A quantitative study examining infographic assessment guidelines for undergraduate nursing students with specific learning difficulties (SpLDs).

This research investigates the perceived clarity and usefulness of infographic versus traditional text-based assessment guidelines among undergraduate nursing students with and without specific learning difficulties (SpLDs). Through quantitative analysis, the study reveals that undergraduate nursing students with SpLDs significantly prefer infographics over text-based guidelines, both in terms of clarity and usefulness (p < .001). Interestingly, there were no statistically significant differences in the perceptions of students without SpLDs. These findings suggest that the use of infographics as a tool for presenting assessment guidelines could contribute to more inclusive educational practices. The research further highlights the potential of infographics to not only make complex information more accessible but also to cater to diverse learning needs. As higher education institutions strive to be more inclusive, adapting assessment guidelines to suit the varied learning styles and cognitive needs of all students, particularly those with SpLDs, becomes increasingly important. This paper provides initial evidence to support the adoption of infographic-based assessment guidelines as a step towards achieving this goal.

Community engagement in the development of health-related data visualizations: a scoping review.

OBJECTIVE: This scoping review aims to address a gap in the literature on community engagement in developing data visualizations intended to improve population health. The review objectives are to: (1) synthesize literature on the types of community engagement activities conducted by researchers working with community partners and (2) characterize instances of "creative data literacy" within data visualizations developed in community-researcher partnerships. 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 from 2010 to 2022 in PubMed, Web of Science, and Google Scholar. A community engagement tool was applied to the studies by independent reviewers to classify levels of community engagement, social determinants, and vulnerable populations. RESULTS: Twenty-seven articles were included in the scoping review. Twelve articles worked with vulnerable populations. Four articles attempted to alleviate barriers to representation in their respective studies, with addressing language barriers being the most prevalent approach. Thirteen articles considered social determinants of health. Sixteen studies engaged in iterative approaches with intended users when developing the visualization or tool. DISCUSSION: Only a few significant examples of creative data literacy are incorporated in the studies. We recommend a specific focus on engaging intended users at every step of the development process, addressing language and cultural differences, and empowering intended users as data storytellers. CONCLUSIONS: There is room for deeper and more meaningful community involvement in the development of health-related data visualizations geared towards them.

SuperMap-Based Research on the Spread Situation and Visual Monitoring Platform of Major Health Events.

To present information on infectious diseases caused by viruses clearly and track the changes of data in real-time, data visualization can be used preferentially considering that it can identify problems behind data accurately. In this paper, based on the SuperMap Online platform and Tianditu, a national platform for common geospatial information services, a risk level map of infectious diseases distribution area is made by Web GIS and cartography. Meanwhile, the platform plays an important role in information collection, management, analysis, prevention and control, and release of measures when a major health event spreads. The method shows many advantages, such as various visualization means, ease to be published and shared, simple operation, and programming realization, which may be taken as technical references for solving the same type of visualization application problems. The research also facilitates the data visualization and monitoring of the spread of infectious diseases in major health events, and can effectively provide services for monitoring, decision-making, dispatching, and handling the spread of infectious diseases.

[Application of Data Analysis and Data Visualization in Medical Equipment: Take Infusion Pump as Example].

OBJECTIVE: To combine data analysis and data visualization with medical devices, provide a set of data analysis and data visualization solutions. This solutions can deeply excavate the data of the whole life cycle of medical equipment, and then play a guiding role in business. METHODS: With the help of mature tools in the Internet field, YIYI and YOUSHU, we can quickly complete data collection and rich visualization effects, and introduce the concept of data analysis to deeply mine data. RESULTS: Taking the maintenance data of infusion pump as an example, the data collection is completed through YIYI, and the maintenance system is built on YOUSHU. CONCLUSIONS: The maintenance system of infusion pump system is simple and clear, with good visualization effect. It can quickly analyze maintenance failures, reduce maintenance times and maintenance costs, ensure the safety of the equipment. Moreover, the system can be easily transferred to other medical equipment, and can carry on the whole life cycle data research.

Origami plot: a novel multivariate data visualization tool that improves radar chart.

