A brief overview of some terms relating to data and health

Secondary data refers to data that was collected by someone else for a different purpose, but can be used for new research or analysis. It's not original or newly gathered data, but rather data that's been previously collected and is now being repurposed. Secondary data is like reusing an old report or dataset that someone else made instead of gathering all the new information yourself.

Secondary use involves (re-)using health data for purposes beyond individual care, such as research, public health monitoring, or policy-making. This might include using data to track disease outbreaks or conduct studies to find new treatments. 

Sensitive data refers to information that is particularly private and confidential. It’s more private than regular data and needs extra care when it’s collected, stored, or shared. In many cases, sensitive data is subject to stricter privacy laws and regulations to ensure it is handled securely.

SHAIPED is an European initiative that will support the synergetic implementation of the EHDS regulation with the AI regulation.

SNOMED it short for Systematized Nomenclature of Medicine - Clinical Terms.SNOMED CT is a structured clinical vocabulary for use in an electronic health record. It is the most comprehensive and precise clinical health terminology product in the world. SNOMED CT gives clinical IT systems a single shared language, which makes exchanging information between systems easier, safer and more accurate. It contains all the clinical terms needed, from procedures and symptoms through to clinical measurements, diagnoses and medications.

A secure processing environment (SPE) is a highly secure infrastructure and isolated environment. A SPE provides enhanced security compared to using a laptop when dealing with sensitive data. It prevents data from being transferred from its source to the data user. The data stays at its location where the research question is brought to the data in a secured environment and only the anonymous, aggregated results are transferred to the researcher.

Synthetic data is artificially generated information that mimics real-world data. It is created using algorithms, simulations, or models rather than being collected from actual real-world events or observations. Data is generated based on predefined rules or logic that reflects expected patterns. It avoids exposing sensitive or personally identifiable information since it isn't based on real people or situations.