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Publications (3)1.08 Total impact

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    ABSTRACT: We compare the effectiveness of two types of verbal protocol, concurrent think aloud vs. retrospective sense making, for evaluating the usability of a clinical decision support tool. Thirty-five medical and nursing students participated in a usability experiment. Participants were asked to complete seven tasks using the system under evaluation. Eighteen students were allocated to the concurrent think aloud group and the remainder followed the retrospective protocol. The retrospective protocol was significantly more sensitive than the concurrent protocol in recording unique usability problems related to users' cognitive behaviour. These problems concerned the interpretation and comprehension of statistical output, search results and system messages. These findings can be explained by the retrospective protocol's greater ability to detect compound usability problems, capturing the cognitive dimensions of users' interactions with the interface in greater depth. Evaluations of clinical decision support systems should take an evidence-based approach to selecting protocols.
    Studies in health technology and informatics 01/2013; 192:283-7.
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    ABSTRACT: Populations are under-served by local health policies and management of resources. This partly reflects a lack of realistically complex models to enable appraisal of a wide range of potential options. Rising computing power coupled with advances in machine learning and healthcare information now enables such models to be constructed and executed. However, such models are not generally accessible to public health practitioners who often lack the requisite technical knowledge or skills. To design and develop a system for creating, executing and analysing the results of simulated public health and healthcare policy interventions, in ways that are accessible and usable by modellers and policy-makers. The system requirements were captured and analysed in parallel with the statistical method development for the simulation engine. From the resulting software requirement specification the system architecture was designed, implemented and tested. A model for Coronary Heart Disease (CHD) was created and validated against empirical data. The system was successfully used to create and validate the CHD model. The initial validation results show concordance between the simulation results and the empirical data. We have demonstrated the ability to connect health policy-modellers and policy-makers in a unified system, thereby making population health models easier to share, maintain, reuse and deploy.
    Methods of Information in Medicine 09/2011; 50(5):454-63. · 1.08 Impact Factor
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    ABSTRACT: Populations are under-served by local health policies and management of resources, partly because of a lack of realistically complex models to enable a wide range of potential options to be appraised. Rising computing power coupled with advances in machine learning and healthcare information now enables such models to be constructed and executed. However, such models are not generally accessible to public health practitioners because they do not have the requisite technical knowledge or skills. This paper presents a system for creating, executing and analyzing the results of simulated public health and healthcare policy interventions, which is more accessible and usable by modellers and policy-makers alike.
    Studies in health technology and informatics 01/2010; 160(Pt 1):486-90.