Start Submission Become a Reviewer

Reading: Data Extraction And Management In Networks Of Observational Health Care Databases For Scient...

Download

A- A+
dyslexia friendly

Comparative case study

Data Extraction And Management In Networks Of Observational Health Care Databases For Scientific Research: A Comparison Among EU-ADR, OMOP, Mini-Sentinel And MATRICE Strategies

Authors:

Rosa Gini ,

Agenzia regionale di sanità della Toscana, Florence, Italy; and Erasmus MC University Medical Center, Department of Medical Informatics, Rotterdam, Netherlands
X close

Martijn Schuemie,

Janssen Research & Development, Epidemiology, Titusville, New Jersey, United States; and Observational Health Data Sciences and Informatics (OHDSI) New York, New York, United States
X close

Jeffrey Brown,

Harvard Medical School, Department of Population Medicine, Boston, Massachusetts, United States
X close

Patrick Ryan,

Janssen Research & Development, Epidemiology, Titusville, New Jersey, United States; and Observational Health Data Sciences and Informatics (OHDSI) New York, New York, United States
X close

Edoardo Vacchi,

Università degli Studi di Milano, Dipartimento di Informatica, Milan, Italy
X close

Massimo Coppola,

Consiglio Nazionale delle Ricerche, Istituto di Scienza e Tecnologie dell'Informazione, Pisa, Italy
X close

Walter Cazzola,

Università degli Studi di Milano, Dipartimento di Informatica, Milan, Italy
X close

Preciosa Coloma,

Erasmus MC University Medical Center, Department of Medical Informatics, Rotterdam, Netherlands
X close

Roberto Berni,

Agenzia regionale di sanità della Toscana, Florence, Italy
X close

Gayo Diallo,

Université Bordeaux, LESIM - ISPED, Bordeaux, France
X close

José Luis Oliveira,

University of Aveiro, DETI/IEETA, Aveiro, Portugal
X close

Paul Avillach,

Harvard Medical School, Center for Biomedical Informatics, Boston, Massachusetts, United States
X close

Gianluca Trifirò,

Erasmus University Medical Center, Department of Medical Informatics, Rotterdam, Netherlands
X close

Peter Rijnbeek,

Erasmus University Medical Center, Department of Medical Informatics, Rotterdam, Netherlands
X close

Mariadonata Bellentani,

Agenzia nazionale per i servizi sanitari regionali, Rome, Italy
X close

Johan van Der Lei,

Erasmus University Medical Center, Department of Medical Informatics, Rotterdam, Netherlands
X close

Niek Klazinga,

University of Amsterdam, Academic Medical Center, Amsterdam, Netherlands
X close

Miriam Sturkenboom

Erasmus University Medical Center, Department of Medical Informatics, Rotterdam, Netherlands
X close

Abstract

Introduction: We see increased use of existing observational data in order to achieve fast and transparent production of empirical evidence in health care research. Multiple databases are often used to increase power, to assess rare exposures or outcomes, or to study diverse populations. For privacy and sociological reasons, original data on individual subjects can’t be shared, requiring a distributed network approach where data processing is performed prior to data sharing.

Case Descriptions and Variation Among Sites: We created a conceptual framework distinguishing three steps in local data processing: (1) data reorganization into a data structure common across the network; (2) derivation of study variables not present in original data; and (3) application of study design to transform longitudinal data into aggregated data sets for statistical analysis. We applied this framework to four case studies to identify similarities and differences in the United States and Europe: Exploring and Understanding Adverse Drug Reactions by Integrative Mining of Clinical Records and Biomedical Knowledge(EU-ADR),Observational Medical Outcomes Partnership(OMOP), the Food and Drug Administration’s (FDA’s) Mini-Sentinel, and the Italian network—the Integration of Content Management Information on the Territory of Patients with Complex Diseases or with Chronic Conditions (MATRICE).

Findings: National networks (OMOP, Mini-Sentinel, MATRICE) all adopted shared procedures for local data reorganization. The multinational EU-ADR network needed locally defined procedures to reorganize its heterogeneous data into a common structure. Derivation of new data elements was centrally defined in all networks but the procedure was not shared in EU-ADR. Application of study design was a common and shared procedure in all the case studies. Computer procedures were embodied in different programming languages, including SAS, R, SQL, Java, and C++.

Conclusion: Using our conceptual framework we found several areas that would benefit from research to identify optimal standards for production of empirical knowledge from existing databases.

How to Cite: Gini R, Schuemie M, Brown J, Ryan P, Vacchi E, Coppola M, et al.. Data Extraction And Management In Networks Of Observational Health Care Databases For Scientific Research: A Comparison Among EU-ADR, OMOP, Mini-Sentinel And MATRICE Strategies. eGEMs (Generating Evidence & Methods to improve patient outcomes). 2016;4(1):2. DOI: http://doi.org/10.13063/2327-9214.1189
1
Views
Published on 02 Aug 2016.
Peer Reviewed

Downloads

  • PDF (EN)