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OptiPres: a distributed mobile agent decision support system for optimal patient drug prescription

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  • Kevin Miller

    (The University of the West Indies)

  • Gunjan Mansingh

    (The University of the West Indies)

Abstract

Prescribing the right drugs for a patient is a difficult task that takes into consideration several factors. The Institute of Medicine (IOM), U.S.A., has reported based on two major studies (1999–2001 & 2006) that prescribing the wrong medication is a big problem, and the effects can sometimes be fatal. To address this problem, we designed and implemented, a distributed intelligent mobile agent-based system by the name, OptiPres. This system will be used by doctors on their smart phones while prescribing medicines. It will assist them in making more informed decisions by either choosing the optimal solution from processing a repository of past decisions or by presenting a set of possible drugs and using criteria specified by them to identify the optimal drug. The evaluation of OptiPres was done by comparing its recommended outcome of three predefined medical scenarios against the recommendations from a group of doctors and the World Health Organization (WHO) manual entitled:‘Guide to Good Prescribing’. The results indicate that OptiPres is effective in prescribing optimal drugs and in reducing the cognitive burden on doctors, especially in subjective decision making contexts where they have to consider multiple parameters.

Suggested Citation

  • Kevin Miller & Gunjan Mansingh, 2017. "OptiPres: a distributed mobile agent decision support system for optimal patient drug prescription," Information Systems Frontiers, Springer, vol. 19(1), pages 129-148, February.
    • Handle: RePEc:spr:infosf:v:19:y:2017:i:1:d:10.1007_s10796-015-9595-9
    DOI: 10.1007/s10796-015-9595-9
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    References listed on IDEAS

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    Cited by:

    1. Sergey Motorny & Surendra Sarnikar & Cherie Noteboom, 2022. "Design of an Intelligent Patient Decision aid Based on Individual Decision-Making Styles and Information Need Preferences," Information Systems Frontiers, Springer, vol. 24(4), pages 1249-1264, August.

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