Interactive Data Visualization Techniques Applied to Healthcare Decision Making

Data visualization techniques are widely applied in all kinds of organizations, turning tables of numbers into visualizations for discovery, information communication, and knowledge sharing. Data visualization solutions can be found everywhere in healthcare systems from hospital operations monitoring and patient profiling to demand projection and capacity planning. In this chapter, interactive data visualization techniques are discussed and their applications to various aspects of healthcare systems are explored. Compared to static data visualization techniques, interactive ones allow users to explore the data and find the insights themselves. Four case studies are given to illustrate how interactive data visualization techniques are applied in healthcare: summary and overview, information selection and filtering, patient flow visualization, and geographical and longitudinal analyses. These case studies show that interactive data visualization techniques expand the boundary of data visualization as a pure presentation tool and bring certain analytical capability to support better healthcare decision making.

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Interactive Data Visualization to Understand Data Better

Decision Management ◽

10.4018/978-1-5225-1837-2.ch002 ◽

2017 ◽

pp. 27-36

Author(s):

Zhecheng Zhu ◽

Bee Hoon Heng ◽

Kiok-Liang Teow

Keyword(s):

Case Studies ◽

Healthcare System ◽

Data Visualization ◽

Healthcare Systems ◽

Multiple Data ◽

Interactive Data ◽

Interactive Map ◽

Visual Impact ◽

Visualization Techniques

This paper focuses on interactive data visualization techniques and their applications in healthcare systems. Interactive data visualization is a collection of techniques translating data from its numeric format to graphic presentation dynamically for easy understanding and visual impact. Compared to conventional static data visualization techniques, interactive data visualization techniques allow users to self-explore the entire data set by instant slice and dice, quick switching among multiple data sources. Adjustable granularity of interactive data visualization allows for both detailed micro information and aggregated macro information displayed in a single chart. Animated transition adds extra visual impact that describes how system transits from one state to another. When applied to healthcare system, interactive visualization techniques are useful in areas such as information integration, flow or trajectory presentation and location related visualization, etc. In this paper, three case studies are shared to illustrate how interactive data visualization techniques are applied to various aspects of healthcare systems. The first case study shows a pathway visualization representing longitudinal disease progression of a patient cohort. The second case study shows a dashboard profiling different patient cohorts from multiple perspectives. The third case study shows an interactive map illustrating patient geographical distribution at adjustable granularity. All three case studies illustrate that interactive data visualization techniques help quick information access, fast knowledge sharing and better decision making in healthcare system.

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Interactive Data Visualization to Understand Data Better

International Journal of Knowledge Discovery in Bioinformatics ◽

10.4018/ijkdb.2014070101 ◽

2014 ◽

Vol 4 (2) ◽

pp. 1-10 ◽

Cited By ~ 1

Author(s):

Zhecheng Zhu ◽

Bee Hoon Heng ◽

Kiok Liang Teow

Keyword(s):

Case Studies ◽

Healthcare System ◽

Data Visualization ◽

Healthcare Systems ◽

Data Set ◽

First Case ◽

Interactive Data ◽

Visual Impact ◽

Visualization Techniques

This paper focuses on interactive data visualization techniques and their applications in healthcare systems. Interactive data visualization is a collection of techniques translating data from its numeric format to graphic presentation dynamically for easy understanding and visual impact. Compared to conventional static data visualization techniques, interactive data visualization techniques allow users to self-explore the entire data set by instant slice and dice, quick switching among multiple data sources. Adjustable granularity of interactive data visualization allows for both detailed micro information and aggregated macro information displayed in a single chart. Animated transition adds extra visual impact that describes how system transits from one state to another. When applied to healthcare system, interactive visualization techniques are useful in areas such as information integration, flow or trajectory presentation and location related visualization, etc. In this paper, three case studies are shared to illustrate how interactive data visualization techniques are applied to various aspects of healthcare systems. The first case study shows a pathway visualization representing longitudinal disease progression of a patient cohort. The second case study shows a dashboard profiling different patient cohorts from multiple perspectives. The third case study shows an interactive map illustrating patient geographical distribution at adjustable granularity. All three case studies illustrate that interactive data visualization techniques help quick information access, fast knowledge sharing and better decision making in healthcare system.

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An Interactive Data Visualization Framework for Exploring Geospatial Environmental Datasets and Model Predictions

Water ◽

10.3390/w12102928 ◽

2020 ◽

Vol 12 (10) ◽

pp. 2928

Author(s):

Jeffrey D. Walker ◽

Benjamin H. Letcher ◽

Kirk D. Rodgers ◽

Clint C. Muhlfeld ◽

Vincent S. D’Angelo

Keyword(s):

Decision Making ◽

Case Studies ◽

Data Visualization ◽

Large Scale ◽

Research Management ◽

Web Based ◽

Environmental Models ◽

Potential Benefits ◽

Interactive Data ◽

Data Visualizations

With the rise of large-scale environmental models comes new challenges for how we best utilize this information in research, management and decision making. Interactive data visualizations can make large and complex datasets easier to access and explore, which can lead to knowledge discovery, hypothesis formation and improved understanding. Here, we present a web-based interactive data visualization framework, the Interactive Catchment Explorer (ICE), for exploring environmental datasets and model outputs. Using a client-based architecture, the ICE framework provides a highly interactive user experience for discovering spatial patterns, evaluating relationships between variables and identifying specific locations using multivariate criteria. Through a series of case studies, we demonstrate the application of the ICE framework to datasets and models associated with three separate research projects covering different regions in North America. From these case studies, we provide specific examples of the broader impacts that tools like these can have, including fostering discussion and collaboration among stakeholders and playing a central role in the iterative process of data collection, analysis and decision making. Overall, the ICE framework demonstrates the potential benefits and impacts of using web-based interactive data visualization tools to place environmental datasets and model outputs directly into the hands of stakeholders, managers, decision makers and other researchers.

