Global Forum
Speakers
Day 1
Digital Technology and AI to Strengthen Health Systems: Emerging Practices and Remaining Challenges
Marelize Gorgens
Lead: Digital and AI Solutions for People, World Bank
Lead: Digital and AI Solutions for People, World Bank
Biography
Marelize Gorgens Prestidge, B.Eng PMP MSc MA. With an academic background in engineering, mathematical modelling, public health, data science and integrative (functional) medicine, her career path started in the private sector as a director at a management consulting firm before changing gears; she worked at a Ministry of Education in a low-income country, ran a start-up company in the health analytics space where she worked with several non-governmental organizations and in academia.
In 2006, she joined the World Bank, where she is the lead of the World Bank’s program on Digital and AI for People.
She has an extensive academic and non-fiction publication record and is on the editorial board of two journals (Global Health Science and Practice, and Oxford Digital Health).
In 2006, she joined the World Bank, where she is the lead of the World Bank’s program on Digital and AI for People.
She has an extensive academic and non-fiction publication record and is on the editorial board of two journals (Global Health Science and Practice, and Oxford Digital Health).
Abstract
This keynote address explores how digital technologies and artificial intelligence (AI) are reshaping health systems in countries around the world.
As governments seek to deliver more equitable, efficient, and resilient health services, digitally-enabled solutions—ranging from interoperable data platforms to AI-powered clinical decision support—are playing an increasingly central role.
Drawing from emerging practices across diverse country contexts, the talk will highlight successful use cases that demonstrate real-time benefits in service delivery, supply chain optimization, and disease surveillance.
For instance, AI tools are helping predict disease outbreaks, digital registries are improving maternal health tracking, and mobile platforms are expanding access to health information in underserved regions.
However, these innovations face persistent barriers. Many systems remain fragmented, donor-driven pilots fail to scale, and governance frameworks lag behind rapid technological change.
Data privacy concerns, digital literacy gaps, and insufficient public sector capacity compound these challenges.
The presentation will offer a critical overview of what’s working and why—while also unpacking the conditions under which digital health solutions can meaningfully contribute to universal health coverage (UHC).
It will also address the role of digital public infrastructure, the importance of inclusive design, and the risks of amplifying inequities.
The session concludes with policy recommendations for governments and development partners, including the need for long-term investment in evidence, governance, financing, and workforce capacity to enable digital and AI tools to support integrated, people-centered health systems.
The findings aim to inform decision-makers navigating the digital transformation of health in a complex and evolving landscape.
As governments seek to deliver more equitable, efficient, and resilient health services, digitally-enabled solutions—ranging from interoperable data platforms to AI-powered clinical decision support—are playing an increasingly central role.
Drawing from emerging practices across diverse country contexts, the talk will highlight successful use cases that demonstrate real-time benefits in service delivery, supply chain optimization, and disease surveillance.
For instance, AI tools are helping predict disease outbreaks, digital registries are improving maternal health tracking, and mobile platforms are expanding access to health information in underserved regions.
However, these innovations face persistent barriers. Many systems remain fragmented, donor-driven pilots fail to scale, and governance frameworks lag behind rapid technological change.
Data privacy concerns, digital literacy gaps, and insufficient public sector capacity compound these challenges.
The presentation will offer a critical overview of what’s working and why—while also unpacking the conditions under which digital health solutions can meaningfully contribute to universal health coverage (UHC).
It will also address the role of digital public infrastructure, the importance of inclusive design, and the risks of amplifying inequities.
The session concludes with policy recommendations for governments and development partners, including the need for long-term investment in evidence, governance, financing, and workforce capacity to enable digital and AI tools to support integrated, people-centered health systems.
The findings aim to inform decision-makers navigating the digital transformation of health in a complex and evolving landscape.
