EUROlinkCAT Common Data Model

Maria Loane, James Densem, Joan Morris, Joachim Tan

Research output: Contribution to conferenceAbstract

Abstract

Background:
Over 130,000 children are born in Europe every year with congenital anomalies which are a major cause of infant mortality, childhood morbidity and long-term disability. A European data linkage study (EUROlinkCAT) aims to investigate the health and educational outcomes of children up to 10 years of age with congenital anomalies, born between 1995 and 2014. While congenital anomaly data including information on potential risk factors are standardised across the EUROCAT network, information on mortality, morbidity and educational outcomes are not.
Objective:
To create a common data model that transforms key variables in local databases to standardised formats enabling data on health and educational outcomes to be pooled and analysed across multiple registries.
Method:
Twenty-two EUROCAT registries in fourteen countries are participating in the study. Each registry records uniformly coded data on cases of congenital anomaly registered in their local population using the EUROCAT Data Management Program. The registries will link their congenital anomaly data to their local mortality, hospital discharge, prescriptions and educational data. The linked individual case data cannot leave the local institution or “safe haven” environment, therefore verification and validation of all derived variables, data transformations and proxy variables must be performed locally.
Findings:
Creating a common data model is challenging as there are diverse coding classification systems, languages, healthcare and educational systems in Europe. As with many administrative datasets, the common data model is based on coded data rather than the often richer “free text” information.
Conclusion:
The use of administrative datasets across Europe enables pooling of data on rare outcomes and allows hypotheses on the health and education of children to be investigated. However, a common data model must be applied to ensure that data from multiple sites conform to a standard format.

Conference

ConferenceInternational Conference for Administrative Data Research
Abbreviated titleADR2018
CountryUnited Kingdom
CityBelfast
Period21/06/1822/06/18
Internet address

Fingerprint

Registries
Morbidity
Information Services
Information Storage and Retrieval
Health
Infant Mortality
Proxy
Hospital Mortality
Health Education
Prescriptions
Meta-Analysis
Language
Databases
Delivery of Health Care
Mortality
Population
Datasets

Cite this

Loane, M., Densem, J., Morris, J., & Tan, J. (2018). EUROlinkCAT Common Data Model. 1. Abstract from International Conference for Administrative Data Research, Belfast, United Kingdom. https://doi.org/doi.org/10.23889/ijpds.v3i2.537
Loane, Maria ; Densem, James ; Morris, Joan ; Tan, Joachim. / EUROlinkCAT Common Data Model. Abstract from International Conference for Administrative Data Research, Belfast, United Kingdom.
@conference{7c74584c2ddf41c6930acd738e784da1,
title = "EUROlinkCAT Common Data Model",
abstract = "Background:Over 130,000 children are born in Europe every year with congenital anomalies which are a major cause of infant mortality, childhood morbidity and long-term disability. A European data linkage study (EUROlinkCAT) aims to investigate the health and educational outcomes of children up to 10 years of age with congenital anomalies, born between 1995 and 2014. While congenital anomaly data including information on potential risk factors are standardised across the EUROCAT network, information on mortality, morbidity and educational outcomes are not. Objective:To create a common data model that transforms key variables in local databases to standardised formats enabling data on health and educational outcomes to be pooled and analysed across multiple registries.Method:Twenty-two EUROCAT registries in fourteen countries are participating in the study. Each registry records uniformly coded data on cases of congenital anomaly registered in their local population using the EUROCAT Data Management Program. The registries will link their congenital anomaly data to their local mortality, hospital discharge, prescriptions and educational data. The linked individual case data cannot leave the local institution or “safe haven” environment, therefore verification and validation of all derived variables, data transformations and proxy variables must be performed locally. Findings: Creating a common data model is challenging as there are diverse coding classification systems, languages, healthcare and educational systems in Europe. As with many administrative datasets, the common data model is based on coded data rather than the often richer “free text” information. Conclusion:The use of administrative datasets across Europe enables pooling of data on rare outcomes and allows hypotheses on the health and education of children to be investigated. However, a common data model must be applied to ensure that data from multiple sites conform to a standard format.",
author = "Maria Loane and James Densem and Joan Morris and Joachim Tan",
year = "2018",
month = "6",
day = "13",
doi = "doi.org/10.23889/ijpds.v3i2.537",
language = "English",
pages = "1",
note = "International Conference for Administrative Data Research : Belfast, UK, 21-22 June 2018, ADR2018 ; Conference date: 21-06-2018 Through 22-06-2018",
url = "https://adr2018.wordpress.com/",

