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. 2023 Apr;37(2):461-472.
doi: 10.1007/s10877-022-00898-y. Epub 2022 Aug 6.

Development and usage of an anesthesia data warehouse: lessons learnt from a 10-year project

Antoine Lamer  1   2 , Mouhamed Djahoum Moussa  3 , Romaric Marcilly  4   5 , Régis Logier  5 , Benoit Vallet  4 , Benoît Tavernier  4   6
Affiliations

Development and usage of an anesthesia data warehouse: lessons learnt from a 10-year project

Antoine Lamer et al. J Clin Monit Comput. 2023 Apr.

Abstract

This paper describes the development and implementation of an anesthesia data warehouse in the Lille University Hospital. We share the lessons learned from a ten-year project and provide guidance for the implementation of such a project. Our clinical data warehouse is mainly fed with data collected by the anesthesia information management system and hospital discharge reports. The data warehouse stores historical and accurate data with an accuracy level of the day for administrative data, and of the second for monitoring data. Datamarts complete the architecture and provide secondary computed data and indicators, in order to execute queries faster and easily. Between 2010 and 2021, 636 784 anesthesia records were integrated for 353 152 patients. We reported the main concerns and barriers during the development of this project and we provided 8 tips to handle them. We have implemented our data warehouse into the OMOP common data model as a complementary downstream data model. The next step of the project will be to disseminate the use of the OMOP data model for anesthesia and critical care, and drive the trend towards federated learning to enhance collaborations and multicenter studies.

Keywords: Anesthesia information management system; Data reuse; Data warehouse; Database; Retrospective studies.

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Conflict of interest statement

The authors have no relevant financial or non-financial interests to disclose.

Figures

Fig. 1
Fig. 1
Data warehouse architecture and process. AIMS Anesthesia Information Management System, PMSI Programme de Médicalisation des Systèmes d’Information (hospital discharge reports)
Fig. 2
Fig. 2
Data model of the data warehouse and the datamarts. Tables of the data warehouse store historical and precise data, at the greatest level of detail, and are linked to each other by foreign key relationships. Tables of the datamarts are constituted of secondary computed data
Fig. 3
Fig. 3
Challenges encountered over the course of a data warehouse project. Red items represent challenges that will stop the project if they are not fully mastered
Fig. 4
Fig. 4
Tips for setting up and managing a data warehouse project
See this image and copyright information in PMC

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