Bridging Innovation and Policy: Leveraging Emerging Data for Healthcare Decisions
Hyun-Young, Park
Director General, National Institute of Health
Director General, National Institute of Health
Biography
2023.07 – Present : Director General, Korea National Institute of Health (KNIH)
2020.09 – 2023.07 : Director general, Department of Precision Medicine, Korea National Institute of Health
2018.02 – 2020.09 : Director, Center for Genome Science, Korea National Institute of Health
2017.05 – 2018.02 : Director, Division of Cardiovascular Diseases, Center for Biomedical Sciences, Korea National Institute of Health
2005.02 – 2017.05 : Director, Division of Cardiovascular and Rare Diseases, Center for Biomedical Sciences, Korea National Institute of Health
2000 – 2005.02 : Assistant Professor, Cardiovascular Research Institute, Yonsei University College of Medicine
1998 – 1999 : Research Assistant Professor, Cardiovascular Research Institute, Yonsei University College of Medicine
1995 – 1996 : Clinical Fellow (Instructor), Department of Cardiology, Severance Cardiovascular Hospital, Yonsei University College of Medicine
2020.09 – 2023.07 : Director general, Department of Precision Medicine, Korea National Institute of Health
2018.02 – 2020.09 : Director, Center for Genome Science, Korea National Institute of Health
2017.05 – 2018.02 : Director, Division of Cardiovascular Diseases, Center for Biomedical Sciences, Korea National Institute of Health
2005.02 – 2017.05 : Director, Division of Cardiovascular and Rare Diseases, Center for Biomedical Sciences, Korea National Institute of Health
2000 – 2005.02 : Assistant Professor, Cardiovascular Research Institute, Yonsei University College of Medicine
1998 – 1999 : Research Assistant Professor, Cardiovascular Research Institute, Yonsei University College of Medicine
1995 – 1996 : Clinical Fellow (Instructor), Department of Cardiology, Severance Cardiovascular Hospital, Yonsei University College of Medicine
Abstract
In the era of rapid medical technology innovation, the integration of digital health solutions and genomic information is accelerating the development of precision medicine.
These advancements are generating vast volumes of new data—such as real-world data and bio big data—that hold immense potential for transforming evidence-based health policy.
This keynote will explore how emerging data can be strategically leveraged to enhance healthcare policy decision-making, supporting more personalized, predictive, and preventive healthcare systems.
By connecting technological innovation with policy frameworks, we can ensure that the benefits of precision medicine and digital health are equitably and efficiently realized across populations.
These advancements are generating vast volumes of new data—such as real-world data and bio big data—that hold immense potential for transforming evidence-based health policy.
This keynote will explore how emerging data can be strategically leveraged to enhance healthcare policy decision-making, supporting more personalized, predictive, and preventive healthcare systems.
By connecting technological innovation with policy frameworks, we can ensure that the benefits of precision medicine and digital health are equitably and efficiently realized across populations.
Big Data-Driven Evidence-Based Policymaking in the Korean Context : Characteristics and Cases
Jai-Yong, Kim
Director-General of Department of Big Data Research and Development, National Health Insurance Service
Director-General of Department of Big Data Research and Development, National Health Insurance Service
Biography
2024 - Present : Director-General, Big Data Research and Development, National Health Insurance Service (NHIS), Republic of Korea
2021 - 2024 : Head of Big Data Research Department, Big Data Operations Division, NHIS, Republic of Korea
2019 - 2021 : Research Professor, Yonsei University Wonju College of Medicine
2017 - 2019 : Research Professor, Institute for Health and Society, Hanyang University
2008 - 2012 : Associate Professor, College of Medicine, Hallym University
2021 - 2024 : Head of Big Data Research Department, Big Data Operations Division, NHIS, Republic of Korea
2019 - 2021 : Research Professor, Yonsei University Wonju College of Medicine
2017 - 2019 : Research Professor, Institute for Health and Society, Hanyang University
2008 - 2012 : Associate Professor, College of Medicine, Hallym University
Abstract
The Korean National Health Insurance Service (NHIS) has developed a comprehensive evidence-based policymaking (EBPM) model utilizing its vast national health data infrastructure.
Covering nearly the entire population, the NHIS database includes detailed medical, demographic, socioeconomic, and behavioral data. This system supports real-time policy feedback, predictive analytics, and cross-agency collaboration.
Key case studies include:
COVID-19 Response – Integration with the Korea Disease Control and Prevention Agency (KDCA) enabled real-time risk scoring, vaccine effectiveness monitoring, and data-driven quarantine policies.
