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In the era of big data, healthcare practitioners are increasingly generating and analyzing data. The huge volume of data provides opportunities for evidence based medicine to answer research and practical questions, and for individuals to make better informed, smarter decision. Yet, making sense of massive healthcare datasets remains a fundamental challenge. In order to make inferences on the data, an effective visual representations of the data is needed. We propose visualization as a means to derive inferences on healthcare data. Design of visual analytics tools, therefore, becomes important in the healthcare domain. Healthcare is a broad area involving users with high variation in roles, expertise, and background. The diverse characteristics of users and their shifting contexts makes it a challenge to process and to present healthcare data in appropriate visual representations that is directly relevant to the analytics tasks.We advocate using the User-Centered Design (UCD) approach in designing and developing visual analytics tools in healthcare. The core research question is how a user centered approach should be adopted in designing visual analytics tools. We address the question by bringing the user centered design process and visual analytics process together, and by applying interdisciplinary methods, such as data mining, information visualization and network analytics. In particular, the dissertation looks to three studies in the healthcare domain where practitioners follow UCD to design visual analytics in healthcare domain. We emphasis the role of user involvement in the entire iterative design lifecycle. The users spanning these studies include patients, physicians, nanomaterial scientists, biomedical professionals, and healthcare policy makers. The three studies are:1. Developing a visual web-based tool called VisOSA to interpret and explore medical records of patients with sleep apnea. For physicians, the ClinicView provides an interactive tool to have an overview of the entire medical record of patients including anomalies, and therefore help with generating research hypothesis. For patients, the PatientView allows the lay individual - without any medical background - to understand their health conditions under treatment at a glance. We also defined medical dashboard in this study. We conducted a supporting quantitative behavioral research to examine the effect of multiple monitors on people's performance. Results suggested that the medical dashboard needs to be arranged as that the most important information is in a single screen. 2. Studying the nanomaterial environmental impact (NEI) is a critical task in nano-health and safety. The information visualization module for NEIMiner is a visual analytic tool that can efficiently query and present large-scale bibliography meta-data, NEI characterizations and nanomaterial toxicity. It supports nanomaterial scientists and analysts to explore the concepts and relationships in studying nanomaterial toxicity and its impact on health. 3. Translating research findings into effective clinical care is another overwhelming task. VATS is a scalable multi-scale visual analytical tool for advancing translational sciences. The system integrates the data of National Center for Advancing Translational Science (NCATS) funded projects and publications from NIH Research Portfolio Online Reporting Tools (RePORTER) and PubMed, and helps healthcare policy makers to understand the big picture of translational science and to evaluate the impact of NCATS funded projects through publicly available data sources.Through these studies, we discuss how innovative visual analytics techniques and capabilities with help users understand and act on various type of data. The results and applications demonstrate what purposes visualizations are used for each problem, how the design and development team make decisions around datasets, and the different visual representations healthcare practitioners use to explore and gain insight of data. The research contributions are (1) a joint model of UCD and visual analytics process that overcomes the design challenges, (2) a justification of how existing data mining and visualization techniques can be usefully combined to support analytics task in healthcare, (3) the approaches to integrate and enrich the dataset, and turn the data into reliable and provable information, (4) the visual encoding and interaction mechanisms to present complex information, (5) three visual analytics system built are beneficial to healthcare community and society. The design guidelines and recommendations generated from these studies are applicable to various domains. We hope this work inspire more innovations and conversations at the intersection of user centered design and visual analytics.
"This book features a comprehensive review of advances in medical visualization and human-computer interaction. It investigates the human roles during a visualization process, specifically motivation-based design, user-based design, and perception-and-cognitive-based design. It also provides real-world examples and insight into the analytical and architectural aspects of user centered design"--Provided by publisher.
Visual analytics has come a long way since its inception in 2005. The amount of data in the world today has increased significantly and experts in many domains are struggling to make sense of their data. Visual analytics is helping them conduct their analyses. While software developers have worked for many years to develop software that helps users do their tasks, this task is becoming more and more onerous, as understanding the needs and data used by expert users requires more than some simple usability testing during the development process. The need for a user centered evaluation process was envisioned in Illuminating the Path, the seminal work on visual analytics by James Thomas and Kristin Cook in 2005. We have learned over the intervening years that not only will user-centered evaluation help software developers to turn out products that have more utility, the evaluation efforts can also help point out the direction for future research efforts. This book describes the efforts that go into analysis, including critical thinking, sensemaking, and various analytics techniques learned from the intelligence community. Support for these components is needed in order to provide the most utility for the expert users. There are a good number of techniques for evaluating software that has been developed within the human-computer interaction (HCI) community. While some of these techniques can be used as is, others require modifications. These too are described in the book. An essential point to stress is that the users of the domains for which visual analytics tools are being designed need to be involved in the process. The work they do and the obstacles in their current processes need to be understood in order to determine both the types of evaluations needed and the metrics to use in these evaluations. At this point in time, very few published efforts describe more than informal evaluations. The purpose of this book is to help readers understand the need for more user-centered evaluations to drive both better-designed products and to define areas for future research. Hopefully readers will view this work as an exciting and creative effort and will join the community involved in these efforts.
This book provides students with an in-depth understanding of the concepts, frameworks and processes used to analyze and present visual data for better decision-making. Expert contributors provide guidance in translating complex concepts from large data sets and how this translation drives management practice. The book’s first part provides a descriptive consideration of state-of-the-art science in visual design. The second part complements the first with a rich set of cases and visual examples, illustrating development and best practice to provide students with real-world context. Through their presentation of modern scientific principles, the editors inspire structured discussions of audience and design, recognizing differences in need, bias and effective processes across contexts and stakeholders. This cutting-edge resource will be of value to students in business analytics, business communication and management science classes, who will learn to be capable managers through the effective and direct visual communication of data. Researchers and practitioners will also find this an engaging and informative book.
