Support for fast comprehension of ICU data: visualization using metaphor graphics.
ABSTRACT The time-oriented analysis of electronic patient records on (neonatal) intensive care units is a tedious and time-consuming task. Graphic data visualization should make it easier for physicians to assess the overall situation of a patient and to recognize essential changes over time.
Metaphor graphics are used to sketch the most relevant parameters for characterizing a patient's situation. By repetition of the graphic object in 24 frames the situation of the ICU patient is presented in one display, usually summarizing the last 24 h.
VIE-VISU is a data visualization system which uses multiples to present the change in the patient's status over time in graphic form. Each multiple is a highly structured metaphor graphic object. Each object visualizes important ICU parameters from circulation, ventilation, and fluid balance.
The design using multiples promotes a focus on stability and change. A stable patient is recognizable at first sight, continuous improvement or worsening condition are easy to analyze, drastic changes in the patient's situation get the viewers attention immediately.
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ABSTRACT: In this paper, we reflect on the use of visualization techniques for analyzing electronic health record data with privacy concerns. Privacy-preserving data visualization is a relatively new area of research compared to the more established research areas of privacy-preserving data publishing and data mining. We describe the opportunities and challenges for privacy-preserving visualization of electronic health record data by analyzing the different disclosure risk types, and vulnerabilities associated with commonly used visualization techniques.IEEE VIS 2014 Workshop on Visualizing Electronic Health Record Data, Paris; 11/2014
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ABSTRACT: The purpose of this research is to provide medical clinicians with a new technology for interpreting large and diverse datasets to expedite critical care decision-making in the ICU. We refer to this technology as the medical information visualization assistant (MIVA). MIVA delivers multivariate biometric (bedside) data via a visualization display by transforming and organizing it into temporal resolutions that can provide contextual knowledge to clinicians. The result is a spatial organization of multiple datasets that allows rapid analysis and interpretation of trends. Findings from the usability study of the MIVA static prototype and heuristic inspection of the dynamic prototype suggest that using MIVA can yield faster and more accurate results. Furthermore, comments from the majority of the experimental group and the heuristic inspectors indicate that MIVA can facilitate clinical task flow in context-dependent health care settings. KeywordsBiomedical data visualization–human-computer interaction–health care–health information technology–interface design06/2011: pages 119-128;
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ABSTRACT: Objectives: We evaluated the design of three novel visualization techniques for integrated health information with health care providers in older adult care. Through focus groups, we identified generalizable themes related to the visualization and interpretation of health information. Using these themes we address challenges with visualizing integrated health information and provide recommendations for designers. Methods: We recruited ten health care providers to participate in three focus groups. We applied a qualitative descriptive approach to code and extract themes related to the visualization of graphical displays. Results: We identified a set of four common themes across focus groups related to: 1) Trust in data for decision-making; 2) Perceived level of detail for visualization (subthemes: holistic, individual components); 3) Cognitive issues (subthemes: training and experience; cognitive overload; contrast); and 4) Application of visual displays. Furthermore, recommendations are provided as part of the iterative design process for the visualizations. Conclusions: Data visualization of health information is an important component of care, impacting both the accuracy and speed of decision making. There are both functional and cognitive elements to consider during the development of appropriate visualizations that integrate different components of health.Methods of Information in Medicine 02/2013; 52(3). · 1.08 Impact Factor