A Multi-agent Decision Support Model For Medical Referral Indication

Medical Referral Decisions are clinical decisions by which clinicians determine referralrnindication, type of required services and selection of appropriate providers in medicalrnreferral systems. A referral indication is a decision made by clinicians to determinernwhether referral is needed or not for a patient case under consideration. These decisions arernmade in a clinical environment through referral systems that aim at providing of efficientrnhealthcare services by improving patient outcomes and decreasing cost incurred and timernspent for such services. The quality of referral decisions is highly dependent on thernefficiency and soundness of the decision making process. This inherently complicatedrnreferral decision process depends on a complex mix of both clinical and non-clinicalrnfactors such as patient, clinicians and healthcare system determinants. Recently, a Multi-rnAgent Referral Decision Support (MARDS) framework [6] has been proposed with the aimrnof improving the quality of referral decisions. However, it doesn’t fully address the referralrnindication aspect that is a key component of the medical referral process, which may causernunder-referral and over-referral problems.rnThis thesis proposes a Multi-Agent Decision Support (MADS) model for ReferralrnIndication, Service Identification and Local Consultation aspects of medical referral aimedrnat providing improved decision support to clinicians. The proposed decision support modelrnundertakes the analysis of determinants related to the referral indication, servicernidentification and local medical consultation. This aid is provided through the social agentsrnthat interact and cooperate in the clinical environment, which are designed to interact withrnthe existing CIS (Clinical Information System) and the CKB (Clinical Knowledgebase) tornfetch critical information which supports the analysis of decision making.rnIt is believed that this model extends the MARDS framework by addressing the referralrnindication and service identification aspect for its realization. Moreover, the local medicalrnconsultation service is believed to address the communication and organizationalrnchallenges of the medical consultation process and in turn contributes for the minimizationrnof over-referrals and helps to overcome clinical uncertainties.rnKeywords: Medical Referral Decisions, Referral Indication, Service Identification, LocalrnConsultation, Multi-Agent Systems, Decision Support Systems

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