Visualization, Visual Analytics and Virtual Reality in Medicine: State-of-the-art Techniques and Applications describes important techniques and applications that show an understanding of actual user needs as well as technological possibilities. The book includes user research, for example, task and requirement analysis, visualization design and algorithmic ideas without going into the details of implementation. This reference will be suitable for researchers and students in visualization and visual analytics in medicine and healthcare, medical image analysis scientists and biomedical engineers in general. Visualization and visual analytics have become prevalent in public health and clinical medicine, medical flow visualization, multimodal medical visualization and virtual reality in medical education and rehabilitation. Relevant applications now include digital pathology, virtual anatomy and computer-assisted radiation treatment planning. - Combines visualization, virtual reality and analytics - Written by leading researchers in the field - Gives the latest state-of-the-art techniques and applications
The only data visualization book written by and for health and healthcare professionals. In health and healthcare, data and information are coming at organizations faster than they can consume and interpret it. Health providers, payers, public health departments, researchers, and health information technology groups know the ability to analyze and communicate this vast array of data in a clear and compelling manner is paramount to success. However, they simply cannot find experienced people with the necessary qualifications. The quickest (and often the only) route to meeting this challenge is to hire smart people and train them. Visualizing Health and Healthcare Data: Creating Clear and Compelling Visualizations to "See how You're Doing" is a one-of-a-kind book for health and healthcare professionals to learn the best practices of data visualization specific to their field. It provides a high-level summary of health and healthcare data, an overview of relevant visual intelligence research, strategies and techniques to gather requirements, and how to build strong teams with the expertise required to create dashboards and reports that people love to use. Clear and detailed explanations of data visualization best practices will help you understand the how and the why. Learn how to build beautiful and useful data products that deliver powerful insights for the end user Follow along with examples of data visualization best practices, including table and graph design for health and healthcare data Learn the difference between dashboards, reports, multidimensional exploratory displays and infographics (and why it matters) Avoid common mistakes in data visualization by learning why they do not work and better ways to display the data Written by a top leader in the field of health and healthcare data visualization, this book is an excellent resource for top management in healthcare, as well as entry-level to experienced data analysts in any health-related organization.
At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear understanding of the analytical techniques currently available
Business intelligence supports managers in enterprises to make informed business decisions in various levels and domains such as in healthcare. These technologies can handle large structured and unstructured data (big data) in the healthcare industry. Because of the complex nature of healthcare data and the significant impact of healthcare data analysis, it is important to understand both the theories and practices of business intelligence in healthcare. Theory and Practice of Business Intelligence in Healthcare is a collection of innovative research that introduces data mining, modeling, and analytic techniques to health and healthcare data; articulates the value of big volumes of data to health and healthcare; evaluates business intelligence tools; and explores business intelligence use and applications in healthcare. While highlighting topics including digital health, operations intelligence, and patient empowerment, this book is ideally designed for healthcare professionals, IT consultants, hospital directors, data management staff, data analysts, hospital administrators, executives, managers, academicians, students, and researchers seeking current research on the digitization of health records and health systems integration.
Design for Health: Applications of Human Factors delves into critical and emergent issues in healthcare and patient safety and how the field of human factors and ergonomics play a role in this domain. The book uses the Design for X (DfX) methodology to discuss a wide range of contexts, technologies, and population dependent criteria (X's) that must be considered in the design of a safe and usable healthcare ecosystem. Each chapter discusses a specific topic (e.g., mHealth, medical devices, emergency response, global health, etc.), reviews the concept, and presents a case study that demonstrates how human factors techniques and principles are utilized for the design, evaluation or improvements to specific tools, devices, and technologies (Section 1), healthcare systems and environments (Section 2), and applications to special populations (Section 3). The book represents an essential resource for researchers in academia as well as practitioners in medical device industries, consumer IT, and hospital settings. It covers a range of topics from medication reconciliation to self-care to the artificial heart. - Uses the Design for X (DfX) methodology - A case study approach provides practical examples for operationalization of key human factors principles and guidelines - Provides specific design guidelines for a wide range of topics including resilience, stress and fatigue management, and emerging technologies - Examines special populations, such as the elderly and the underserved - Brings a multidisciplinary, multi-industry approach to a wide range of healthcare human factors issues
The Handbook of Computational Neurodegeneration provides a comprehensive overview of the field and thus bridges the gap between standard textbooks of research on neurodegeneration and dispersed publications for specialists that have a narrowed focus on computational methods to study this complicated process. The handbook reviews the central issues and methodological approaches related to the field for which the reader pursues a thorough overview. It also conveys more advanced knowledge, thus serving both as an introductory text and as a starting point for an in-depth study of a specific area, as well as a quick reference source for the expert by reflecting the state of the art and future prospects. The book includes topics that are usually missing in standard textbooks and that are only marginally represented in the specific literature. The broad scope of this handbook is reflected by five major parts that facilitate an integration of computational concepts, methods and applications in the study of neurodegeneration. Each part is intended to stand on its own, giving an overview of the topic and the most important problems and approaches, which are supported by examples, practical applications, and proposed methodologies. The basic concepts and knowledge, standard procedures and methods are presented, as well as recent advances and new perspectives.