On Regulatory and Organizational Constraints in Visualization Design and Evaluation

Problem-based visualization research provides explicit guidance toward identifying and designing for the needs of users, but absent is more concrete guidance toward factors external to a user's needs that also have implications for visualization design and evaluation. This lack of more explicit guidance can leave visualization researchers and practitioners vulnerable to unforeseen constraints beyond the user's needs that can affect the validity of evaluations, or even lead to the premature termination of a project. Here we explore two types of external constraints in depth, regulatory and organizational constraints, and describe how these constraints impact visualization design and evaluation. By borrowing from techniques in software development, project management, and visualization research we recommend strategies for identifying, mitigating, and evaluating these external constraints through a design study methodology. Finally, we present an application of those recommendations in a healthcare case study. We argue that by explicitly incorporating external constraints into visualization design and evaluation, researchers and practitioners can improve the utility and validity of their visualization solution and improve the likelihood of successful collaborations with industries where external constraints are more present.Comment: 9 pages, 2 figures, presented at BELIV workshop associated with IEEE VIS 201

User-centered visual analysis using a hybrid reasoning architecture for intensive care units

One problem pertaining to Intensive Care Unit information systems is that, in some cases, a very dense display of data can result. To ensure the overview and readability of the increasing volumes of data, some special features are required (e.g., data prioritization, clustering, and selection mechanisms) with the application of analytical methods (e.g., temporal data abstraction, principal component analysis, and detection of events). This paper addresses the problem of improving the integration of the visual and analytical methods applied to medical monitoring systems. We present a knowledge- and machine learning-based approach to support the knowledge discovery process with appropriate analytical and visual methods. Its potential benefit to the development of user interfaces for intelligent monitors that can assist with the detection and explanation of new, potentially threatening medical events. The proposed hybrid reasoning architecture provides an interactive graphical user interface to adjust the parameters of the analytical methods based on the users' task at hand. The action sequences performed on the graphical user interface by the user are consolidated in a dynamic knowledge base with specific hybrid reasoning that integrates symbolic and connectionist approaches. These sequences of expert knowledge acquisition can be very efficient for making easier knowledge emergence during a similar experience and positively impact the monitoring of critical situations. The provided graphical user interface incorporating a user-centered visual analysis is exploited to facilitate the natural and effective representation of clinical information for patient care

Potential applications of simulation modelling techniques in healthcare: lessons learned from aerospace and military

The Aerospace and Military areas are to do with complex missions and situations. Modelling and Simulation (M&S) has been applied in many areas of defence ranging from space sciences, satellite engineering to multi-warfare (air warfare, undersea warfare), air & missile defence, acquisition, tactical military trainings & exercises, national security analysis and strategic decision making & planning, etc. The application of simulation modelling techniques in healthcare would improve the provision of healthcare services; however, their application has been much relatively feeble in the healthcare sector as compared to the defence sector. This paper presents results from a systematic literature survey on applications of modelling simulation techniques in the Aerospace & Military. The knowledge gained or lessons learned from the survey were finally used to analyze the potential applications of the simulation modelling techniques to the healthcare sector. Results show that in the defence sector, Distributed Simulation has now become a widely adopted technique. However, System Dynamics (SD) and Discrete Event Simulation (DSE) have also gained relative attention. From this survey it becomes clear that various simulation modelling techniques are useful for specific purposes and have potential applications in the healthcare sector

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 341)

This bibliography lists 133 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during September 1990. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

A Decision Support System for Diagnostics and Treatment Planning in Traumatic Brain Injury.

Traumatic brain injury (TBI) occurs when an external force causes functional or structural alterations in the brain. Clinical characteristics of TBI vary greatly from patient to patient, and a large amount of data is gathered during various phases of clinical care in these patients. It is hard for clinicians to efficiently integrate and interpret all of these data and plan interventions in a timely manner. This paper describes the technical architecture and functionality of a web-based decision support system (DSS), which not only provides advanced support for visualizing complex TBI data but also predicts a possible outcome by using a state-of-the-art Disease State Index machine-learning algorithm. The DSS is developed by using a three-layered architecture and by employing modern programming principles, software design patterns, and using robust technologies (C#, ASP.NET MVC, HTML5, JavaScript, Entity Framework, etc.). The DSS is comprised of a patient overview module, a disease-state prediction module, and an imaging module. After deploying it on a web-server, the DSS was made available to two hospitals in U.K. and Finland. Afterwards, we conducted a validation study to evaluate its usability in clinical settings. Initial results of the study indicate that especially less experience clinicians may benefit from this type of decision support software tool

