Addis Ababa University Libraries Electronic Thesis and Dissertations: AAU-ETD! >
Faculty of Informatics >
Thesis - Computer Science >
Please use this identifier to cite or link to this item:
|Title: ||A FRAMEWORK FOR MULTI-AGENT FRAMEWORK FOR MULTI-AGENT REFERRAL DECISION SUPPORT|
|Authors: ||ZEWDU, GEBEYEHU|
|Advisors: ||Dr. Mulugeta Libsie,|
|Keywords: ||Medical Referral Systems,|
Decision Support Systems,
|Copyright: ||Jul-2007 |
|Date Added: ||3-May-2012 |
Medical Referral Systems aim at achieving high standards of care by improving patient outcomes and decreasing costs through optimal use of medical services. The success of these systems is highly dependent on the quality of referral decisions. A referral decision is a clinical decision by which physicians determine referral indication, type of required services and selection of appropriate providers. This inherently complicated process depends on a complex mix of patient, provider and healthcare system determinants. It requires medical and non-medical knowledge that exist distributed among several healthcare providers. In addition, the process requires communication and coordination of information between providers. Little research is done in studying how to provide an intelligent decision support that can help physicians in making better referral decisions. Most of the works focus in studying how to improve referral communication by employing e-Referral systems. This in turn leads to minimal effect in terms of achieving the objectives of Medical Referral Systems.
This thesis proposes a Multi-Agent Referral Decision Support (MARDS) framework aimed at improving quality of referral decisions. It specifically presents a Multi-Criteria Provider Selection (MCPS) model that can be employed by the MARDS to aid physicians in making a better provider selection. The core part of the selection model is simulated by a Multi-Agent Provider Selection System (MPSS), which is developed using JADE (Java Agent DEvelopment Framework). The system is experimented with limited but relevant data and has shown the feasibility of the selection strategy.
The result of this work is believed to be one step towards enhancing existing e-Referral systems with intelligent referral decision support. Moreover, there is a possibility of employing the decision support framework to other application areas of e-Health (like e-Consultation) with some modifications.|
|Appears in:||Thesis - Computer Science|
Items in the AAUL Digital Library are protected by copyright, with all rights reserved, unless otherwise indicated.