}

Loane, M, Densem, J, Morris, J & Tan, J 2018, 'EUROlinkCAT Common Data Model' International Conference for Administrative Data Research, Belfast, United Kingdom, 21/06/18 - 22/06/18, pp. 1. https://doi.org/doi.org/10.23889/ijpds.v3i2.537

EUROlinkCAT Common Data Model. / Loane, Maria; Densem, James; Morris, Joan; Tan, Joachim.

2018. 1 Abstract from International Conference for Administrative Data Research, Belfast, United Kingdom.

Research output: Contribution to conferenceAbstract

TY - CONF

T1 - EUROlinkCAT Common Data Model

AU - Loane, Maria

AU - Densem, James

AU - Morris, Joan

AU - Tan, Joachim

PY - 2018/6/13

Y1 - 2018/6/13

N2 - Background:Over 130,000 children are born in Europe every year with congenital anomalies which are a major cause of infant mortality, childhood morbidity and long-term disability. A European data linkage study (EUROlinkCAT) aims to investigate the health and educational outcomes of children up to 10 years of age with congenital anomalies, born between 1995 and 2014. While congenital anomaly data including information on potential risk factors are standardised across the EUROCAT network, information on mortality, morbidity and educational outcomes are not. Objective:To create a common data model that transforms key variables in local databases to standardised formats enabling data on health and educational outcomes to be pooled and analysed across multiple registries.Method:Twenty-two EUROCAT registries in fourteen countries are participating in the study. Each registry records uniformly coded data on cases of congenital anomaly registered in their local population using the EUROCAT Data Management Program. The registries will link their congenital anomaly data to their local mortality, hospital discharge, prescriptions and educational data. The linked individual case data cannot leave the local institution or “safe haven” environment, therefore verification and validation of all derived variables, data transformations and proxy variables must be performed locally. Findings: Creating a common data model is challenging as there are diverse coding classification systems, languages, healthcare and educational systems in Europe. As with many administrative datasets, the common data model is based on coded data rather than the often richer “free text” information. Conclusion:The use of administrative datasets across Europe enables pooling of data on rare outcomes and allows hypotheses on the health and education of children to be investigated. However, a common data model must be applied to ensure that data from multiple sites conform to a standard format.

AB - Background:Over 130,000 children are born in Europe every year with congenital anomalies which are a major cause of infant mortality, childhood morbidity and long-term disability. A European data linkage study (EUROlinkCAT) aims to investigate the health and educational outcomes of children up to 10 years of age with congenital anomalies, born between 1995 and 2014. While congenital anomaly data including information on potential risk factors are standardised across the EUROCAT network, information on mortality, morbidity and educational outcomes are not. Objective:To create a common data model that transforms key variables in local databases to standardised formats enabling data on health and educational outcomes to be pooled and analysed across multiple registries.Method:Twenty-two EUROCAT registries in fourteen countries are participating in the study. Each registry records uniformly coded data on cases of congenital anomaly registered in their local population using the EUROCAT Data Management Program. The registries will link their congenital anomaly data to their local mortality, hospital discharge, prescriptions and educational data. The linked individual case data cannot leave the local institution or “safe haven” environment, therefore verification and validation of all derived variables, data transformations and proxy variables must be performed locally. Findings: Creating a common data model is challenging as there are diverse coding classification systems, languages, healthcare and educational systems in Europe. As with many administrative datasets, the common data model is based on coded data rather than the often richer “free text” information. Conclusion:The use of administrative datasets across Europe enables pooling of data on rare outcomes and allows hypotheses on the health and education of children to be investigated. However, a common data model must be applied to ensure that data from multiple sites conform to a standard format.

U2 - doi.org/10.23889/ijpds.v3i2.537

DO - doi.org/10.23889/ijpds.v3i2.537

M3 - Abstract

SP - 1

ER -

Loane M, Densem J, Morris J, Tan J. EUROlinkCAT Common Data Model. 2018. Abstract from International Conference for Administrative Data Research, Belfast, United Kingdom. https://doi.org/doi.org/10.23889/ijpds.v3i2.537