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Application of Geographical Information System and Interactive Data Visualization in Healthcare Decision Making

Decision Management ◽

10.4018/978-1-5225-1837-2.ch057 ◽

2017 ◽

pp. 1244-1254

Author(s):

Zhecheng Zhu

Keyword(s):

Decision Making ◽

Information System ◽

Data Visualization ◽

Healthcare Services ◽

Geographical Information ◽

Multiple Data ◽

Interactive Data ◽

Visual Impact ◽

Site Planning ◽

Visualization Techniques

This paper focuses on two techniques and their applications in healthcare systems: geographic information system (GIS) and interactive data visualization. GIS is a type of technique applied to manipulate, analyze and display spatial information. It is a useful tool tackling location related problems. GIS applications in healthcare include evaluation of accessibility to healthcare facilities, site planning of new healthcare services and analysis of risks and spreads of infectious diseases. Interactive data visualization is a collection of techniques translating data from its numeric format to graphic presentation dynamically for easy understanding and visual impact. Compared to conventional static data visualization techniques, interactive data visualization techniques allow user to self-explore the entire data set by instant slice and dice, quick switching among multiple data sources. Adjustable granularity of interactive data visualization allows for both detailed micro information and aggregated macro information displayed in a single chart. Animated transition adds extra visual impact that describes how system transits from one state to another. When applied to healthcare system, interactive visualization techniques are useful in areas such as information integration, flow or trajectory presentation and location related visualization, etc. One area both techniques intersect is location analysis. In this paper, real life case studies will be given to illustrate how these two techniques, when combined together, help in solving quantitative or qualitative location related problem, visualizing geographical information and accelerating decision making procedures.

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Data Visualization in R

Advances in Business Information Systems and Analytics - Sentiment Analysis and Knowledge Discovery in Contemporary Business ◽

10.4018/978-1-5225-4999-4.ch012 ◽

2019 ◽

pp. 205-222

Author(s):

S. R. Mani Sekhar ◽

Siddesh G. M. ◽

Sunilkumar S. Manvi

Keyword(s):

Decision Making ◽

Case Studies ◽

Data Visualization ◽

Information Visualization ◽

Real World ◽

Valuable Insight ◽

Visualization Method ◽

Use Of Data ◽

R Programming ◽

Visualization Techniques

Data visualization helps the users to understand the relationships and associations between information. Visualization helps in minimizing the errors generated during decision making. Different visualization methods have been developed to unlock the valuable insight. These methods have been developed on the supposition that the information to be present is free from ambiguity. This chapter provides an overview of data visualization techniques in R programming. Various methods have been discussed with supported explanation and examples which in turn helps the reader to create their own visualization method. Later, four different case studies are presented to understand the importance and use of data visualization in real-world problems.

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Application of Geographical Information System and Interactive Data Visualization in Healthcare Decision Making

International Journal of Big Data and Analytics in Healthcare ◽

10.4018/ijbdah.2016010104 ◽

2016 ◽

Vol 1 (1) ◽

pp. 49-58 ◽

Cited By ~ 1

Author(s):

Zhecheng Zhu

Keyword(s):

Decision Making ◽

Information System ◽

Data Visualization ◽

Spatial Information ◽

Real Life ◽

Geographical Information ◽

Data Set ◽

Interactive Data ◽

Visual Impact ◽

Visualization Techniques

This paper focuses on two techniques and their applications in healthcare systems: geographic information system (GIS) and interactive data visualization. GIS is a type of technique applied to manipulate, analyze and display spatial information. It is a useful tool tackling location related problems. GIS applications in healthcare include evaluation of accessibility to healthcare facilities, site planning of new healthcare services and analysis of risks and spreads of infectious diseases. Interactive data visualization is a collection of techniques translating data from its numeric format to graphic presentation dynamically for easy understanding and visual impact. Compared to conventional static data visualization techniques, interactive data visualization techniques allow user to self-explore the entire data set by instant slice and dice, quick switching among multiple data sources. Adjustable granularity of interactive data visualization allows for both detailed micro information and aggregated macro information displayed in a single chart. Animated transition adds extra visual impact that describes how system transits from one state to another. When applied to healthcare system, interactive visualization techniques are useful in areas such as information integration, flow or trajectory presentation and location related visualization, etc. One area both techniques intersect is location analysis. In this paper, real life case studies will be given to illustrate how these two techniques, when combined together, help in solving quantitative or qualitative location related problem, visualizing geographical information and accelerating decision making procedures.

Download Full-text