Abstract
This paper details updated results concerning an implementation of a Multiple Classification Ripple Down Rules (MCRDR) system which can be used to provide quality Decision Support Services to pharmacists practicing medication reviews (MRs), particularly for high risk patients. The system was trained on 126 genuine cases by an expert in the field; over the course of 19 hours the system had learned 268 rules and was considered to encompass over 80% of the domain. Furthermore, the system was found able to improve the quality and consistency of the medication review reports produced, as it was shown that there was a high incidence of missed classifications under normal conditions, which were repaired by the system automatically. However, shortcomings were identified including an inability to handle absent data, and shortcomings concerning standardization in the domain, proposals to solve these shortcomings are included.
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References
Peterson, G.: Continuing evidence of inappropriate medication usage in the elderly, in Australian Pharmacist 23, 2 (2004)
Bates, D., Cullen, D., Laird, N., Petersen, L., Small, S., Servi, D., Laffel, G., Sweitzer, B., Shea, B., Hallisey, R.: Incidence of adverse drug events and potential adverse drug events. Implications for prevention. ADE Prevention Study Group. JAMA , pp.29–34 (1995)
Peterson, G.: The future is now: the importance of medication review, in Australian Pharmacist, pp. 268–75 (2002)
Bindoff, I., Tenni, P., Kang, B., Peterson, G.:Intelligent Decision Support for Medication Review. In: Advances in Knowledge Acquisition and Management, Conference. Location (2006)
Bindoff, I., Tenni, P., Peterson, G., Kang, B., Jackson, S.: Development of an intelligent decision support system for medication review. J. Clin. Pharm. Ther. 32, 81–88 (2007)
Kinrade, W.: Review of Domiciliary Medication Management Review Software, Pharmacy Guild of Australia (2003)
Aamodt, A., Plaza, E.: Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. AICom - Artificial Intelligence Communications 7, 39–59 (1994)
Compton, P., Kang, B., Preston, P., Mulholland, M.: Knowledge Acquisition without Analysis. In: Knowledge Acquisition for Knowledge-Based Systems, Conference. Location (1993)
Tenni, P., Peterson, G., Jackson, S., Hassan, O. to I. Bindoff (2005)
MediFlags, http://www.mediflags.com/
Compton, P., Jansen, R.: A philosophical basis for knowledge acquisition. In: European Knowledge Acquisition for Knowledge-Based Systems, Conference. Location (1989)
Rivest, R.: Learning Decision Lists. Machine Learning 2, 229–246 (1987)
Kang, B., Compton, P., Preston, P.: Multiple Classification Ripple Down Rules (1994)
Kang, B., Compton, P., Preston, P.: Multiple Classification Ripple Down Rules: Evaluation and Possibilities. In: AIII-Sponsored Banff Knowledge Acquisition for Knowledge-Based Systems, Conference. Location (1995)
Preston, P., Edwards, G., Compton, P.: A 2000 Rule Expert System Without a Knowledge Engineer. In: AIII-Sponsored Banff Knowledge Acquisition for Knowledge-Based Systems, Conference. Location (1994)
Compton, P., Jansen, R.: Cognitive aspects of knowledge acquisition. In: AAAI Spring Consortium, Conference. Location (1992)
Kang, B., Compton, P.: A Maintenance Approach to Case Based Reasoning (1994)
Bindoff, I.: An Intelligent Decision Support System for Medication Review, in Computing, vol. 65. University of Tasmania, Hobart (2005)
Tenni, P. to I. Bindoff (2005)
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Bindoff, I., Kang, B.H., Ling, T., Tenni, P., Peterson, G. (2007). Applying MCRDR to a Multidisciplinary Domain. In: Orgun, M.A., Thornton, J. (eds) AI 2007: Advances in Artificial Intelligence. AI 2007. Lecture Notes in Computer Science(), vol 4830. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76928-6_53
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DOI: https://doi.org/10.1007/978-3-540-76928-6_53
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