Visual Analytic Tools and Techniques in Population Health and Health Services Research: Scoping Review

Abstract

Background Visual analytics (VA) promotes the understanding of data with visual, interactive techniques, using analytic and visual engines. The analytic engine includes automated techniques, whereas common visual outputs include flow maps and spatiotemporal hot spots. Objective This scoping review aims to address a gap in the literature, with the specific objective to synthesize literature on the use of VA tools, techniques, and frameworks in interrelated health care areas of population health and health services research (HSR). Methods Using the 2018 PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, the review focuses on peer-reviewed journal articles and full conference papers from 2005 to March 2019. Two researchers were involved at each step, and another researcher arbitrated disagreements. A comprehensive abstraction platform captured data from diverse bodies of the literature, primarily from the computer and health sciences. Results After screening 11,310 articles, findings from 55 articles were synthesized under the major headings of visual and analytic engines, visual presentation characteristics, tools used and their capabilities, application to health care areas, data types and sources, VA frameworks, frameworks used for VA applications, availability and innovation, and co-design initiatives. We found extensive application of VA methods used in areas of epidemiology, surveillance and modeling, health services access, use, and cost analyses. All articles included a distinct analytic and visualization engine, with varying levels of detail provided. Most tools were prototypes, with 5 in use at the time of publication. Seven articles presented methodological frameworks. Toward consistent reporting, we present a checklist, with an expanded definition for VA applications in health care, to assist researchers in sharing research for greater replicability. We summarized the results in a Tableau dashboard. Conclusions With the increasing availability and generation of big health care data, VA is a fast-growing method applied to complex health care data. What makes VA innovative is its capability to process multiple, varied data sources to demonstrate trends and patterns for exploratory analysis, leading to knowledge generation and decision support. This is the first review to bridge a critical gap in the literature on VA methods applied to the areas of population health and HSR, which further indicates possible avenues for the adoption of these methods in the future. This review is especially important in the wake of COVID-19 surveillance and response initiatives, where many VA products have taken center stage. International Registered Report Identifier (IRRID) RR2-10.2196/14019

Interactive Visualization Applications in Population Health and Health Services Research: Systematic Scoping Review

“…Various methodologies outlining effective design requirements and experiences from stakeholders to create new products and solutions have been explored [ 102 - 104 ]. For our scoping review, we opted to use the term co-design , which is more commonly used in health care literature, as opposed to design thinking and other related terms [ 13 ].…”

“…In this review, we found that at least two-thirds of the applications involved co-design approaches, involving stakeholders for developing interactive visualization applications. This was in contrast to a smaller proportion of co-designed VA applications (18%), which were mostly prototypes developed by and for data scientists at academic centers [ 13 ]. In line with this finding, more than half of the interactive visualization applications were developed in-house within health care organizations.…”

“…Both fields involve the analysis of large secondary data sources such as clinical databases, administrative data sets, and electronic medical records (EMRs) [ 10 - 12 ]. In a prior review, we summarized evidence on VA applications in these interrelated fields of health care [ 13 ]; this review complements it by reviewing the evidence on interactive visualization applications in population health and HSR.…”

“…This companion review is our second synthesis of literature on visualization and analytics tools, techniques, and approaches in population health and HSR. Our first publication focused on VA methods in these areas, where we offered an updated definition of VA in health care as “an approach, method, or application for analytic reasoning, exploration, knowledge discovery, and sense making of complex data, using one or more interactive visual interfaces, employing analytic and visual engines” [ 13 ]. As part of VA applications, analytic engines involve advanced machine learning, database querying, and manipulation.…”

Explaining artificial intelligence with visual analytics in healthcare

“…Despite the diverging terminology, a lot of interesting work has been presented in different healthcare areas, for example, population health services (Chishtie et al, 2020), prevention of disease outbreaks (Preim & Lawonn, 2020), and cancer-related genomics (Qu et al, 2019). In biomedics, Sturm et al (2015) categorized existing work on interactivity level versus analysis type and visualization technique, and Turkay et al (2014) classified visual analysis tools by their analytical task and integration of computational methods.…”