European health room space He has a significant promise to transform healthcare, research and innovation throughout Europe. The main EHDS targets that the European Commission launched in 2022 revolves around the improvement of healthcare, research, policy and strengthening of patient positions.
One of the key promises is the development of research and making decisions about public health by facilitating the creation of gigantic, high quality health data sets that are necessary to develop modern methods of treatment and precision medicine.
In the case of EHDS people, it enables digital access to their electronic medical records (EHR), prescriptions, medical images, laboratory results and dismissal reports throughout Europe.
Challenge related to the harmonization of data for trouble -free reuse
The European Commission has set an ambitious goal: by 2030, all citizens in Europe will have full possession of their data.
However, despite its potential, the current EHDS framework is two critical challenges:
- Although it is designed to bring the benefits of a wider population, it does not satisfy the needs and control of individual patients in relation to their own data.
- The process of generating secondary data sets remains elaborate and unskilled due to heterogeneity and lack of interoperability within the individual patient records.
To optimize the apply of secondary data, personal health data must first be selected and not identified in source format, and then selected for each case of apply. Currently, the process of treating and publishing data is done after extraction for secondary apply and is exorbitant, time -consuming and possible to manage only by experts. As a result, we do not apply gigantic amounts of data and there are narrow benefits for a patient who remains with heterogeneous data of non -optimal quality.
To solve these challenges, a consortium of 14 partners began AidavaProject financed by Europe from the horizon. Started in 2022, the project aims to solve management, integrated, integrated and apply of data on patient health by developing a virtual AI assistant. Thanks to Aidava, partners strive to provide patients with high quality personal medical documentation, offering personalized care, while facilitating trouble -free and high -quality secondary apply of data.
Access to all their personal health information is challenging for citizens and patients because it is dispersed from different systems. Even health care employees do not always have access to this data or do not archive them properly. In addition, health data is in heterogeneous format and are susceptible to errors (up to 10% of entries contain potentially life -threatening errors). Aidava is looking for virtual AI assistants who will facilitate facilitate the process of integration and quality improvement.
“How” for re -use of data
This four -year project has two main goals:
- Maximize automation in the treatment of personal health data to augment its reuse.
- Test the solution with three concrete activities:
- Establish a breast cancer register covering the entire EU, integrating data from three federed centers in different countries and languages.
- Calculate automatically an bright risk result to support subsequent cardiovascular patients with the latest history of myocardial infarction.
- Automatically generate a individual patient summary (IPS) in the format of European electronic electronic exchange of health documentation (EEHRXF), reducing the burden of data holders to generate these standards.
The consortium focuses its efforts on data treatment by integration of all data from many sources connected to each person, and then cleaning and homogenization. A virtual assistant supported by artificial intelligence will facilitate people in search of data and flag problems that require human intervention by the patient or their devoted curator.
“Most healthcare initiatives, including EHD, focus on the population data. This does not benefit every patient with patients’ provisions that remain heterogeneous and susceptible to errors; additionally repeated source data treatment for secondary use at the population level is not balanced,” says Isabelle de Zegrher, MD, MSC Aitava with 30+ years of experience in digital health.
“Aidava proposes to maximize the automation of the treatment of individual medical records and minimizing the need for human intervention using AI technology. The results of the first generation of the prototype-stone by patients in hospitals-promising and show that this may be the right direction of solving long-term problems of lack of health interoperability,” she adds.