Private Insurance Overuse – Analysis revealed significant overuse and financial strain on public insurance due to private supplemental insurance. Estimated excess public costs ranged from $2.78 to $7.91 billion annually.
Regional Medical Map – Geographic accessibility and service sufficiency were visualized to support equitable healthcare distribution and local policy planning.
Korea's EBPM model demonstrates high timeliness, transparency, and efficiency. It has strong potential for global application in pandemic response, aging population management, and health system design. Data, when ethically governed and strategically utilized, becomes infrastructure for trust and resilient governance.
Covering nearly the entire population, the NHIS database includes detailed medical, demographic, socioeconomic, and behavioral data. This system supports real-time policy feedback, predictive analytics, and cross-agency collaboration.
Key case studies include:
COVID-19 Response – Integration with the Korea Disease Control and Prevention Agency (KDCA) enabled real-time risk scoring, vaccine effectiveness monitoring, and data-driven quarantine policies.
Private Insurance Overuse – Analysis revealed significant overuse and financial strain on public insurance due to private supplemental insurance. Estimated excess public costs ranged from $2.78 to $7.91 billion annually.
Regional Medical Map – Geographic accessibility and service sufficiency were visualized to support equitable healthcare distribution and local policy planning.
Korea's EBPM model demonstrates high timeliness, transparency, and efficiency. It has strong potential for global application in pandemic response, aging population management, and health system design. Data, when ethically governed and strategically utilized, becomes infrastructure for trust and resilient governance.
The French Health Data Hub: towards data-driven healthcare
Salam ABBARA
Post-doctorate researcher, Research Institute of Bacterial Resistance, Department of Laboratory Medicine, Gangnam Severance Hospital, Yonsei University
Post-doctorate researcher, Research Institute of Bacterial Resistance, Department of Laboratory Medicine, Gangnam Severance Hospital, Yonsei University
Biography
Infectious diseases clinician, epidemiologist
2023 - 2025 : Infectious diseases clinician (AP-HP Paris hospitals), researcher (Pasteur Institute / INSERM), and university lecturer (Versailles Saint-Quentin-en-Yvelines University)
2022 - 2023 : Medical expert at the Scientific Division, French Health Data Hub
2019 - 2022 : PhD in Epidemiology
- Thesis: “Antimicrobial Resistant Infections: Contribution of the AP-HP Hospitals Clinical Data Warehouse”
2013 - 2019 : Medical doctor specializing in internal medicine and infectious diseases, Sorbonne University and Greater Paris hospitals
2016 - 2017 : Master’s degree in Interdisciplinary Approaches in Life Sciences, Paris Descartes University
2023 - 2025 : Infectious diseases clinician (AP-HP Paris hospitals), researcher (Pasteur Institute / INSERM), and university lecturer (Versailles Saint-Quentin-en-Yvelines University)
2022 - 2023 : Medical expert at the Scientific Division, French Health Data Hub
2019 - 2022 : PhD in Epidemiology
- Thesis: “Antimicrobial Resistant Infections: Contribution of the AP-HP Hospitals Clinical Data Warehouse”
2013 - 2019 : Medical doctor specializing in internal medicine and infectious diseases, Sorbonne University and Greater Paris hospitals
2016 - 2017 : Master’s degree in Interdisciplinary Approaches in Life Sciences, Paris Descartes University
Abstract
The uses of health data are increasing and it has become essential to ensure access to data sources as quickly as possible. Indeed, disparities and complexities in governance models mean that the potential to reuse health data is still underexplored.
Created at the end of 2019, the French Health Data Hub (HDH) is a public body tasked with facilitating access to health data for projects in the public interest and addressing the challenges of health data access in France, through three main pillars: 1) establishing a single gateway for health data in France; 2) setting-up a secure state-of-the-art platform with various tools including AI; 3) developing a data catalogue including one of the world’s largest healthcare claims database.
As of today, more than 170 projects are supported by the HDH, of which +120 use the HDH’s technological state-of-the art platform, and a third of them use artificial intelligence tools.
Among the data catalogue administered by the HDH is the main database of the French National Health Data System, which contains individual sociodemographic and medical characteristics data for all health insurance beneficiaries in France, all hospital care and office medicine reimbursements, and medical causes of death.
