Literature DB >> 35933465

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

Antoine Lamer1,2, Mouhamed Djahoum Moussa3, Romaric Marcilly4,5, Régis Logier5, Benoit Vallet4, Benoît Tavernier4,6.   

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.
© 2022. The Author(s).

Entities:  

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

Year:  2022        PMID: 35933465     DOI: 10.1007/s10877-022-00898-y

Source DB:  PubMed          Journal:  J Clin Monit Comput        ISSN: 1387-1307            Impact factor:   1.977


  9 in total

1.  Comparison of manual and automated documentation of adverse events with an Anesthesia Information Management System (AIMS).

Authors:  M Benson; A Junger; A Michel; G Sciuk; L Quinzio; K Marquardt; G Hempelmann
Journal:  Stud Health Technol Inform       Date:  2000

2.  Implementation of an Anesthesia Information Management System (AIMS).

Authors:  James R Douglas; Melody J Ritter
Journal:  Ochsner J       Date:  2011

3.  Specifications for the Routine Implementation of Federated Learning in Hospitals Networks.

Authors:  Antoine Lamer; Alexandre Filiot; Yannick Bouillard; Paul Mangold; Paul Andrey; Jessica Schiro
Journal:  Stud Health Technol Inform       Date:  2021-05-27

4.  Automated Generation of Individual and Population Clinical Pathways with the OMOP Common Data Model.

Authors:  Fabio Boudis; Guillaume Clement; Amelie Bruandet; Antoine Lamer
Journal:  Stud Health Technol Inform       Date:  2021-05-27

5.  Architecting the Data Loading Process for an i2b2 Research Data Warehouse: Full Reload versus Incremental Updating.

Authors:  Andrew R Post; Miao Ai; Akshatha Kalsanka Pai; Marc Overcash; David S Stephens
Journal:  AMIA Annu Symp Proc       Date:  2018-04-16

6.  Automated Data Aggregation for Time-Series Analysis: Study Case on Anaesthesia Data Warehouse.

Authors:  Antoine Lamer; Mathieu Jeanne; Grégoire Ficheur; Romaric Marcilly
Journal:  Stud Health Technol Inform       Date:  2016

7.  From Data Extraction to Analysis: Proposal of a Methodology to Optimize Hospital Data Reuse Process.

Authors:  Antoine Lamer; Grégoire Ficheur; Louis Rousselet; Marine van Berleere; Emmanuel Chazard; Alexandre Caron
Journal:  Stud Health Technol Inform       Date:  2018

8.  Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers.

Authors:  George Hripcsak; Jon D Duke; Nigam H Shah; Christian G Reich; Vojtech Huser; Martijn J Schuemie; Marc A Suchard; Rae Woong Park; Ian Chi Kei Wong; Peter R Rijnbeek; Johan van der Lei; Nicole Pratt; G Niklas Norén; Yu-Chuan Li; Paul E Stang; David Madigan; Patrick B Ryan
Journal:  Stud Health Technol Inform       Date:  2015
  9 in total

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