OBJECTIVES: We propose the origami plot, which maintains the original functionality of a radar chart and avoids potential misuse of its connected regions, with newly added features to better assist multicriteria decision-making. STUDY DESIGN AND SETTING: Built upon a radar chart, the origami plot adds additional auxiliary axes and points such that the area of the connected region of all dots is invariant to the ordering of axes. As such, it enables ranking different individuals by the overall performance for multicriteria decision-making while maintaining the intuitive visual appeal of the radar chart. We develop extensions of the origami plot, including the weighted origami plot, which allows reweighting of each attribute to define the overall performance, and the pairwise origami plot, which highlights comparisons between two individuals. RESULTS: We illustrate the different versions of origami plots using the hospital compare database developed by the Centers for Medicare & Medicaid Services (CMS). The plot shows individual hospital's performance on mortality, readmission, complication, and infection, as well as patient experience and timely and effective care, as well as their overall performance across these metrics. The weighted origami plot allows weighing the attributes differently when some are more important than others. We illustrate the potential use of the pairwise origami plot in electronic health records (EHR) system to monitor five clinical measures (body mass index [BMI]), fasting glucose level, blood pressure, triglycerides, and low-density lipoprotein ([LDL] cholesterol) of a patient across multiple hospital visits. CONCLUSION: The origami plot is a useful visualization tool to assist multicriteria decision making. It improves radar charts by avoiding potential misuse of the connected regions. It has several new features and allows flexible customization.

Design, Usability, and Acceptability of a Needs-Based, Automated Dashboard to Provide Individualized Patient-Care Data to Pediatric Residents.

BACKGROUND AND OBJECTIVES: Pediatric residency programs are required by the Accreditation Council for Graduate Medical Education to provide residents with patient-care and quality metrics to facilitate self-identification of knowledge gaps to prioritize improvement efforts. Trainees are interested in receiving this data, but this is a largely unmet need. Our objectives were to (1) design and implement an automated dashboard providing individualized data to residents, and (2) examine the usability and acceptability of the dashboard among pediatric residents. METHODS: We developed a dashboard containing individualized patient-care data for pediatric residents with emphasis on needs identified by residents and residency leadership. To build the dashboard, we created a connection from a clinical data warehouse to data visualization software. We allocated patients to residents based on note authorship and created individualized reports with masked identities that preserved anonymity. After development, we conducted usability and acceptability testing with 11 resident users utilizing a mixed-methods approach. We conducted interviews and anonymous surveys which evaluated technical features of the application, ease of use, as well as users' attitudes toward using the dashboard. Categories and subcategories from usability interviews were identified using a content analysis approach. RESULTS: Our dashboard provides individualized metrics including diagnosis exposure counts, procedure counts, efficiency metrics, and quality metrics. In content analysis of the usability testing interviews, the most frequently mentioned use of the dashboard was to aid a resident's self-directed learning. Residents had few concerns about the dashboard overall. Surveyed residents found the dashboard easy to use and expressed intention to use the dashboard in the future. CONCLUSION: Automated dashboards may be a solution to the current challenge of providing trainees with individualized patient-care data. Our usability testing revealed that residents found our dashboard to be useful and that they intended to use this tool to facilitate development of self-directed learning plans.

The Drinking Water Tool: A Community-Driven Data Visualization Tool for Policy Implementation.

The Drinking Water Tool (DWT) is a community-driven online tool that provides diverse users with information about drinking water sources and threats to drinking water quality and access due to drought. Development of the DWT was guided by the Community Water Center (CWC) as part of the Water Equity Science Shop (WESS), a research partnership integrating elements of community-based participatory research and the European Science Shop model. The WESS engages in scientific projects that inform policy change, advance water justice, and reduce cumulative exposure and disproportionate health burdens among impacted communities in California. WESS researchers conducted qualitative analysis of 15 stakeholder interviews regarding the DWT, including iterative feedback and the stakeholder consultation process as well as stakeholder perceptions of the tool's impact on California water policy, organizing, and research. Results indicate that the DWT and the stakeholder engagement process which developed it were effective in influencing policy priorities and in promoting interagency coordination at multiple levels to address water equity challenges and their disproportionate burdens, particularly among rural and low socioeconomic status areas and communities of color.

