- Literature search
We reviewed 137 citations from PubMed and four reports from the following organizations: OECD (Organization for Economic Co-operation and Development) [12], Euro-REACH [13], HBM4EU (Human Biomonitoring for Europe) [14], EUROCISS (European Cardiovascular Indicators Surveillance Set) [15], to develop this questionnaire (Fig. 1).
Fig. 1: Flow diagram of studies using linked data and artificial intelligence for health status monitoring to develop a questionnaire identifying various practices of data linkages across European countries in 2019 (insert here)
Thirty-one European countries [28 EU-MSs + 2 EEA (Iceland and Norway) + Others (Serbia)] were invited to participate in the WP9 survey and twenty-nine countries (i.e., EU MSs 27 + EEA 1 [Norway] + Others 1 [Serbia]) participated with a response rate of 94% (29/31). Hungary, Iceland and Northern Ireland did not participate. For the United Kingdom, data were provided separately by the three countries England, Scotland and Wales but was counted as one member state. The results have been validated by the all survey respondents.
- Use of data linkage in routine public health activities
Our survey results highlighted that 24 European countries perform data linkage in their routine public health activities. These countries link administrative data such as EHRs, mortality data, disease specific registries whereas six of them (Cyprus, Italy, Poland, Portugal, Spain and Slovakia) are also developing this technique further to link with different other data sources (i.e., demographic data, domestic/leisure accidents data, congenital anomalies registry). Ireland and Latvia have ongoing initiatives of data linkage (Table 1.1).
Table1.1: Current status of European countries using data linkage in routine public health activities in 2019 for innovative use of data sources
Use of Data Linkage
|
|
Advanced
N = 24
|
In progress*
N = 8
|
Not yet
N = 3
|
European Countries
|
AT, BE, BG, CY, CZ, DE, DK, EE, ES, FI, FR, HR, IT, LT, MT, NL, NO, PL, PT, SI, SK, SRB, SW, UK (ENG, SC, WL)
|
CY, ES, IE, IT, PL, PT, SK, LV
|
GR, LU, RO
|
* 6 countries (CY, ES, IT, PL, PT & SK) use data linkage in routine (i.e., advanced) but also developing further this technology to link different other data sources (i.e., in progress).
Three countries (Greece, Luxembourg and Romania) have not yet planned any perspectives to integrate data linkage in routine public health activities. Following reasons were mentioned by some countries for not having institutionalized data linkage in their country: lack of a public health institution which should collect and govern the health related data, data linkage is not part of the health agenda, lack of commitment from the ministry of health, lack of resources to establish a national health information system, and the institutional complexity of the Ministry of Health and strict laws and regulations which hinder data linkage with different data sources.
Objectives of data linkage: Data linkage are performed in routine for different objectives such as for health status monitoring, health system performance, health policy or for scientific research (i.e., public health, epidemiology or clinical) purposes. Our results showed that data linkage was performed for health status monitoring in 20 countries (BE, CY, CZ, DE, DK, EE, ES, FI, FR, HR, IT, LT, MT, NL, PT, SI, SK, SRB, SW, UK (SC, WL), for health policy development in 13 (AT, BE, BG, DK, EE, FR, MT, NL, NO, PL, SK, SW, UK (SC, WL) and for scientific research (public health, epidemiological and clinical) purposes in 13 (BE, CZ, DE, DK, EE, ES, FI, FR, NL, PT, SI, SW, UK (ENG, SC, WL). Finland, Spain, Sweden and Scotland also perform data linkages to identify the risk factors. In Sweden, data linkage is also used to monitor compliance with national treatment guidelines to improve health care quality.
Data sources used for linkage: Our results showed that 24 European countries who perform data linkage in routine, used most frequently five following data sources: health-related administrative data sources, non-health related administrative data sources, disease-specific registries, national health surveys, population-based epidemiological cohort and clinical trials. (Table 1.2). These data sources are linked with each other in different combinations and some examples of various combinations used across member countries, are reported in table 1.3. These countries perform data linkage by using one of following information: social security number, patient unique identification number, person unique pseudonymous identifier, encrypted personal identification number, citizen or national identification number. In Ireland, the lack of a unique patient identifier number limits the potential to link with different data sources.
