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From data to quality: the story of A-QUA, Switzerland's Anaesthesia QUAlity initiative and database.

European journal of anaesthesiology and intensive care2026-09-13PubMed 42730411
Design
Design 8 of 10
Novelty
Novelty 9 of 10
Journal
Journal 8 of 10
Clinical
Clinical 9 of 10

Summary

This retrospective analysis describes A-QUA, a nationwide Swiss anesthesia quality program. By the end of 2024, its case-based registry contained 2,045,026 cases from 54 centers, enabling standardized benchmarking, detection of recurrent data-quality problems, and analysis of regional and hospital variation in anesthesia practice and postoperative disposition.

Key Findings

  • The registry contained 2,045,026 anesthesia cases from 54 Swiss centers by the end of 2024.
  • General anesthesia accounted for 74% of cases, regional anesthesia alone for 18%, and monitored anesthesia care for 8.5%.
  • Plausibility checks identified recurrent preventable errors, while case studies demonstrated variation in anesthesia choice, timing, and postoperative destination across hospitals and regions.

Clinical Implications

Anesthesia departments and health systems can use comparable routine data to identify preventable documentation or process errors, benchmark practice patterns, target quality-improvement interventions, and generate hypotheses for future prospective studies.

Why It Matters

The registry demonstrates how standardized, nationwide anesthesia data can support continuous quality improvement and perioperative research at a scale rarely available in anesthesiology. Its value lies in infrastructure and reproducibility rather than a single clinical association.

Limitations

  • The retrospective registry design cannot establish causality for observed practice variation or outcomes.
  • Participation was weighted toward large teaching hospitals, limiting representativeness of smaller nonteaching institutions.

Future Directions

Future work should link anesthesia processes to risk-adjusted patient outcomes, expand participation from smaller institutions, develop automated error-detection tools, and evaluate whether registry-informed interventions improve safety and efficiency.

Study Information

Study Type
Cohort
Research Domain
Prevention
Evidence Level
III - Large multicenter retrospective observational registry analysis providing strong descriptive and quality-improvement evidence but limited causal inference.
Study Design