It provides a comprehensive view of the healthcare journey for the entire French population (>67 million people) in a pseudonymized way, over a maximum historical depth of 20 years. More than 400 publications have been based on this database since its creation.
The HDH also works with the French government to prepare a national doctrine for hospital data warehouses, in order to standardize practices and tools at the national level, promote data sharing, and build a sustainable financial model. The HDH also supports public interest artificial intelligence through its platform, and is the leader of a consortium to develop an open source medical LLM in French, with use cases across hospitals.
The HDH is actively involved in shaping the landscape of secondary reuse of health data in Europe by leading and participating in various EU projects, paving the way towards a European Health Data Space.
Created at the end of 2019, the French Health Data Hub (HDH) is a public body tasked with facilitating access to health data for projects in the public interest and addressing the challenges of health data access in France, through three main pillars: 1) establishing a single gateway for health data in France; 2) setting-up a secure state-of-the-art platform with various tools including AI; 3) developing a data catalogue including one of the world’s largest healthcare claims database.
As of today, more than 170 projects are supported by the HDH, of which +120 use the HDH’s technological state-of-the art platform, and a third of them use artificial intelligence tools.
Among the data catalogue administered by the HDH is the main database of the French National Health Data System, which contains individual sociodemographic and medical characteristics data for all health insurance beneficiaries in France, all hospital care and office medicine reimbursements, and medical causes of death.
It provides a comprehensive view of the healthcare journey for the entire French population (>67 million people) in a pseudonymized way, over a maximum historical depth of 20 years. More than 400 publications have been based on this database since its creation.
The HDH also works with the French government to prepare a national doctrine for hospital data warehouses, in order to standardize practices and tools at the national level, promote data sharing, and build a sustainable financial model. The HDH also supports public interest artificial intelligence through its platform, and is the leader of a consortium to develop an open source medical LLM in French, with use cases across hospitals.
The HDH is actively involved in shaping the landscape of secondary reuse of health data in Europe by leading and participating in various EU projects, paving the way towards a European Health Data Space.
Big Data-Driven Policies: Taiwan’s Experience
Hsueh-Fen Chen
Associate Professor, Kaohsiung Medical University
Associate Professor, Kaohsiung Medical University
Biography
2023.06 – Present : Associate Researcher, Department of Medical Research, Kaohsiung Medical University Hospital
2021.02 – Present : Associate Professor, Department of Health Administration and Medical Informatics, College of Health Sciences, Kaohsiung Medical University
2016.07 – 2020.06 : Associate Professor, Department of Health Management and Policy, College of Public Health, University of Arkansas for Medical Sciences
2015.09 – 2016.07 : Associate Professor, Department of Health Management and Policy, School of Public Health, University of North Texas Health Science Center
2008.07 – 2015.08 : Assistant Professor, Department of Health Management and Policy, School of Public Health, University of North Texas Health Science Center
1995.08 – 2005.08 : Lecturer, Department of Health Care Management, National Taipei College of Nursing
1994.08 – 1995.08 : Teaching Assistant, Department of Health Care Management, National Taipei College of Nursing
1990.06 – 1994.07 : Administrator, Division of Healthcare Utilization Review and Payment, Department of Government Employees Insurance
2021.02 – Present : Associate Professor, Department of Health Administration and Medical Informatics, College of Health Sciences, Kaohsiung Medical University
2016.07 – 2020.06 : Associate Professor, Department of Health Management and Policy, College of Public Health, University of Arkansas for Medical Sciences
2015.09 – 2016.07 : Associate Professor, Department of Health Management and Policy, School of Public Health, University of North Texas Health Science Center
2008.07 – 2015.08 : Assistant Professor, Department of Health Management and Policy, School of Public Health, University of North Texas Health Science Center
1995.08 – 2005.08 : Lecturer, Department of Health Care Management, National Taipei College of Nursing
1994.08 – 1995.08 : Teaching Assistant, Department of Health Care Management, National Taipei College of Nursing
1990.06 – 1994.07 : Administrator, Division of Healthcare Utilization Review and Payment, Department of Government Employees Insurance
Abstract
The lecture aims to help audiences understand how Taiwan's National Health Insurance Administration (NHIA) implements the big data-driven polices to reach its mission: Health for All and Financial Sustainability. The lecture covers three sections: 1) the background of Taiwan and its NHI, 2) data-driven policies by using the two examples, Pharmcloud/Medicloud and Diabetes Pay-for-Performance, to demonstrate how these policies were implemented and their cost-effectiveness, and 3) the ongoing challenges and efforts.
