How to exchange and grant access to health data in a secure way. Approaches and recommendations
•
0 j'aime•128 vues
The health crisis due to COVID-19 is shaping a new reality in which the exchange and access to health data in a secure way will be more and more necessary. In this complex challenge converge both the respect for the individual rights as well as the interests of the patients and the need to promote the research in pursuit of the public interest. To face this challenge, we can find different approaches across Europe. In this webinar, we will present the experiences of three EU-funded projects (BigMedilytics, BodyPass, and DeepHealth), besides an overview of the legal framework and recommendations to enforce both national regulations and GDPR by an expert in data privacy and security
Recommandé
Recommandé
Contenu connexe
Plus de Big Data Value Association
Plus de Big Data Value Association (20)
Dernier
Dernier (20)
How to exchange and grant access to health data in a secure way. Approaches and recommendations
- 1. 001010010100101 1010010010001001001 0100101001 01000110 001011111100010 0000101010010010001001001 001001001000010001 01001000101001 01001 01001010010 01010010010100100100010101001 010100010100010 01010 10010010010001010 01010010010010010010010 0100100100010001001001001 0100101001010010 0101001001 How to exchange and grant access to health data in a secure way. Approaches and recommendations BigMedilytics Project Big Data for Medical Analytics. Comorbidities pilot 14th May 2020 Dr. Javier Gámez Payá Project manager
- 3. 10010100100001010101001001001010100101 01010010001001001010001001001 10100100100101100011100101011011001 1011001010010010000010101001010111001010010100101010 10010100100001010101001001001010100101 01010010001001001010001001001 1001010010010101001001001010100101 01010010001000010100010100101001001001010001001001 BigMedilytics (Big Data for Medical Analytics) . € 15 M Budget Funded under H2020-EU.2.1.1. 35 partners Healthcare providers Technology companies SMEs Pharma Insurers Research institutes Universities 12 countries 11 M patients’ health records
- 4. 10010100100001010101001001001010100101 01010010001001001010001001001 10100100100101100011100101011011001 1011001010010010000010101001010111001010010100101010 1001010010010101001001001010100101 01010010001000010100010100101001001001010001001001 Quality Cost Access BigMedilytics (Big Data for Medical Analytics) To transform healthcare in Europe by using state-of-the-art big data technologies to achieve breakthrough productivity by reducing cost, improving healthcare services quality and fostering its access.
- 5. 10010100100001010101001001001010100101 01010010001001001010001001001 10100100100101100011100101011011001 1011001010010010000010101001010111001010010100101010 10010100100001010101001001001010100101 01010010001001001010001001001 1001010010010101001001001010100101 01010010001000010100010100101001001001010001001001 How does BigMedilytics achieve its goal? 12 pilots that cover 3 themes with the greatest impact on the sector 78% of deaths within non-communicable diseases 33% of the expenditure in the sector
- 6. 10010100100001010101001001001010100101 01010010001001001010001001001 10100100100101100011100101011011001 1011001010010010000010101001010111001010010100101010 10010100100001010101001001001010100101 01010010001001001010001001001 1001010010010101001001001010100101 01010010001000010100010100101001001001010001001001 How does BigMedilytics achieve its goal? 12 pilots that cover 3 themes with the greatest impact on the sector 78% of deaths within non-communicable diseases 33% of the expenditure in the sector
- 7. 10010100100001010101001001001010100101 01010010001001001010001001001 10100100100101100011100101011011001 1011001010010010000010101001010111001010010100101010 10010100100001010101001001001010100101 01010010001001001010001001001 1001010010010101001001001010100101 01010010001000010100010100101001001001010001001001 How does BigMedilytics achieve its goal? 12 pilots that cover 3 themes with the greatest impact on the sector 78% of deaths within non-communicable diseases 33% of the expenditure in the sector
- 8. 10010100100001010101001001001010100101 01010010001001001010001001001 10100100100101100011100101011011001 1011001010010010000010101001010111001010010100101010 10010100100001010101001001001010100101 01010010001001001010001001001 1001010010010101001001001010100101 01010010001000010100010100101001001001010001001001 How does BigMedilytics achieve its goal? 12 pilots that cover 3 themes with the greatest impact on the sector 78% of deaths within non-communicable diseases 33% of the expenditure in the sector
