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Validation of decision support software for identification of drug-related problems in home medicines reviews


Curtain, C and Bindoff, I and Westbury, J and Peterson, G, Validation of decision support software for identification of drug-related problems in home medicines reviews, Making an Impact: 11th National Conference of Emerging Researchers in Ageing - Abstracts and Proceedings, 19-20 November, Brisbane, Queensland Australia, pp. 94-97. (2012) [Refereed Conference Paper]

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Copyright 2010 Emerging Researchers in Ageing Australia (ERA)

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Background: Accredited pharmacists in Australia are funded to conduct home medicines reviews (HMRs) to address drug-related problems (DRPs) and optimise patient medication use. HMRs are suited to older patients who are more likely to be associated with greater medication use and DRPs. The HMR process involves collation and analysis of patient-specific information to determine actual and potential DRPs and recommend solutions. Clinical decision support systems have been commercially implemented to assist with this task. This research performs validation of two such systems by comparison with the reviewing pharmacists’ findings.

Method: HMR data collected during 2008 were entered into software which utilised artificial intelligence, Medscope™ Medication Review Mentor (MRM), and software which did not, Monitor-Rx (MRX). DRPs identified by each software program were recorded. A random sample of 20 HMRs with the DRP findings of MRM (N=125), MRX (N=259) and original pharmacist findings (N=73) were presented to 12 clinical pharmacy experts. Experts evaluated each source on a per case basis for clinical relevance, excessive DRP findings and missed clinically relevant DRPs.

Results: Experts agreed that MRM (193 of 240 opinions - 80%) and pharmacists (76%) identified clinically relevant DRPs, yet significantly less agreed MRX was clinically relevant (13%). No significant difference was found between pharmacists and MRM concerning relevant DRPs, yet MRM actually identified a greater number of DRPs. Experts agreed each source missed clinically relevant DRPs (pharmacists 69%, MRM 48%, MRX 76%), with significant difference between sources. Opinion concerning excessive DRP findings was also significantly different between sources. Experts agreed pharmacists (88%) and MRM (65%) did not identify excessive DRPs, in contrast to MRX (3%).

Conclusion: Software which utilises artificial intelligence, such as MRM, may assist pharmacists in performing HMR activities via identification of an acceptable number of relevant DRPs.

Item Details

Item Type:Refereed Conference Paper
Keywords:pharmacy, clinical decision, support, home, medicines, review
Research Division:Biomedical and Clinical Sciences
Research Group:Pharmacology and pharmaceutical sciences
Research Field:Clinical pharmacy and pharmacy practice
Objective Division:Health
Objective Group:Evaluation of health and support services
Objective Field:Evaluation of health and support services not elsewhere classified
UTAS Author:Curtain, C (Mr Colin Curtain)
UTAS Author:Bindoff, I (Dr Ivan Bindoff)
UTAS Author:Westbury, J (Associate Professor Juanita Breen)
UTAS Author:Peterson, G (Professor Gregory Peterson)
ID Code:81459
Year Published:2012
Deposited By:Pharmacy
Deposited On:2012-12-07
Last Modified:2017-11-02
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