Projects

This multidisciplinary study aims to decrease cardiovascular mortality in Estonia by increasing treatment adherence and empowering patients to create a supportive self-management environment for monitoring their health and actively participating in the treatment process. Analysing 1) the LDL-cholesterol values of North Estonia Medical Centre (NEMC) patients to find underdiagnosed and undertreated patients and 2) treatment adherence to lipid-lowering drugs (LLD). Identifying patient groups who need additional support. During the pilot project, a novel application will be developed, together with personal support, used to increase LLD adherence. The novelty of the tool – combining the data used in Estonia from the Nationwide Health Information System, ePrescription, and NEMC electronic medical record with the data collected by the patient and enabling two-way communication between the patient and medical staff. In the last stage of the study, an impact assessment of the tool is planned.

The present project aims to develop novel and enhance existing methods of explainable artificial intelligence for the analysis of human motor functions. Pilot studies have demonstrated promising results to support the diagnosis of neurodegenerative diseases. In addition, we plan to extend the area of application from medicine to cognitive development and cognitive fatigue analysis. The integration of the explainer component will provide medical professionals with the necessary transparency of the decisions made by AI. Application in the area of cognitive development to support the school education process. Cognitive fatigue is known to cause severe injuries and serious financial losses. In-depth understanding of this phenomenon and ability to recognise mental fatigue targets to make the work environment safer and reduce monetary and non-monetary losses in the process of work.

The overall goal of the project is to increase the number of healthy life years of the population. Currently, Estonia has recorded one of the lowest number of healthy life years at birth in the EU. To achieve this goal, three closely related areas of digital health are researched, developed and piloted. We use the standardized data exchange environment and digital data of the Estonian health information system (EHIS) to develop applications that increase the use of data collected by the person for health promotion, prevention and control of chronic conditions. Second, we focus on sensors and digital applications supported by artificial intelligence (AI) to allow a person to collect both biosignals and textual data in machine-readable form. With this, we speed up the detection of health risks and reduce the healthcare workload. Thirdly, we develop various AI methods by combining the data in EHIS and the Health Insurance Fund's database, as well as the data collected by the person.

The Xpanding Innovative Alliance (XiA) project is dedicated to advancing interoperability within the healthcare sector, particularly in anticipation of the European Health Data Space (EHDS) regulation. Through a comprehensive educational initiative, XiA aims to address the skills gap in advanced digital health interoperability standards among healthcare providers, digital health solution providers, and individuals. By developing high-quality educational materials and courses, XiA seeks to equip stakeholders with the necessary skills to embrace EHDS-related standards and foster a culture of interoperability.

A cloud-based digital health platform for private clinics in East Africa will be developed, focusing on optimizing workflows, monitoring chronic patients, and managing patient care. A distinctive feature of the platform is the combination of a mobile application and an SMS-based triage solution, allowing access for patients with limited digital capabilities. The product is being piloted in Kenya, where a shortage of doctors and a growing population create strong demand for efficient, labor-saving solutions. The solution is based on the logic of primary care digital models tested in Estonia, adapted to the local context.

"Background: Teledermoscopy has shown high diagnostic accuracy (sensitivity 90.48% and specificity 92.57%) for early detection of skin cancer in Estonia. However, not all its potential for early detection has been utilized, contributing to high melanoma mortality rates. Objective: This project aims to assess the impact of an integrated approach to patient pathways initiated by teledermoscopy on melanoma management effectiveness, focusing on faster diagnosis confirmation and treatment. Methodology: The study will evaluate the smoothness and effectiveness of the patient pathway initiated by teledermoscopy, integrating improvements based on existing requirements and study findings. The primary outcome measure will be the speed of histologically confirmed diagnosis and subsequent treatment. Result-Hypothesis: It's hypothesized that the integrated pathway will lead to better melanoma patient outcomes compared to previous studies, ensuring timely diagnosis confirmation and treatment."