic VTE coded). The interpretation of differences in international comparisons of healthcare associated VTE rates should be cautious; possible determinants of these differences should be considered. Key messages Understanding and reducing heterogeneity in international comparisons of adverse events of healthcare is crucial Caution is needed when interpreting international comparisons of adverse events of healthcare
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".