Health data collection methods and procedures across EU member states: findings from the InfAct Joint Action on health information

Abstract

Background Health-related data are collected from a variety of sources for different purposes, including secondary use for population health monitoring (HM) and health system performance assessment (HSPA). Most of these data sources are not included in databases of international organizations (e.g., WHO, OECD, Eurostat), limiting their use for research activities and policy making. This study aims at identifying and describing collection methods, quality assessment procedures, availability and accessibility of health data across EU Member States (MS) for HM and HSPA. Methods A structured questionnaire was developed and administered through an online platform to partners of the InfAct consortium form EU MS to investigate data collections applied in HM and HSPA projects, as well as their methods and procedures. A descriptive analysis of the questionnaire results was performed. Results Information on 91 projects from 18 EU MS was collected. In these projects, data were mainly collected through administrative sources, population health interview or health examination surveys and from electronic medical records. Tools and methods used for data collection were mostly mandatory reports, self-administered questionnaires, or record linkage of various data sources. One-third of the projects shared data with EU research networks and less than one-third performed quality assessment of their data collection procedures using international standardized criteria. Macrodata were accessible via open access and reusable in 22 projects. Microdata were accessible upon specific request and reusable in 15 projects based on data usage licenses. Metadata was available for the majority of the projects, but followed reporting standards only in 29 projects. Overall, compliance to FAIR Data principles (Findable, Accessible, Interoperable, and Reusable) was not optimal across the EU projects. Conclusions Data collection and exchange procedures differ across EU MS and research data are not always available, accessible, comparable or reusable for further research and evidence-based policy making. There is a need for an EU-level health information infrastructure and governance to promote and facilitate sharing and dissemination of standardized and comparable health data, following FAIR Data principles, across the EU.

Food intake markers in Sisvan: temporal trends in coverage and integration with e-SUS APS, Brazil 2015-2019

“…The use of e-SUS APS has increased across the country in recent years. In 2019, 92.2% of municipalities displayed a level of implementation different to "not implemented" 34 , which is in line with recent international discussions on health data integration 35 . However, the findings do not allow us to infer that e-SUS APS utilization has contributed to substantial increases in coverage of recording of food intake markers in Brazil.…”

Marcadores do consumo alimentar do Sisvan: tendência temporal da cobertura e integração com o e-SUS APS, 2015-2019

“…Apesar da possibilidade de registro de dados de VAN pela Estratégia e-SUS APS e o acompanhamento de indicadores pelo Sisvan Web 21 , devese apontar que a adoção do e-SUS APS como sistema único para entrada dos dados de VAN ainda não é unânime nos municípios e que há funcionalidades do Sisvan Web que não foram totalmente contempladas no e-SUS APS, como a identificação de grupos prioritários e de estratégias de vigilância epidemiológica por meio de ferramentas de customização 29 . O uso do e-SUS APS tem evoluído no território nacional nos últimos anos, sendo que, em 2019, 92,2% dos municípios exibiram grau de implantação diferente de "não implantado" 34 , de forma alinhada a discussões internacionais recentes sobre a integração de dados de saúde 35 . Contudo, não parece ser possível inferir que o início de seu uso já contribui para incrementos substanciais da cobertura do registro de marcadores do consumo alimentar no Brasil.…”

Digital Health Technologies for Medical Devices – Real World Evidence Collection – Challenges and Solutions Towards Clinical Evidence

“…Potential clinical data collection sources may include (but are not limited to) clinical trials (CTs), clinical investigations (CIs), electronic health records/ medical records, administrative data (e.g., hospital records, pharmaceutical prescriptions), health and postmarket clinical follow-up surveys, and patient registries [5][6][7][8][9] (See Figure 2). The MDR introduces post-market surveillance (PMS), and in particular, post-market clinical follow-up (PMCF) as a clinical data source [1].…”

“…The type of data to be collected will determine the methods and processes used for data collection and data analysis. Paper-based, as well as electronic and hybrid methods (combination of paper-based and electronic means), are the most common methods used for data collection activities [8,12]. Depending on the design of the clinical study and the related endpoints, clinical data are generated and/or collected by the investigator(s), research staff, and/or participants/patients [13].…”