Anonymous data: Data which cannot (without disproportionate effort) be traced to a specific person.
Big data: Datasets which have a size that is beyond the ability of typical database software tools to capture, store, manage, and analyse the amount of data.
Biobank: A structured collection of human biospecimen samples (tissue, blood, urine etc.) and information pertaining to the donors (demography, lifestyle, history of present illness, treatment, etc.), stored for the purposes of present and future research.
Clinical data management system: A clinical data repository which contains both patient structured and unstructured data.
'Driver' projects: SPHN projects that are based in a concrete research field (e.g. oncology/immunology) and will push the development of clinical data management systems in all University Hospitals by testing data interoperability & data sharing principles within the whole SPHN network.
Encoded/encrypted data: Data linked to a specific person via a code.
General consent: The one-time consent of a patient to the re-use of certain data and samples for future, still undefined research projects. The utilization of the data and samples occurs in compliance with legal requirements.
Infrastructure: Resources, personnel, and softwares that are necessary for the installation of the required network.
Infrastructure development projects: SPHN projects that thrive to develop and test new technologies, methods and infrastructures for personalized health related research in connection with infrastructure implementation.
Infrastructure implementation projects: SPHN projects that are devoted to build a progressive shareable data system enabling nationwide interoperability of molecular and clinical patient data.
Interoperability: In healthcare, interoperability is the ability of different health information technology systems and software applications to communicate, exchange data, and use the information that has been exchanged. Data exchange schema and standards should permit data to be shared within and across organizational and geographical boundaries (i.e. clinicians, lab, hospital, pharmacy, and patient) regardless of the application or application vendor.
-omics data: The entire data set of some kind , i.e. molecules, such as proteins, lipids, or metabolites, in a cell, organ, or organism. Genomics data i.e. refers to the entire set of genes within a cell/organ/organism.
Personalized medicine: The integration of different sets of data related to human health, e.g « -omics » data (genomics, transcriptomic, proteomic, metabolomics etc.), clinical data , data from biobanks, self-tracking data from individuals or environmental data, for the optimal medical care of each individual - starting with prevention of disease, to diagnostics and treatment until rehabilitation.
Personalized health: Concept that goes beyond the concept of personalized medicine: the findings from the various sets of health-related data will not only benefit the individual patient but also the population at large, as they will make it possible to recognise health risks at an early stage and develop appropriate health strategies.
The European Patients' Academy (EUPATI) has published a series of articles on personalised medicine to help patient understand this field.