Table 1.2: Data sources used for linkage across European countries in 2019 for innovative use of data sources
S/No
|
Data sources used for linkage
|
European countries
|
Advanced
N = 24
|
In progress
N = 2
|
1
|
Health-related administrative data sources (i.e., Electronic Health Records) ʘ
|
Primary care visits, emergency care, referral records, hospital discharge, prescribed medications, health insurance claims, diagnostics procedures, laboratory tests, biobank
|
21
|
AT, BE, CY, DE, DK, EE, ES, FI, FR, HR, IT, LT, MT, NL, NO, PT, SI, SK, SRB, SW, UK[ENG, SC, WL]
|
LV
|
2
|
Non-health related administrative data sources ǂ
|
Birth and mortality database, education level, income tax, GIS, occupation, housing conditions, criminal statistics, land and housing, socioeconomic, census (demographic), house of handicap persons, environmental, road and transport, air pollution, UV light exposure
|
22
|
BE, CY, CZ, DE, DK, EE, ES, FI, FR, HR, IT, LT, MT, NL, NO, PL, PT, SI, SK, SRB, SW, UK[ENG, SC, WL]
|
IE, LV
|
3
|
Disease-specific registries
|
Cancer, diabetes, cardiovascular, congenital malformation, tuberculosis, HIV/AIDS, inflammatory bowel disease, renal, reproductive health, dementia, organ transplantation, traffic accidents/trauma or injury, hospital registry of domestic and leisure accidents
|
22
|
BE, BG, CY, CZ, DE, DK, EE, ES, FI, FR, HR, IE, LV, MT, NL, NO, PL, PT, SK, SRB, SW, UK [ENG, SC, WL]
|
LV
|
4
|
National health surveys*
|
National health examination and interview surveys
|
15
|
BE, CZ, DK, DE, EE, ES, FI, FR, IT, NL, NO, PT, SI, SW, UK [ENG, SC, WL]
|
PL
|
5
|
Population-based epidemiological cohort/National cohorts
|
DANCOS, IDEFICS, CONSTANCE, ELFE, Growing up in Scotland, HealthWise Wales cohort, Millennium cohort, Caerphilly cohort study
|
7
|
DK, EE, FI, FR, NO, PL, UK [ENG, SC, WL]
|
|
6
|
Clinical trials data
|
FINGER, PRISMATIC
|
3
|
DK, FI, UK [ENG, WL]
|
|
ʘ Latvia is developing data linkage techniques to link EHRs with other data sources.
ǂ In Ireland, income database is linked with EHRs of prescribing medicine at small level. Latvia is developing data linkage techniques to link birth and mortality databases either with EHRs or with disease-specific registries.
* Poland is planning to link this national health survey data with other health data sources in near future. In Ireland, this is done for specific surveys such as housing and health conditions at small scale.
General characteristics of linked dataset: Our results showed that among 24 European countries who perform data linkage in routine, 17 do linkage at national level (Table 1.4). France, Portugal and Scotland do data linkage both at national and sub-national levels. Denmark, Germany, Norway and Sweden do data linkage at all levels. 23 countries either use the deterministic type of linkage (12 countries) or a combination of deterministic and probabilistic linkage (11 countries). Among 16/24 countries, linked data is available and is used in routine. Among 12/24 countries, the register owner (i.e., who governs the data register) provides the approval to access linked data. Among 15/24 countries, the accessibility to linked data is in routine or permanent whereas, in 13 countries, the accessibility could be ad-hoc or at intermittent basis depending on the project. Among 15/24 countries, linked data do not operate in real-time (i.e., integrate the updated information with minimum delay in time). Among 19/24 countries, linked data are flexible to integrate new variables.
There are ongoing projects on data linkage (i.e., in next five years) aiming to integrate this technology in their routine public health activities in following European countries: Austria, Cyprus, Czech Republic, Ireland, Italy, Latvia, Norway, Poland, Portugal, and Spain.
Table 1.4: General characteristics of linked datasets in European countries in 2019 for innovative use of data sources (insert table here)
- Use of artificial intelligence (AI) in routine public health activities
The use of AI is not frequent across European countries (Table 2). Only five countries have reported applying following techniques in routine public health activities: machine learning (Denmark, Finland, Sweden, and UK-Wales), natural language processing (Finland, Sweden, and UK-Wales), Markov decision process (Finland), support vector machine (Finland, UK-Wales), data mining (Finland) and TSP [Travelling Salesman Problem] modelling (Norway). Denmark can apply these techniques not only at a national level but also at a metropolitan level.
