CARE 2014 - Fifth International Workshop on Collaborative Agents -- Research & Development, CARE for Intelligent Mobile Services

Towards Better and more Affordable Healthcare: Incentives, Game Theory, and Artificial Intelligence
Organizers: Amir Ronen, Michal Rosen-Zvi, Ofer Lavi, IBM Research Haifa
Healthcare systems are known to be among the most costly and inefficient ecosystems. It is widely accepted that better and more affordable healthcare is feasible. Interestingly, many of the reasons for this inefficiency are game theoretic: conflicting objectives, asymmetric information, lack of proper incentives, externalities, and more.
The fields of multi-agent systems and algorithmic game theory combine techniques from both computer science and game theory or micro economics to produce algorithms that take these self-interests into account. Such methodologies can be used to develop computerized solutions that overcome the above problems. Moreover, by incorporating patients’ preferences into the algorithms, these solutions can be used to transform health systems to put the interests of patients in center, resulting in better care.
Potential contributions may include but are not limited to the following types:
Analysis and optimization of systems and policies taking self interested behavior into account.
Better allocation of resources aiming to maximize the public’s welfare while meeting budget constraints
Mechanisms to obtain provable fairness of resource allocation fairness for patients, doctors, geographies, and more
Efficient matching taking actors’ preferences into account
Crowd sourcing and prediction markets
Mechanisms to encourage healthy lifestyle
Cost sharing techniques
Description of strategic aspects and complexities in healthcare systems
The workshop will bring together senior decision makers in the EU health system, scientists in algorithmic game theory and multi-agent systems, industry representatives, and healthcare economists in order to identify research gaps, opportunities, and promising directions, evidence for the validity of this approach, long term research strategies, and potential projects.