- 9. 10010100100001010101001001001010100101 01010010001001001010001001001 10100100100101100011100101011011001 1011001010010010000010101001010111001010010100101010 10010100100001010101001001001010100101 01010010001001001010001001001 1001010010010101001001001010100101 01010010001000010100010100101001001001010001001001 How does BigMedilytics achieve its goal? 12 pilots that cover 3 themes with the greatest impact on the sector 78% of deaths within non-communicable diseases 33% of the expenditure in the sector
- 11. Population Health & Chronic Diseases 10010100100001010101001001001010100101 010100010010100010010010100100100101100011100 010110100101000010010101011001 000100100101000001010010001010100000100101 10010100100001010101001001001010100101 01010010001001001010001001001 1001010010010101001001001010100101 01010010001000010100010100101001001001010001001001 Critical patients WHO. World Report on Ageing and Health 2015 Multimorbidity- comorbidity is one of the main challenges in the healthcare sector. Its prevalence is increasing across Europe
- 12. Population Health & Chronic Disease 10010100100001010101001001001010100101 010100010010100010010010100100100101100011100 010110100101000010010101011001 000100100101000001010010001010100000100101 10010100100001010101001001001010100101 01010010001001001010001001001 1001010010010101001001001010100101 01010010001000010100010100101001001001010001001001 Big Data Analytics to apply the personalized best therapeutic strategy and reduce the burden on the healthcare system High-risk Primary care Secondary care Low-moderate risk 1. Retrospective analysis 2. Technological development (ML) 3. Prospective analysis to validate the tool 4 M EHR Valencian Community Objective: to develop a decision support system for GP based on the stratification and clustering of the population. In order to assess the hospitalization risk and mortality.
- 13. Population Health & Chronic Disease Management Comorbidities 10010100100001010101001001001010100101 01010010001001001010001001001 1001010010010101001001001010100101 01010010001000010100010100101001001001010001001001 Our approach. 3 pillars Technology Computational cluster + secure channel Legal Bilateral agreement between partners Data anonymization Anonymization + re-identification risk assessment
- 14. Population Health & Chronic Disease Management Comorbidities 10010100100001010101001001001010100101 01010010001001001010001001001 1001010010010101001001001010100101 01010010001000010100010100101001001001010001001001 Our approach. Anonymization
- 15. Population Health & Chronic Disease Management Comorbidities 10010100100001010101001001001010100101 01010010001001001010001001001 1001010010010101001001001010100101 01010010001000010100010100101001001001010001001001 Our approach. Technology, visiting concept
- 16. Population Health & Chronic Disease Management Comorbidities 10010100100001010101001001001010100101 01010010001001001010001001001 1001010010010101001001001010100101 01010010001000010100010100101001001001010001001001 Our approach. Technology. Cluster 4 3 2 8 9 1 56 7
- 17. Population Health & Chronic Disease Management Comorbidities 10010100100001010101001001001010100101 01010010001001001010001001001 Recommendations Technology Computational cluster + secure channel • Data should be in a secure server in-house. • VPN. 2 steps authentication • Traceability. One login per person. Important to track all access. • Virtualized environment implemented in Redundant high performance servers (at least 2) • Minimum requirements: • SSD disk (fast access) + conventional disk (slow access) • 1TB RAM • 10GB ethernet, interconnection between servers • 24 cores
- 18. Population Health & Chronic Disease Management Comorbidities 10010100100001010101001001001010100101 01010010001001001010001001001 1001010010010101001001001010100101 01010010001000010100010100101001001001010001001001 Recommendations Legal Bilateral agreement between partners Anonymization Anonymization + re-identification risk assessment • A bilateral agreement among partners that are going to have access to data is highly recommended. • Accountability principle. Be able to document everything and show that you comply with all regulations • Double-anonymization process • Conduct a re-identification risk assessment • Check the recommendation of your national authority
- 19. Population Health & Chronic Disease Management Comorbidities 10010100100001010101001001001010100101 01010010001001001010001001001 1001010010010101001001001010100101 01010010001000010100010100101001001001010001001001 Recommendations Act as if fully anonymized data don’t exist Reach the highest levels of security as possible Prove that you apply all possible measures
- 20. 10010100100001010101001001001010100101 01010010001001001010001001001 10100100100101100011100101011011001 1011001010010010000010101001010111001010010100101010 10010100100001010101001001001010100101 01010010001001001010001001001 1001010010010101001001001010100101 01010010001000010100010100101001001001010001001001 Thank you for your attention! jgamez@incliva.es