The common data model: Lessons from past projects and ongoing initiatives

Patrick Ryan; Morten Anderson; Martijn Schuemie; Alison Burke; Kevin Haynes; Kenneth Man; Helga Gardarsdottir; Marie L. De Bruin

doi:10.1002/pds.3701

The common data model: Lessons from past projects and ongoing initiatives

Patrick Ryan, Morten Anderson, Martijn Schuemie, Alison Burke, Kevin Haynes, Kenneth Man, Helga Gardarsdottir, Marie L. De Bruin

Pharmacoepidemiology and Clinical Pharmacology

Research output: Contribution to journal › Meeting Abstract › Other research output

Abstract

Background: Multi-database studies face unique challenges beyond the routine epidemiological studies. Observational research initiatives, like OMOP, MiniSentinel, EUADR, PROTECT, EMIF and ASPEN, have demonstrated the value of collaborative research and offer potential for improving the power and reliability of epidemiologic studies. Objectives: In this workshop we will give an overview of the methods applied and challenges encountered in multi-database drug effect studies. Practical experiences from Europe, the US and Asia will be shared.

Original language	English
Pages (from-to)	361-362
Number of pages	2
Journal	Pharmacoepidemiology and Drug Safety
Volume	23
Issue number	S1
DOIs	https://doi.org/10.1002/pds.3701
Publication status	Published - 1 Oct 2014

Keywords

pharmacoepidemiology
risk management
model
data base
laryngeal mask
drug effect
epidemiology
workshop
Europe
Asia
reliability

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title = "The common data model: Lessons from past projects and ongoing initiatives",

abstract = "Background: Multi-database studies face unique challenges beyond the routine epidemiological studies. Observational research initiatives, like OMOP, MiniSentinel, EUADR, PROTECT, EMIF and ASPEN, have demonstrated the value of collaborative research and offer potential for improving the power and reliability of epidemiologic studies. Objectives: In this workshop we will give an overview of the methods applied and challenges encountered in multi-database drug effect studies. Practical experiences from Europe, the US and Asia will be shared.",

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author = "Patrick Ryan and Morten Anderson and Martijn Schuemie and Alison Burke and Kevin Haynes and Kenneth Man and Helga Gardarsdottir and {De Bruin}, {Marie L.}",

note = "Special Issue: Abstracts of the 30th International Conference on Pharmacoepidemiology and Therapeutic Risk Management, October 24–27, 2014, Taipei, Taiwan",

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AU - Ryan, Patrick

AU - Anderson, Morten

AU - Schuemie, Martijn

AU - Burke, Alison

AU - Haynes, Kevin

AU - Man, Kenneth

AU - Gardarsdottir, Helga

AU - De Bruin, Marie L.

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N2 - Background: Multi-database studies face unique challenges beyond the routine epidemiological studies. Observational research initiatives, like OMOP, MiniSentinel, EUADR, PROTECT, EMIF and ASPEN, have demonstrated the value of collaborative research and offer potential for improving the power and reliability of epidemiologic studies. Objectives: In this workshop we will give an overview of the methods applied and challenges encountered in multi-database drug effect studies. Practical experiences from Europe, the US and Asia will be shared.

AB - Background: Multi-database studies face unique challenges beyond the routine epidemiological studies. Observational research initiatives, like OMOP, MiniSentinel, EUADR, PROTECT, EMIF and ASPEN, have demonstrated the value of collaborative research and offer potential for improving the power and reliability of epidemiologic studies. Objectives: In this workshop we will give an overview of the methods applied and challenges encountered in multi-database drug effect studies. Practical experiences from Europe, the US and Asia will be shared.

KW - pharmacoepidemiology

KW - risk management

KW - model

KW - data base

KW - laryngeal mask

KW - drug effect

KW - epidemiology

KW - workshop

KW - Europe

KW - Asia

KW - reliability

U2 - 10.1002/pds.3701

DO - 10.1002/pds.3701

M3 - Meeting Abstract

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EP - 362

JO - Pharmacoepidemiology and Drug Safety

JF - Pharmacoepidemiology and Drug Safety

IS - S1

ER -

The common data model: Lessons from past projects and ongoing initiatives

Abstract

Keywords

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