Taiwan has a population of 23 million. In 1995, Taiwan implemented the national health insurance (NHI) program, with a single payer system and universal coverage, including outpatient/ inpatient care, dental services, drugs, traditional Chinese medicine, day-care for mental illness, and home-based medical care, which makes healthcare affordable and accessible. More than 99% of the population in Taiwan is enrolled in NHI. Overall, people in Taiwan are satisfied with NHI, with the satisfaction rate remaining at least 80% for a decade and reaching 91% since 2020.
NHIA marks its 30th anniversary this year. Since its inauguration, NHIA, as a single payer, has made significant efforts to form today’s population-based big data system, including, but not limited to, an electronic claims submission system and NHI smart card (IC card). The population-based big data system allows NHIA to aggregate healthcare utilizations at the patient, provider/ institution, region, and national level to identify critical and meaningful issues (e.g., high-risk, high-cost, and high-volume) for policy interventions to reach its missions. As Taiwan faces a rising aging population and chronic diseases, as well as deadly cancer and costly rare diseases, NHIA strives to address challenges through data-driven policy interventions to carry on its mission.
Taiwan has a population of 23 million. In 1995, Taiwan implemented the national health insurance (NHI) program, with a single payer system and universal coverage, including outpatient/ inpatient care, dental services, drugs, traditional Chinese medicine, day-care for mental illness, and home-based medical care, which makes healthcare affordable and accessible. More than 99% of the population in Taiwan is enrolled in NHI. Overall, people in Taiwan are satisfied with NHI, with the satisfaction rate remaining at least 80% for a decade and reaching 91% since 2020.
NHIA marks its 30th anniversary this year. Since its inauguration, NHIA, as a single payer, has made significant efforts to form today’s population-based big data system, including, but not limited to, an electronic claims submission system and NHI smart card (IC card). The population-based big data system allows NHIA to aggregate healthcare utilizations at the patient, provider/ institution, region, and national level to identify critical and meaningful issues (e.g., high-risk, high-cost, and high-volume) for policy interventions to reach its missions. As Taiwan faces a rising aging population and chronic diseases, as well as deadly cancer and costly rare diseases, NHIA strives to address challenges through data-driven policy interventions to carry on its mission.
Healthcare Big Data and AI: Barriers, Breakthroughs, and Roles of Medical Institutions
Hyeon-Chang, Kim
Professor, Yonsei University College of Medicine
Professor, Yonsei University College of Medicine
Biography
2004 – Present : Professor, Department of Preventive Medicine, Yonsei University College of Medicine
2014 – 2016 : Associate Dean for Research, Yonsei University College of Medicine
2017 – Present : Special Advisor for Big Data Utilization, National Health Insurance Service (NHIS), Korea
2018 – 2022 : Chair Professor, Department of Preventive Medicine, Yonsei University College of Medicine
2020 – 2022 : Director, Big Data Office, Yonsei Medical Center
2021 – Present : Editor-in-Chief, Epidemiology and Health
2022 – Present : CIO and Director, Digital Health Centor of Yonsei University Health System
2022 – Present : Director, Institute for Innovation in Digital Healthcare, Yonsei University
2024 – Present : Member and Chair of Expert Committee on Digital Healthcare, Health and Medical Technology Policy Advisory Committee
2014 – 2016 : Associate Dean for Research, Yonsei University College of Medicine
2017 – Present : Special Advisor for Big Data Utilization, National Health Insurance Service (NHIS), Korea
2018 – 2022 : Chair Professor, Department of Preventive Medicine, Yonsei University College of Medicine
2020 – 2022 : Director, Big Data Office, Yonsei Medical Center
2021 – Present : Editor-in-Chief, Epidemiology and Health
2022 – Present : CIO and Director, Digital Health Centor of Yonsei University Health System
2022 – Present : Director, Institute for Innovation in Digital Healthcare, Yonsei University
2024 – Present : Member and Chair of Expert Committee on Digital Healthcare, Health and Medical Technology Policy Advisory Committee
Abstract
The integration of healthcare big data—or real-world data—with artificial intelligence (AI) has the potential to transform medical research, clinical care, and related industries.
