A brief overview of some terms relating to data and health

The General Data Protection Regulation (GDPR) is a regulation created by the European Union to protect people's personal data and privacy. It sets rules for how organizations collect, store, use, and share personal information and gives individuals more control over their data. Organizations must handle personal data responsibly and securely. They need clear and explicit consent to collect and process personal data. Companies must explain what data they collect, why, and how they use it. The word RGPD is the French translation of the GDPR.

Health data access bodies (HDAB) will monitor and contribute to a consistent application of the rules throughout the EU, including by advising the European Commission, while cooperating with other EU bodies and stakeholders (e.g. patient organisations). They also monitor, examine and supervise compliance by data users and data holders with the requirements in the EHDS Regulation. This body acts as a facilitator to help organizations securely access and share health data for specific purposes like research, policy-making, and innovation. They ensure that sensitive health data is handled with care, privacy, and security at the forefront. In Belgium, this responsibility is held by the Belgian Health Data Access Body (Belgian HDA). The Belgian HDA helps organizations like hospitals, universities, companies, and research institutions to access health data in a regulated way. It ensures that health data is only used for legal, ethical, and scientific purposes, with all necessary safeguards in place to protect patient privacy.

HeDERA stands for Health Data Enabled for Re-use Across Belgium. HeDERA supports the mission of the HDA to facilitate secondary use of health, healthcare and well-being data in a safe, uniform, and transparent environment. The project will especially support Belgium’s efforts to enlarge the capacity of the HDA, ensuring its connection, alignment and technical interoperability with the European Health Data Space and other European developments. HeDERA is coordinated by the Belgian Federal Public Service (FPS) Health, Food chain safety and Environment, in partnership with Sciensano.

Health Level Seven International (HL7) is a not-for-profit, ANSI-accredited standards developing organization dedicated to providing a comprehensive framework and related standards for the exchange, integration, sharing and retrieval of electronic health information.

ICD serves a broad range of uses globally and provides critical knowledge on the extent, causes and consequences of human disease and death worldwide via data that is reported and coded with the ICD. It allows the systematic recording, analysis, interpretation and comparison of mortality and morbidity data collected in different countries or regions and at different times. It also ensures semantic interoperability and reusability of recorded data for the different use cases beyond mere health statistics, including decision support, resource allocation, reimbursement, guidelines and more.

Data from different sources becomes compatible and combinable with other datasets and tools or technologies. This implies using standardized formats, languages and vocabularies.

Logical Observation Identifiers Names and Codes (LOINC) is a database and universal standard for identifying medical laboratory and clinical test results. LOINC applies universal code names and identifiers to medical terminology related to electronic health records. The purpose is to assist in the electronic exchange and gathering of clinical results (such as laboratory tests, clinical observations, outcomes management and research).

Machine learning (ML) is a type of technology that allows computers to learn and improve from experience without being explicitly programmed. Instead of giving the computer step-by-step instructions, we provide it with data and let it figure out patterns or solutions on its own. A machine learning system uses examples (data) to understand and predict outcomes or make decisions. An everyday example is recommendation systems like Netflix suggesting movies.

Mature data refers to data that is well-organized, reliable, and ready to be used effectively for decision-making or analysis. It means the data has been properly managed over time and meets key quality standards, making it trustworthy and valuable.

Metadata is "data about the data". In other words, metadata is information that describes other data, helping to explain what it is, how it can be used, and where to find it. Metadata provides valuable information but needs to be properly managed, to avoid losing its benefits. Metadata gives the ability to manage and use data effectively.