Innovative use of data sources: a cross-sectional study of data linkage and artificial intelligence practices across European countries

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14110%2F20%3A00116003" target="_blank" >RIV/00216224:14110/20:00116003 - isvavai.cz</a>

Result on the web

<a href="https://archpublichealth.biomedcentral.com/track/pdf/10.1186/s13690-020-00436-9" target="_blank" >https://archpublichealth.biomedcentral.com/track/pdf/10.1186/s13690-020-00436-9</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1186/s13690-020-00436-9" target="_blank" >10.1186/s13690-020-00436-9</a>

Result language

angličtina

Original language name

Innovative use of data sources: a cross-sectional study of data linkage and artificial intelligence practices across European countries

Original language description

Background The availability of data generated from different sources is increasing with the possibility to link these data sources with each other. However, linked administrative data can be complex to use and may require advanced expertise and skills in statistical analysis. The main objectives of this study were to describe the current use of data linkage at the individual level and artificial intelligence (AI) in routine public health activities, to identify the related estimated health indicators (i.e., outcome and intervention indicators) and health determinants of non-communicable diseases and the obstacles to linking different data sources. Method We performed a survey across European countries to explore the current practices applied by national institutes of public health, health information and statistics for innovative use of data sources (i.e., the use of data linkage and/or AI). Results The use of data linkage and AI at national institutes of public health, health information and statistics in Europe varies. The majority of European countries use data linkage in routine by applying a deterministic method or a combination of two types of linkages (i.e., deterministic &amp; probabilistic) for public health surveillance and research purposes. The use of AI to estimate health indicators is not frequent at national institutes of public health, health information and statistics. Using linked data, 46 health outcome indicators, 34 health determinants and 23 health intervention indicators were estimated in routine. The complex data regulation laws, lack of human resources, skills and problems with data governance, were reported by European countries as obstacles to routine data linkage for public health surveillance and research. Conclusions Our results highlight that the majority of European countries have integrated data linkage in their routine public health activities but only a few use AI. A sustainable national health information system and a robust data governance framework allowing to link different data sources are essential to support evidence-informed health policy development. Building analytical capacity and raising awareness of the added value of data linkage in national institutes is necessary for improving the use of linked data in order to improve the quality of public health surveillance and monitoring activities.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

30304 - Public and environmental health

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

ARCHIVES OF PUBLIC HEALTH

ISSN

0778-7367

e-ISSN

2049-3258

Volume of the periodical

78

Issue of the periodical within the volume

1

Country of publishing house

GB - UNITED KINGDOM

Number of pages

11

Pages from-to

1-11

UT code for WoS article

000542574800001

EID of the result in the Scopus database

2-s2.0-85089562817