However, the sensitive nature of health data poses significant challenges.
A key concern is the ethical and legal use of patient data without explicit consent. While pseudonymization frameworks have improved data safety, using such data—especially for AI models operating on external servers—remains difficult due to privacy and re-identification risks.
This presentation emphasizes the essential role of healthcare institutions as more than data providers.
They must ensure ethical, secure, and equitable data use while fostering interdisciplinary collaboration.
To do so, institutions need appropriate infrastructure, expertise, and sustained financial support.
Public funding alone is insufficient.
A sustainable model should ensure that data users share financial responsibility, enabling reinvestment into institutional data infrastructure.
Balancing utility and privacy is critical to unlocking the full potential of healthcare big data and AI.
However, the sensitive nature of health data poses significant challenges.
A key concern is the ethical and legal use of patient data without explicit consent. While pseudonymization frameworks have improved data safety, using such data—especially for AI models operating on external servers—remains difficult due to privacy and re-identification risks.
This presentation emphasizes the essential role of healthcare institutions as more than data providers.
They must ensure ethical, secure, and equitable data use while fostering interdisciplinary collaboration.
To do so, institutions need appropriate infrastructure, expertise, and sustained financial support.
Public funding alone is insufficient.
A sustainable model should ensure that data users share financial responsibility, enabling reinvestment into institutional data infrastructure.
Balancing utility and privacy is critical to unlocking the full potential of healthcare big data and AI.
When Hippocrates met AI: Moving fast AND doing NO harm
Eric Sutherland
Senior Health Economist, OECD
Senior Health Economist, OECD
Biography
[Professional Experience]
2022 – Present : Senior Health Economist, Organisation for Economic Cooperation and Development (OECD)
2020 – 2022 : Executive Director, Public Health Agency of Canada
2018 – 2020 : Executive Director, Canadian Institute for Health Information (CIHI)
2017 – 2018 : Director, Ministry of Health and Long-Term Care
2015 – 2016 : Vice President, TD Bank Financial Group
2013 – 2015 : Associate Vice President, TD Bank Financial Group
[Education]
2021 : Data Stewards Academy, Gov Lab
2019 : CDO Summer School, Jackson + Carruthers / Collibra
2017 : Post-Graduate Certificate in Public Administration, University of Liverpool
2016 : Machine Learning, Coursera / Stanford University
2016 : Data Capability Assessment Model, Enterprise Data Management Council
2007 : Six Sigma Canada Green Belt
1995 : Master of Mathematics, University of Waterloo
1994 : Bachelor of Mathematics, University of Waterloo
2022 – Present : Senior Health Economist, Organisation for Economic Cooperation and Development (OECD)
2020 – 2022 : Executive Director, Public Health Agency of Canada
2018 – 2020 : Executive Director, Canadian Institute for Health Information (CIHI)
2017 – 2018 : Director, Ministry of Health and Long-Term Care
2015 – 2016 : Vice President, TD Bank Financial Group
2013 – 2015 : Associate Vice President, TD Bank Financial Group
[Education]
2021 : Data Stewards Academy, Gov Lab
2019 : CDO Summer School, Jackson + Carruthers / Collibra
2017 : Post-Graduate Certificate in Public Administration, University of Liverpool
2016 : Machine Learning, Coursera / Stanford University
2016 : Data Capability Assessment Model, Enterprise Data Management Council
2007 : Six Sigma Canada Green Belt
1995 : Master of Mathematics, University of Waterloo
1994 : Bachelor of Mathematics, University of Waterloo
Abstract
Artificial intelligence is transforming health systems by improving diagnostics, accelerating drug discovery, and streamlining administration.
However, the introduction of AI into health systems is meeting resistance from lack of capacity, trust, or infrastructure.
This presentation will discuss the importance of navigating the meeting of two cultures – where we must ‘move fast and do no harm’.
