The IHI Rochester Report 2022 on Healthcare Informatics Research: Resuming After the CoViD-19

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

Directed deadline obligations in agent-based business contracts

There are B2B relationships that presume cooperation in contract enactment. This issue should be taken into account when modeling, for computational handling, contractual commitments through obligations. Deadline obligations have been modeled by considering that reaching the deadline without compliance brings up a violation. When modeling commitments in business contracts, directed obligations have been studied for identifying two agents: the obligation's bearer and the counterparty, who may claim for legal action in case of non-compliance. We argue in favor of a directed deadline obligation approach, taking inspiration on international legislation over trade procedures. Our proposal to model contractual obligations is based on authorizations granted in specific states of an obligation lifecycle model, which we formalize using temporal logic and implement in a rule-based system. The performance of a contractual relationship is supported by a model of flexible deadlines, which allow for further cooperation between autonomous agents. As a result, the decision-making space of agents concerning contractual obligations is enlarged and becomes richer. We discuss the issues that agents should take into account in this extended setting

Supporting multi-level multi-perspective dynamic decision making in medicine.

Most medical decision problems are exceedingly complex and contain a large number of variables. Abstraction facilitates the process of building a decision model by allowing a model builder to work at a level of detail that he is most comfortable with; it is also useful in time-critical situations or when there is insufficient data to support complete specification of probabilities of the uncertain events. In this paper, we identify and formalize abstraction and refinement operations commonly used in model construction. We illustrate the use of these mechanisms with an example on the follow-up management of colorectal cancer patients after surgery