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

From Data Extraction to Analysis: Proposal of a Methodology to Optimize Hospital Data Reuse Process. Lamer, A., Ficheur, G., Rousselet, L., van Berleere, M., Chazard, E., & Caron, A. Studies in Health Technology and Informatics, 247:41–45, 2018.
abstract bibtex

In the Lille University Hospital (North of France), data from the Anesthesia Information Management System (Diane® are linked to the Hospital Information System and stored in a dedicated data warehouse since 2010. These electronic medical records need to be reused and analyzed for observational studies. The aim of this paper is to describe the framework developed to structure the operation of that anesthesia data warehouse for research purposes. The presented framework is structured around three meetings between clinicians, computer scientists, and statisticians. The data scientist acts as a coordinator, leads meetings, and checks each milestone. Reuse of anesthesia-related electronic medical record for research purposes is only allowed through this framework. The aim of the first meeting is to decide the primary and secondary objectives of the study. The aim of the second meeting is to validate the statistical protocol. The data are extracted and the statistical analyses are performed. Finally, the results are presented, explained and discussed during the third meeting. During a 6 months period, 27 projects were included in the framework leading to 5 scientific communications. As a result, case studies with extraction and/or analysis situations are presented. This collaboration led to an empowerment process between all three actors, which increased efficiency of the workflow. Implementation of this framework will keep encouraging collaborative publication in order to provide reproducible research evidence.

@article{lamer_data_2018,
	title = {From {Data} {Extraction} to {Analysis}: {Proposal} of a {Methodology} to {Optimize} {Hospital} {Data} {Reuse} {Process}},
	volume = {247},
	issn = {0926-9630},
	shorttitle = {From {Data} {Extraction} to {Analysis}},
	abstract = {In the Lille University Hospital (North of France), data from the Anesthesia Information Management System (Diane® are linked to the Hospital Information System and stored in a dedicated data warehouse since 2010. These electronic medical records need to be reused and analyzed for observational studies. The aim of this paper is to describe the framework developed to structure the operation of that anesthesia data warehouse for research purposes. The presented framework is structured around three meetings between clinicians, computer scientists, and statisticians. The data scientist acts as a coordinator, leads meetings, and checks each milestone. Reuse of anesthesia-related electronic medical record for research purposes is only allowed through this framework. The aim of the first meeting is to decide the primary and secondary objectives of the study. The aim of the second meeting is to validate the statistical protocol. The data are extracted and the statistical analyses are performed. Finally, the results are presented, explained and discussed during the third meeting. During a 6 months period, 27 projects were included in the framework leading to 5 scientific communications. As a result, case studies with extraction and/or analysis situations are presented. This collaboration led to an empowerment process between all three actors, which increased efficiency of the workflow. Implementation of this framework will keep encouraging collaborative publication in order to provide reproducible research evidence.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Lamer, Antoine and Ficheur, Grégoire and Rousselet, Louis and van Berleere, Marine and Chazard, Emmanuel and Caron, Alexandre},
	year = {2018},
	pmid = {29677919},
	keywords = {Data Science, Electronic Medical Records, Healthcare Data Reuse, Reproducible Research, Statistical Analysis},
	pages = {41--45},
}

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