There are ongoing projects on the use of the AI (i.e., in next five years) to integrate this technology in routine public health activities in following countries: Croatia, Czech Republic, France, Germany, Norway, Portugal, and Spain. The objectives of these initiatives are for epidemiological research and surveillance of non-communicable and communicable disease estimating the prevalence and prediction of incidences of certain health conditions at various geographical levels.
Two countries mentioned that due to lack of human resources (Lithuania) and capacities/skills (Republic of Serbia) within their public health institutes, AI techniques are not applied in routine public health activities.
Some European countries also mentioned use of classical statistical techniques without the use of AI (Table 2).
Table 2: Current status of European countries using artificial intelligence in routine public health activities in 2019
Use of Artificial Intelligence (AI)
|
|
Advanced
N = 5
|
In progress
N = 9
|
Not yet
N = 16
|
European countries
|
DK, FI, NO, SW, UK-WL
|
AT, CZ, DE, ES, FR, HR, PL, PT, SK
|
BE, BG, CY, EE, GR, IE, IT, LT, LU, LV, MT, NL, RO, SL, SRB, UK (ENG, SC)
|
Level of application of AI
|
National level
|
DK, FI, NO, SW, UK- WL
|
Sub-national level
|
|
Metropolitan level
|
DK, SW
|
Use of classical statistics without the use of AI
|
|
Advanced
N = 19
|
In progress
N = 5*
|
Not yet
N = 8
|
European countries
|
BE, BG, CZ, DE, EE, ES, DK, FR, FI, IT, MT, NL, NO, PL, PT, SI, SK, SW, UK (ENG, SC, WL)
|
AT, CZ, ES, HR, SK
|
CY, GR, IE, LT, LU, LV, RO, SRB
|
Level of use of classical statistics without AI
|
National level
|
BE, BG, CZ, DK, EE, FR, FI, IT, NL, NO, PL, PT, SK, SW, UK- WL
|
Sub-national level
|
DE, ES, IT, PL, NO, SI, UK (ENG, SC)
|
Metropolitan level
|
DK, MT, NO
|
*Two countries (CZ & SK) use classical statistic in routine (i.e., advanced) but also developing further this technology (i.e., in progress)
|
- Health indicators estimated using linked data
Using linked data, the majority of European countries estimate following health indicators:
Health outcome indicators
Participants were asked to select at least three health conditions and to report the related health outcome indicators which are most important for public health in their country. Using linked data, 46 health outcome indicators related to following seven health conditions were reported from 22 countries: cardiovascular (14), neurodegenerative disease (6), maternal and perinatal health (6), diabetes (6), suicide/trauma/injury (7), cancer (6) and hepatic failure (1) (Table 3.1). The main objectives to estimate these indicators were for public health monitoring and research purposes and the level of estimation was mainly at national and sub-national levels.
Table 3.1: Description of health outcome indicators estimated using linked data across European countries in 2019 (insert table here)
Health determinants
For the health determinants, participants were asked to report the corresponding determinants of the identified health conditions. 34 health determinants related to various health conditions were reported by 15 member states (Table 3.2). These determinants are related to the physical environment (12), socioeconomic and environment (10), health behavior and lifestyle (6) and biological and metabolic parameters (3) (Table 3.2). These determinants were used to measure the potential associations between these risk factors and health conditions for public health monitoring and research purposes. These determinants can be stratified by age, sex, socioeconomic status and by area of residence.
Table 3.2: Description of health determinants using linked data across European countries in 2019 (insert table here)
Health intervention indicators
Participants were asked to report at least three health intervention indicators under three categories (i.e., prevention, promotion, others) corresponding to the given health conditions which are most important for public health in their country. Using linked data, 23 health intervention indicators related to following six health conditions were reported from 17 member states: maternal and perinatal health (7), cancer (6), diabetes (4), cardiovascular (2), neurodegenerative disease (2), suicide/trauma/injury (1) and lower/upper respiratory infections (1), (Table 3.3). The main objectives to estimate these indicators were to guide health policy process, public health monitoring and for research purposes. These intervention indicators are estimated mainly at national and sub-national levels and currently are in use.
Table 3.3: Description of health intervention indicators estimated using linked data across European countries in 2019 (insert table here)