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Teamprojekt Multi -Agent based Patient Scheduling

Teamprojekt Multi -Agent based Patient Scheduling. Prof. Dr. C. Becker Prof. Dr. A. Heinzl. Patient Scheduling Background. Hospitals consist of autonomous decentralized units that rarely share information outside their boundaries Treatment of patients involves different units

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Teamprojekt Multi -Agent based Patient Scheduling

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  1. Teamprojekt Multi-Agent based Patient Scheduling Prof. Dr. C. Becker Prof. Dr. A. Heinzl

  2. Patient Scheduling Background • Hospitals consist of autonomous decentralized units that rarely share information outside their boundaries • Treatment of patients involves different units • During treatment, new information on patient health may induce changes of treatment type and order • Emergencies influence treatment plans Clinical Diag-nostics Radio-logy Labo-ratory Anes-thesia OP Station/ Ward Dis-charge

  3. Steinlaus (Petrophaga lorioti),Pschyrembel, Klinisches Wörterbuch, 258. Auflage Challenges • Goal-conflict: • min waiting time for patients vs. max resource utilization for hospital • Patient arrival process is hard to predict: • Elective patients with appointments • Unscheduled walk-ins (and outpatients turning into inpatients) • Emergencies in urgent need of care (interrupting unit work lists) • Uncertainty about the disease is gradually reduced through diagnostics • Alternating treatment plans (i. e., pathways) • Changing priorities (e. g., “normal” patients turning into emergencies) • Complications (e. g., prolonged treatment duration) Coping with sudden interrupts and treatment changes is mandatory for scheduling and resource allocation

  4. Approach Using small active interacting software components (called agents) to exploit decentral information and to reduce complexity Multi-Agent Systems consist out of multiple interacting software components using one or more coordination mechanisms to achieve their individual goals. Overall improvement of schedule through exchange, compensation, and trade of health improvement against resource utilization  Reflects decentralized nature of hospitals Entities of interests modelled as „agents“ that act autonomously Allows evaluation of different scenarios

  5. Multi-Agent Systems Patient agent P1 negotiates with resource agent R1 Patient Agent P1 Resource Agent R1 Physician Resource Agent R2 X-Ray Coordination mechanismhealth function of patient agent

  6. Multi-Agent System Patient-Agent Resource-Agent Patient-Agent Patient-Agent Patient-Agent Resource-Agent Resource-Agent Resource-Agent • Coordination objects are represented byautonomous interacting agents with own goals and private plans

  7. Your Team Project • A Multi-Agent System for Patient Scheduling • relevant agents: patients, resources • modelingandevaluationof different scenarios • integrationof different healthfunctionsandnegotiation/coordinationmechanisms • Android App forpatientagent • Platform/Prerequisites • Java, Basic ProcessModellingKnowHow, Interest todiginto a fascinatingapplicationdomain

  8. Literature • Paulussen, T.O., Jennings, N.R., Decker, K.S., Heinzl, A., 2003. „Distributed patient scheduling in hospitals“ 18th International Joint Conference on Artificial Intelligence, Acapulco, Mexico, pp. 1224-1229. • Paulussen, T.O., Heinzl, A., Becker C. „Multi-Agent based Patient Scheduling in Hospitals“ working paper

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