Visualization Literacy and Decision-making in Healthcare

The ability of workers in the healthcare industry to analyze, interpret and communicate with health data is critical to decision-making and impacts both health and business outcomes. Optimal decision-making requires having real-time access to information that provides useful insights and that lends itself to collaborative decision-making. Data visualizations have the potential to facilitate decision-making in healthcare when presented as a dashboard. However, dashboards have shown varying results in both effectiveness and adoption. Data or graphical literacy challenges experienced by health team members could complicate strategic decision-making through an inability to correctly interpret or summarize the information presented in a dashboard. One assumption is that visualization literacy and its impact on how people process health data visualizations play a part in the effective interpretation of information to support decision-making. To determine the impact of visualization literacy on the process of decision-making in a healthcare setting, we first developed and deployed a dashboard designed to provide important information for decision-makers on a clinical trial management team. We engaged Project Managers and Medical Managers in the project as key decision-makers on the team. The dashboard was integrated into the normal workflow of a clinical trial management team and designated as the tool used in the workflow to report on the trial status within the organization. Next, we administered a series of assessments to the key decision-makers. The assessments were designed to evaluate numeracy, visualization literacy, and the impact of both on the decision-making ability of participants. Decision-making was assessed using a common workflow scenario supported by visualizations from the deployed dashboard. Additionally, we were interested in exploring indicators related to job satisfaction that was collected during the project period through a formal engagement survey. We performed a general linear model to assess the relationship between the assessments and decision-making. Results of our project show a significant and clear relationship between visualization literacy and decision-making ability and an insignificant relationship between numeracy and decision-making ability. Job satisfaction scores for the participant group obtained through the engagement survey suggest favorable results. However, areas of opportunity for improvement illuminated through the survey included better tools and additional resources to support the execution of tasks, a better workload balance, and improvements in collaboration across departments and functions. The results of this project contribute to the informatics discipline by demonstrating that information obtained from data visualizations produced through the aggregation of multiple sources of data can be effective decision-support tools if they are designed with user skills and abilities in mind. The results of the project suggest an opportunity to develop more useful and usable tools to improve job satisfaction as well as organizational business objectives related to workforce staffing, job competencies, and learning and development initiatives

From Social Simulation to Integrative System Design

As the recent financial crisis showed, today there is a strong need to gain "ecological perspective" of all relevant interactions in socio-economic-techno-environmental systems. For this, we suggested to set-up a network of Centers for integrative systems design, which shall be able to run all potentially relevant scenarios, identify causality chains, explore feedback and cascading effects for a number of model variants, and determine the reliability of their implications (given the validity of the underlying models). They will be able to detect possible negative side effect of policy decisions, before they occur. The Centers belonging to this network of Integrative Systems Design Centers would be focused on a particular field, but they would be part of an attempt to eventually cover all relevant areas of society and economy and integrate them within a "Living Earth Simulator". The results of all research activities of such Centers would be turned into informative input for political Decision Arenas. For example, Crisis Observatories (for financial instabilities, shortages of resources, environmental change, conflict, spreading of diseases, etc.) would be connected with such Decision Arenas for the purpose of visualization, in order to make complex interdependencies understandable to scientists, decision-makers, and the general public.Comment: 34 pages, Visioneer White Paper, see http://www.visioneer.ethz.c

Business Intelligence Competencies: Making Healthcare Data Come Alive

Business Intelligence Competencies: Making Healthcare Data Come Alive While a wealth of healthcare related data exists, nurse leaders (NL) have yet to understand its implications and adopt analytical skills to lead in the transformation of care delivery. Information science is at a new frontier for nursing to embrace. It is critical for nursing leadership to advance and support business intelligence (BI) and interactive data visualization (IDV) skills across the organization and advocate for greater engagement of nurses in health system decision making. With these new tools and competencies, nursing and other health professions can innovate best practices, providing enhanced quality, safety, and value in healthcare. The aim of this Doctor of Nursing evidence-based project was to engage NL’s to improve and extend competencies in BI and IDV. A survey was administered to NL’s to assess their knowledge and use of these analytic tools and then guide a process for skill development via two workshops presenting an overview of BI and IDV to NL’s. The use of BI is still in its’ infancy, dashboards tools are beginning to be deployed across healthcare organization, however, data in real time is not readily available, nor is the ability to interact and conduct data discovery. The effectiveness of the education program was evaluated by the attendees’ willingness to participate in workshops covering the basic uses of BI and IDV and understanding of the opportunities to incorporate them into their current leadership role