Visual displays for cyber network defense.

Five computer network Defence displays (one Alphanumeric and four graphical displays: Radial Traffic Analyser, Bar Graph, Cube, and Treemap) were evaluated. Two experiments were conducted using different methodological procedures. Participants responded to questions that were structured to approximate various ways in which analysts might need to consider network traffic. Numerous significant effects were obtained and a fairly clear rank ordering of performance for the four graphical displays was obtained across experiments (from best to worst): Bar Graph, Cube, Radial Traffic Analyser, and Treemap. The results are interpreted from the perspective of ecological interface design: the quality of performance is directly related to the quality of semantic mapping between work domain, display, and human constraints. Factors that may have contributed to the poor performance for the Radial Traffic Analyser and Treemap displays are discussed. General implications for display and interface design are provided. Practitioner summary: Proposed displays for computer network Defence are evaluated; the results are interpreted from the perspective of ecological interface design. The associated design principles are applicable to all analogical graphical displays. Abbreviation: CND: cyber network defence; CSE: cognitive systems engineering; EID: ecological interface design; ICMP: internet control message protocol; IP: internet protocol; RTA: radial traffic analyzer; TCP: transmission control protocol; UDP: user datagram protocol.

Evaluating a Modular Decision Support Application For Colorectal Cancer Screening.

BACKGROUND: There is a need for health information technology evaluation that goes beyond randomized controlled trials to include consideration of usability, cognition, feedback from representative users, and impact on efficiency, data quality, and clinical workflow. This article presents an evaluation illustrating one approach to this need using the Decision-Centered Design framework. OBJECTIVE: To evaluate, through a Decision-Centered Design framework, the ability of the Screening and Surveillance App to support primary care clinicians in tracking and managing colorectal cancer testing. METHODS: We leveraged two evaluation formats, online and in-person, to obtain feedback from a range primary care clinicians and obtain comparative data. Both the online and in-person evaluations used mock patient data to simulate challenging patient scenarios. Primary care clinicians responded to a series of colorectal cancer-related questions about each patient and made recommendations for screening. We collected data on performance, perceived workload, and usability. Key elements of Decision-Centered Design include evaluation in the context of realistic, challenging scenarios and measures designed to explore impact on cognitive performance. RESULTS: Comparison of means revealed increases in accuracy, efficiency, and usability and decreases in perceived mental effort and workload when using the Screening and Surveillance App. CONCLUSION: The results speak to the benefits of using the Decision-Centered Design approach in the analysis, design, and evaluation of Health Information Technology. Furthermore, the Screening and Surveillance App shows promise for filling decision support gaps in current electronic health records.

Designing Colorectal Cancer Screening Decision Support: A Cognitive Engineering Enterprise.

Adoption of clinical decision support has been limited. Important barriers include an emphasis on algorithmic approaches to decision support that do not align well with clinical work flow and human decision strategies, and the expense and challenge of developing, implementing, and refining decision support features in existing electronic health records (EHRs). We applied decision-centered design to create a modular software application to support physicians in managing and tracking colorectal cancer screening. Using decision-centered design facilitates a thorough understanding of cognitive support requirements from an end user perspective as a foundation for design. In this project, we used an iterative design process, including ethnographic observation and cognitive task analysis, to move from an initial design concept to a working modular software application called the Screening & Surveillance App. The beta version is tailored to work with the Veterans Health Administration's EHR Computerized Patient Record System (CPRS). Primary care providers using the beta version Screening & Surveillance App more accurately answered questions about patients and found relevant information more quickly compared to those using CPRS alone. Primary care providers also reported reduced mental effort and rated the Screening & Surveillance App positively for usability.