A multi-agent system for administering the prescription of anti-retroviral and anti-TB drugs

Abstract

Multi-agent systems (MAS) consist of a number of autonomous agents that communicate among themselves to coordinate their activities in order to solve collectively a complex problem that cannot be tackled by any agent individually. These kinds of systems are appropriate in many domains where problems that are complex, distributed and heterogeneous require communication and coordination between separate autonomous agents, which may be running on different machines distributed over the Internet and are located in many different places.

In the health care domain, MAS have been used for distributed patient scheduling, organ and tissue transplant management, community care, decision support, training and so on. One other promising area of application is in the prescription of antiretroviral and antiTB drugs. The drugs used to treat the two diseases have many and similar side effects that complicate the prescription process. These factors have to be considered when prescribing medication to a person coinfected with HIV and tuberculosis. This is usually done manually using drug recommendation tables, which are complicated to use and require a great deal of decisionmaking. The design and implementation of a multiagent system that assists health care staff in carrying out the complex task of combining antiretroviral and antiTB drugs in an efficient way is described.

The system consists of a number of collaborating agents requiring the communication of complex and diverse forms of information between a variety of clinical and other settings, as well as the coordination between groups of health care professionals (doctors, nurses, counsellors, etcetera.) with very different skills and roles. The agents in the system include: patient agents, nurse agents, lab agents, medication agents and physician agents. The agents may be hosted on different machines, located in many different places distributed over the Internet. The system saves time, minimises decision errors and increases the standard of health care provided to patients.