It will describe the importance of addressing cultural resistance while not succumbing to hype to evolve policies, infrastructure, and trust to enable the responsible adoption of AI solutions that can effectively scale.
However, the introduction of AI into health systems is meeting resistance from lack of capacity, trust, or infrastructure.
This presentation will discuss the importance of navigating the meeting of two cultures – where we must ‘move fast and do no harm’.
It will describe the importance of addressing cultural resistance while not succumbing to hype to evolve policies, infrastructure, and trust to enable the responsible adoption of AI solutions that can effectively scale.
(Moderator) Hyobum Jang
Medical Officer, World Health Organization(WHO)
Medical Officer, World Health Organization(WHO)
Biography
2009 - Present : Medical Officer/Technical Officer, WHO HQ
2015 - 2019 : Fellow/Consultant, WHO Samoa/South Pacific
2012 - 2013 : Master of Public Health, Harvard University
2003 - 2009 : Doctor of Medicine, Seoul National University
2015 - 2019 : Fellow/Consultant, WHO Samoa/South Pacific
2012 - 2013 : Master of Public Health, Harvard University
2003 - 2009 : Doctor of Medicine, Seoul National University
Jip-Min, Jung
General Manager, Korea Health Information Service(KHIS)
General Manager, Korea Health Information Service(KHIS)
Biography
[Career]
2023 – Present: Director, Data Driben Project Department,, Korea Health Information Service (KHIS)
2021 – 2022: Head, Healthcare Information Standarization Project Department, Korea Health Information Service (KHIS)
2020 – 2022: Director, Center for Data and AI Utilization, Korea Health Information Service (KHIS)
2015 – 2020: Section chief, Cancer Big Data Center, National Cancer Center (NCC)
2007 – 2015: Planning and Coordination Office, National Cancer Center (NCC)
[Education]
2015 – 2020: Ph.D. Program in Digital Health, Sungkyunkwan University
2005 – 2007: M.S. in Biomedical Engineering, Yonsei University
1999 – 2005: B.S. in Biomedical Engineering, Yonsei University
2023 – Present: Director, Data Driben Project Department,, Korea Health Information Service (KHIS)
2021 – 2022: Head, Healthcare Information Standarization Project Department, Korea Health Information Service (KHIS)
2020 – 2022: Director, Center for Data and AI Utilization, Korea Health Information Service (KHIS)
2015 – 2020: Section chief, Cancer Big Data Center, National Cancer Center (NCC)
2007 – 2015: Planning and Coordination Office, National Cancer Center (NCC)
[Education]
2015 – 2020: Ph.D. Program in Digital Health, Sungkyunkwan University
2005 – 2007: M.S. in Biomedical Engineering, Yonsei University
1999 – 2005: B.S. in Biomedical Engineering, Yonsei University
Chae-Min, Shin
Senior Research Fellow/Executive Director, National Evidence-based Healthcare Collaborating Agency(NECA)
Senior Research Fellow/Executive Director, National Evidence-based Healthcare Collaborating Agency(NECA)
Biography
2023.11. - Present : Senior Research Fellow/Executive Director, Division of Healthcare Research, National Evidence-based Healthcare Collaborating Agency (NECA)
2018.1. - 2023.11. : Director General, Division of New Health Technology Assessment, National Evidence-based Healthcare Collaborating Agency (NECA)
2016.6. - 2018.2. : Executive Director, Center for Future Healthcare Policy Research, National Evidence-based Healthcare Collaborating Agency (NECA)
2014.1. - 2016.1. : Head, Emerging Medical Technology Exploration Team, National Evidence-based Healthcare Collaborating Agency (NECA)
2018.1. - 2023.11. : Director General, Division of New Health Technology Assessment, National Evidence-based Healthcare Collaborating Agency (NECA)
2016.6. - 2018.2. : Executive Director, Center for Future Healthcare Policy Research, National Evidence-based Healthcare Collaborating Agency (NECA)
2014.1. - 2016.1. : Head, Emerging Medical Technology Exploration Team, National Evidence-based Healthcare Collaborating Agency (NECA)
Jong-Youl, Jeong
