Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Variety of Decision Support Systems and Their Implementation Timeline 1. Low-hanging Fruit 2. Improving Current System 3. Personalised Medicine Pilot 4. Implementing Personalised Medicine • Standardised process/interface for data input in clinical specialist interfaces enabling solid data analytics (usingICD-10, NCSP, SNOMED, …) • Improved data visualisation and health condition overview with highlights • Improved data aggregation across various EHR-s • Structured personal health declaration • Transformation from document based to event based data model • Integration of test-patients’ up to date phenotype data through questionnaires • Integration of test-patients’ family history data through questionnaires • Integration of test-patients’ gene data for genetic disease risk assessment • Interface for DSS rules management • Interface for assessing the validity/invalidity of DSS provided rule-based suggestions • Patient disease risk score calculation • Personalised lifestyle management guidelines • Integration of patient’s own fitness and quantified self data • Integration of patients gene data for genetic disease risk assessment • Possibility to share medical data with family members for genetic risk assessment • Possibility to share medical data with medical specialists for enhanced monitoring and risk notifications • Patient stratification for screening selection • Personalised long-term treatment schemes • Patient and medical specialist communication platform Perspective timeline from today to full implementation of Personalised Medicine in Estonia Clinical Decision Supports Scientific Gene Research Health Management Patient Monitoring Diagnosing and treatment suggestions based on genome data, patient life style, medical and family history data. Notifications for conflicting prescriptions. Checklists for medical procedures. Estonian Genome Center scientific research project. Personalised health management and disease prevention screening process based on genome data, life style data, medical history and family history. Chronic disease and post-clinical episode monitoring and management. Telemedicine solutions for chronic patient regular checkups. Patient diary enriched with life style data. Notifications for expiring prescriptions. Treatment adherence monitoring. Enablers: Implementation and management of digitised clinical scheme algorithms. Benefiting of genome data. Standardisation of data (ICD-10, NCSP, SNOMED, etc.) for implementing preexisting DDSS. Benefits: Higher average treatment quality. Saving time and improving certainty of clinical decisions. Services: • Notifications for conflicting prescriptions • Diagnosing and treatment scheme selection support • Medical procedure checklists Enablers: Sequencing existing tissue samples. Building applications and algorithms for scientific studies. Benefits: New scientific discoveries related to specifics of Estonian genome data. Services: • Estonian gene based gene risk model Enablers: New processes for GP-level screening, including genome data (moving healthcare from volume-based to value-based and preventive). Enablers: New processes (e.g. GP, family nurse monthly reviews). IT solutions for health and medical diaries, notifications). Benefits: Better quality from more efficient prevention. Cost effectiveness through more focused screening programs. Benefits: Better patient engagement. Resource savings from more efficient prevention and treatment. Time savings through more effective regular checkups. Services: • Patient disease risk score calculation • Screening and clinical visits prioritisation based on patient risk score • Personalised lifestyle management guidelines • Health diary enabling systematic collection of quantified self and fitness data Services: • Notification system for expiring prescriptions • Personalised long-term treatment schedules • Patient and medical specialist communication platform • Patient diary for collecting patient measurements and drug/treatment scheme adherence • Virtual medical appointment for chronic patients based on patient diary data Improved Data Usage and Visualisation Genome, health and medical data from various information systems aggregated and visualised in a usable medical doctor application. Enablers: Aggregating current data. Implementing better processes for data collection (standardised process for data input, patient QS + life style data, patient medical profile) Benefits: Saving GP, clinical specialist, work time during clinical visits. More accurate health overview for patient and clinician. Improved treatment quality. Notifications based on aggregated data. Services: • Standardised process for data input in clinical specialist interfaces enabling solid data analytics • Improved data aggregation across various EHR-s • Improved data visualisation and health condition overview with highlights • Inclusion of genome data Public Health Analysis Tools Better overview of general health trends, opportunities for prevention and resource allocation management. Enablers: Analysable aggregated patient data. Benefits: Measuring treatment quality. Better resource management. Assessing effects of prevention and treatment. Services: • Public health and disease trend analysis support