Toomas Klementi

HTTK toob kokku juhtivad psüühika, keha, sotsiaalse konteksti ja ruumilise konteksti uurijad, et luua distsipliinide ülene arusaam komplekssüsteemidest, mis mõjutavad heaolu: elu kvaliteeti erinevates valdkondades objektiivses ja eriti subjektiivses mõttes. Me käsitleme 4 uurimisvaldkonda. 1) KORRELAADID: Millised bio-psühholoogilised ja sotsiaal-ruumilised omadused on seotud heaolu püsivamate komponentidega nagu eluga rahulolu? 2) MEHHANISMID: Kuidas rulluvad inimestes lahti heaolu dünaamilised komponendid, näiteks emotsioonid? 3) ENESEHOOL: Kuidas inimesed ise oma heaolu enesehoole ökosüsteemides mõistavad ja juhivad? 4) SEKKUMISED: Kuidas heaolu isikustatud ja kohandatud sekkumistega edendada? HTTK rahastab interdistsiplinaarseid ametikohti; registriandmetega lõimitud longituud-uuring; doktorikooli; tippsündmusi; ja rändluse ja koostöö toetusmeedet. HTTK tõstab osalevate rühmade, asutuste ja Eesti heaoluteaduste tulemuslikkust ja mõjukust.

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 aim of the Project “Development of universal data model and continuity of care processes based on international standards for new generation health information systems” is to find appropriate model for digital health care data that could be used for data collection and storage in new generation TIS with the feasibility to implement the same model in other large scale Electronic Health Records (EHR). This data model will be foundation for health care professionals to use digital decision support systems in context of Electronic Medical Record. The definition of data model would lead to the development of EHR processes where minimal set of health status summaries are defined for each specialty/health issue to make evidence-based decision possible. In turn, defined health status summaries are needed for development of continuity of care processes and training of artificial intelligence and development of intuitive Electronic Medical Records.