Vice President(Department of Public AI & Data), National Information Society Agency(NIA)
Vice President(Department of Public AI & Data), National Information Society Agency(NIA)
Biography
2023 – Present : Director General, Department of Public AI & Data(Open Data Center)
2021 – 2022 : Director, Open Government Data Dispute Mediation Committee
2017 – 2020 : Director, Public AI & Data Release Team of Department of Public AI & Data(Open Data Center)
2011 – 2016 : Director, Network Division / Director, Technical Support Division / ICT Convergence Project Planning Lead
1995 – 2010 : National Information Super-Highway/ Research & Testbed/Broadband Convergence Network (BcN)/ National Informatization Support Projects
2021 – 2022 : Director, Open Government Data Dispute Mediation Committee
2017 – 2020 : Director, Public AI & Data Release Team of Department of Public AI & Data(Open Data Center)
2011 – 2016 : Director, Network Division / Director, Technical Support Division / ICT Convergence Project Planning Lead
1995 – 2010 : National Information Super-Highway/ Research & Testbed/Broadband Convergence Network (BcN)/ National Informatization Support Projects
Tomonoshin Aoki
Deputy Director, Ministry of Health, Labour and Welfare, Health Policy Bureau, Office of Counsellor for Medical Information Management
Deputy Director, Ministry of Health, Labour and Welfare, Health Policy Bureau, Office of Counsellor for Medical Information Management
Biography
2023 - 2024 : Master of Science in Engineering & Management, Massachusetts Institute of Technology
2022 - 2023 : Master of Public Health in Health Policy, Harvard T.H. Chan School of Public Health
2020 - 2022 : Chief, Division of Health Economics, MHLW
2012 - 2017 : Doctor of Medicine, Hirosaki University
2022 - 2023 : Master of Public Health in Health Policy, Harvard T.H. Chan School of Public Health
2020 - 2022 : Chief, Division of Health Economics, MHLW
2012 - 2017 : Doctor of Medicine, Hirosaki University
Muzna AlToubi
Statistics and Studies Specialist, Social Protection Fund(Oman)
Statistics and Studies Specialist, Social Protection Fund(Oman)
Biography
2024 - Present : Statistics and Studies Specialist in Social Protection Fund
2020 - 2023 : Studies Researcher in Authority for Social Insurance
2020 - 2023 : Studies Researcher in Authority for Social Insurance
Emmanuel Bacry
Scientific Director, Health Data Hub(France)
Scientific Director, Health Data Hub(France)
Biography
2019 - Present : Chief Scientific Officer, French Health Data Hub, Paris
2019 - Present : Fellow, Paris AI Research Institute (PR[AI]RIE, 3IA Institute)
2019 - 2020 : Head of Data and Health Projects, École Polytechnique, France
2017 - Present : Senior Researcher, CNRS (CEREMADE), Université Paris-Dauphine – PSL
2019 - Present : Fellow, Paris AI Research Institute (PR[AI]RIE, 3IA Institute)
2019 - 2020 : Head of Data and Health Projects, École Polytechnique, France
2017 - Present : Senior Researcher, CNRS (CEREMADE), Université Paris-Dauphine – PSL
Husni Zaeem Abd Hadi
Senior Principal Assistant Director, Health Transformation Office/Ministry of Health, Malaysia
Senior Principal Assistant Director, Health Transformation Office/Ministry of Health, Malaysia
Biography
[Education]
2022 : Master of Community Health Science (Hospital Management & Health Economy), National University of Malaysia
2020 : Bachelor of Surgery & Bachelor of Medicine (MBBS)
[Working Experience]
2025 - Present : Senior principal assistant director, Health Transformation Office, MOH Malaysia
2022 - 2025 : National Health Financing Section, MOH Malaysia
2020 - 2022 : Digital Health Division, MOH Malaysia
2022 : Master of Community Health Science (Hospital Management & Health Economy), National University of Malaysia
2020 : Bachelor of Surgery & Bachelor of Medicine (MBBS)
[Working Experience]
2025 - Present : Senior principal assistant director, Health Transformation Office, MOH Malaysia
2022 - 2025 : National Health Financing Section, MOH Malaysia
2020 - 2022 : Digital Health Division, MOH Malaysia