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The AI and Automation in Anaesthesia (TRIPLE-A) Perioperative Database in Eastern Denmark 2017-: A Platform for
Anders Peder Højer Karlsen1,2, Marcus Ølgaard Møller1, Nikolaj Krebs Pedersen3
1Department of Anaesthesia and Intensive Care, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark.
Introduction:
Electronic health records can be used to create high-quality databases if data are structured and well-registered, which is the case for most perioperative data in the Capital and Zealand Regions of Denmark. We present the purpose and development of the AI and Automation in Anaesthesia (TRIPLE-A) database-a platform designed for epidemiology, prediction, quality control, and automated research data collection.
Methods:
Data collection from the electronic medical record (EPIC Systems Corporation, WI, USA) was approved by the Capital Region, Denmark, and ethical approval was waived. The first TRIPLE-A database version included surgical procedures performed in a public hospital in the Capital and Zealand Regions of Denmark from 2017 to 2024 without age restrictions. We received structured, timestamped raw data including event log, medicine administrations, blood samples, vital parameters, etc. In collaboration with surgical specialists, we classified surgical procedures based on procedure codes and names. Variables were coded and enriched using multiple data sources (e.g., acute kidney injury: increase in creatinine OR new dialysis or ICD-10 codes) to improve quality and mirror the clinical reasoning of physicians. Variable coding, validation and improvement continuous in iterative processes with each project in the database. The database is scheduled for updates every 6 months and as needed, currently approved to December 2030 with plans for future extension. The database is used for multiple purposes in research with broad collaboration.
Results:
The first version of the TRIPLE-A database consists of 1,142,108 surgeries in 675,790 patients. Data were processed into 17 summary tables (anaesthesia, airway management, complications, etc.) including a total of 1617 variables. The database currently provides data for 34 research projects.
Conclusion:
TRIPLE-A is a continuously updated, granular, high-quality perioperative database. It will be used for (1) high-quality epidemiological research, (2) automated data retrieval into case report forms in cohort studies and randomized trials, (3) monitoring and evaluation of clinical implementation of interventions, and (4) development of perioperative prediction models for risk stratification and individualized treatment.
