Towards Better and more Affordable Healthcare: Incentives, Game Theory, and Artificial Intelligence

Workshop on System of Systems Approach
May 5th Paris, France
In conjunction with AAMAS, May 5-9, 2014

Important Dates
Keynote Speakers
Papers Submission
Ideas Corner

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
  • Use case ideas

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, concrete use cases, long term research strategies, and potential projects.