In 2020, the CoViD-19 pandemic spread worldwide in an unexpected way and suddenly modified many life issues, including social habits, social relationships, teaching modalities, and more. Such changes were also observable in many different healthcare and medical contexts. Moreover, the CoViD-19 pandemic acted as a stress test for many research endeavors, and revealed some limitations, especially in contexts where research results had an immediate impact on the social and healthcare habits of millions of people. As a result, the research community is called to perform a deep analysis of the steps already taken, and to re-think steps for the near and far future to capitalize on the lessons learned due to the pandemic. In this direction, on June 09th–11th, 2022, a group of twelve healthcare informatics researchers met in Rochester, MN, USA. This meeting was initiated by the Institute for Healthcare Informatics—IHI, and hosted by the Mayo Clinic. The goal of the meeting was to discuss and propose a research agenda for biomedical and health informatics for the next decade, in light of the changes and the lessons learned from the CoViD-19 pandemic. This article reports the main topics discussed and the conclusions reached. The intended readers of this paper, besides the biomedical and health informatics research community, are all those stakeholders in academia, industry, and government, who could benefit from the new research findings in biomedical and health informatics research. Indeed, research directions and social and policy implications are the main focus of the research agenda we propose, according to three levels: the care of individuals, the healthcare system view, and the population view.
Bibliographical noteFunding Information:
Open access funding provided by Politecnico di Milano within the CRUI-CARE Agreement. C.C. is partially funded by the Ministry of University and Research, MIUR, Project Italian Outstanding Departments, 2018-2022. J.C.F. is partially funded by the National Institutes of Health (USA) Clinical Translational Science Award UL1-TR002538. P.H. is partially funded by the Hanse-Wissenschaftskolleg Institute for Advanced Study and by the Mahidol University Office of International Relations under the MIRU phase-II award. J.H. is partially funded by the National Institutes of Health (USA) Clinical Translational Science Award, UL1-TR001878. G.P. is partially funded by the EU H2020 program: “PERISCOPE: Pan European Response to the Impacts of CoViD-19 and future Pandemics and Epidemics” (grant no. 101016233). G.S. is supported in part by the Slovenian Research Agency under the grants ARRS N2-0101 and ARRS P2-0057. P.V. is partially funded by the research project PON VQA (Validated Query Answer) co-funded by the Ministry of Economic Development (MISE) 2019–2022. C.C.Y. is supported in part by the National Science Foundation (USA) under the Grant IIS-1741306, IIS-2235548, and the Department of Defense (USA) Data Science Award.
© 2023, The Author(s).
- Artificial intelligence in medicine
- Biomedical and health informatics
- Research trends
ASJC Scopus subject areas
- Information Systems
- Health Informatics
- Computer Science Applications
- Artificial Intelligence