Factors known to influence acceptance of clinical decision support systems.

Clinical Decision Support Systems (CDSS) have been shown to improve clinical performance and patient outcomes, but the failure rate of such systems is still over 50 percent. To contribute to a wider understanding of issues surrounding CDDS acceptance, we performed a systematic review of studies that evaluated CDSS implementations in clinical care to determine the factors that are associated with acceptance of CDSS by physicians. The factors that were found were categorized according to the HOT-fit framework. The mapping of factors concerning CDSS acceptance on the HOT-fit framework revealed gaps in each domain of the framework and showed that research has mainly focused on human and technology factors and a lack of research on organizational factors. A potential area of research could thus be studying the organizational factors that may influence CDSS acceptance.

Reducing clinicians' cognitive workload by system redesign; a pre-post think aloud usability study.

Interactive Health Information systems are often considered cognitively complex by their users, leading to high cognitive burden and increased workload. This paper explores if Think Aloud usability testing provides valuable input to effectively redesign a web-based Data Query Tool in Intensive Care and to reduce physicians' cognitive workload during system interaction. Pre and post redesign usability testing demonstrated a major reduction in the cognitive task workload after redesign of the tool. Classification of revealed usability problems by means of the User Action Framework pointed out that usability problems related to the cognitively planning of actions by system users foremost affected cognitive task workload. This result may support Health Information system (re)design efforts on how to tackle the system's cognitive complexity and in so doing improve on its usability.

Classification and prioritization of usability problems using an augmented classification scheme.

Various methods exist for conducting usability evaluation studies in health care. But although the methodology is clear, no usability evaluation method provides a framework by which the usability reporting activities are fully standardized. Despite the frequent use of forms to report the usability problems and their context-information, this reporting is often hindered by information losses. This is due to the fact that evaluators' problem descriptions are based on individual judgments of what they find salient about a usability problem at a certain moment in time. Moreover, usability problems are typically classified in terms of their type, number, and severity. These classes are usually devised by the evaluator for the purpose at hand and the used problem types often are not mutually exclusive, complete and distinct. Also the impact of usability problems on the task outcome is usually not taken into account. Consequently, problem descriptions are often vague and even when combined with their classification in type or severity leave room for multiple interpretations when discussed with system designers afterwards. Correct interpretation of these problem descriptions is then highly dependent upon the extent to which the evaluators can retrieve relevant details from memory. To remedy this situation a framework is needed guiding usability evaluators in high quality reporting and unique classification of usability problems. Such a framework should allow the disclosure of the underlying essence of problem causes, the severity rating and the classification of the impact of usability problems on the task outcome. The User Action Framework (UAF) is an existing validated classification framework that allows the unique classification of usability problems, but it does not include a severity rating nor does it contain an assessment of the potential impact of usability flaws on the final task outcomes. We therefore augmented the UAF with a severity rating based on Nielsen's classification and added a classification for expressing the potential impact of usability problems on final task outcomes. Such an augmented scheme will provide the necessary information to system developers to understand the essence of usability problems, to prioritize problems and to tackle them in a system redesign. To investigate the feasibility of such an augmented scheme, it was applied to the results of usability studies of a computerized physician order entry system (CPOE). The evaluators classified the majority of the usability problems identically by use of the augmented UAF. In addition it helped in differentiating problems that looked similar but yet affect the user-system interaction and the task results differently and vice versa. This work is of value not only for system developers but also for researchers who want to study the results of other usability evaluation studies, because this scheme makes the results of usability studies comparable and easily retrievable.