A personalized biomedical risk assessment infographic for people who smoke with COPD: a qualitative study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) causes 3 million deaths each year, yet 38% of COPD patients continue to smoke. Despite proof of effectiveness and universal guideline recommendations, smoking cessation interventions are underused in practice. We sought to develop an infographic featuring personalized biomedical risk assessment through future lung function decline prediction (with vs without ongoing smoking) to both prompt and enhance clinician delivery of smoking cessation advice and pharmacotherapy, and augment patient motivation to quit. METHODS: We recruited patients with COPD and pulmonologists from a quaternary care center in Toronto, Canada. Infographic prototype content and design was based on best evidence. After face validation, the prototype was optimized through rapid-cycle design. Each cycle consisted of: (1) infographic testing in a moderated focus group and a clinician interview (recorded/transcribed) (with questionnaire completion); (2) review of transcripts for emergent/critical findings; and (3) infographic modifications to address findings (until no new critical findings emerged). We performed iterative transcript analysis after each cycle and a summative qualitative transcript analysis with quantitative (descriptive) questionnaire analysis. RESULTS: Stopping criteria were met after 4 cycles, involving 20 patients (58% male) and 4 pulmonologists (50% male). The following qualitative themes emerged: Tool content (infographic content preferences); Tool Design (infographic design preferences); Advantages of Infographic Messaging (benefits of an infographic over other approaches); Impact of Tool on Determinants of Smoking Cessation Advice Delivery (impact on barriers and enablers to delivery of smoking cessation advice in practice); and Barriers and Enablers to Quitting (impact on barriers and enablers to quitting). Patient Likert scale ratings of infographic content and format/usability were highly positive, with improvements in scores for 20/21 questions through the design process. Providers scored the infographic at 77.8% ("superior") on the Suitability Assessment of Materials questionnaire. CONCLUSIONS: We developed a user preference-based personalized biomedical risk assessment infographic to drive smoking cessation in patients with COPD. Our findings suggest that this tool could impact behavioural determinants of provider smoking-cessation advice delivery, while increasing patient quit motivation. Impacts of the tool on provider care, patient motivation to quit, and smoking cessation success should now be evaluated in real-world settings.

Developing Dashboards to Address Children's Health Disparities in Ohio.

OBJECTIVES: Social determinants of health (SDoH) can be measured at the geographic level to convey information about neighborhood deprivation. The Ohio Children's Opportunity Index (OCOI) is a composite area-level opportunity index comprised of eight health domains. Our research team has documented the design, development, and use cases of a dashboard solution to visualize OCOI. METHODS: The OCOI is a multidomain index spanning the following eight domains: (1) family stability, (2) infant health, (3) children's health, (4) access, (5) education, (6) housing, (7) environment, and (8) criminal justice. Information on these eight domains is derived from the American Community Survey and other administrative datasets. Our team used the Tableau Desktop visualization software and applied a user-centered design approach to developing the two OCOI dashboards-main OCOI dashboard and OCOI-race dashboard. We also performed convergence analysis to visualize the census tracts where different health indicators simultaneously exist at their worst levels. RESULTS: The OCOI dashboard has multiple, interactive components as follows: a choropleth map of Ohio displaying OCOI scores for a specific census tract, graphs presenting OCOI or domain scores to compare relative positions for tracts, and a sortable table to visualize scores for specific county and census tracts. A case study using the two dashboards for convergence analysis revealed census tracts in neighborhoods with low infant health scores and a high proportion of minority population. CONCLUSION: The OCOI dashboards could assist health care leaders in making decisions that enhance health care delivery and policy decision-making regarding children's health particularly in areas where multiple health indicators exist at their worst levels.

Assessing the impact of a gynaecomastia assessment and treatment infographic in primary care in Greater Manchester.

INTRODUCTION: Men with gynaecomastia are routinely referred to breast clinics, yet most do not require breast surgical intervention. The aim of this study was to assess the impact of a novel point-of-care gynaecomastia decision infographic in primary care on the assessment, management and referral practices to tertiary breast surgical services. METHODS: A study was carried out of male patient referrals from primary care in Greater Manchester to a tertiary breast centre between January and March in 2018-2020. Referral patterns were compared before and after the infographic went live in general practices in Greater Manchester in January 2020. Data were collected for gynaecomastia referrals, including aetiology, investigation and management. RESULTS: In total, 394 men were referred to a tertiary breast centre from 163 general practices, of which 271 (68.8%) had a diagnosis of gynaecomastia. Use of the decision infographic by primary healthcare providers was associated with a decrease in male breast referrals with gynaecomastia (79.6% to 62.0%). Fewer gynaecomastia patients were referred with a benign physiological or drug-related cause after implementation of the infographic (52.2% vs 41.8%). Only 10 (3.7%) patients with gynaecomastia underwent breast surgery during the study period. CONCLUSION: Implementation of a gynaecomastia infographic in primary care in Manchester was associated with a reduction in gynaecomastia referrals to secondary care. We hypothesise that implementation of the infographic into primary care nationally may potentially translate to hundreds of patients receiving more specialty-appropriate referrals, improving overall management of gynaecomastia. Further study is warranted to test this hypothesis.

Well-being and well-becoming through the life-course in public health economics research and policy: A new infographic.

Background: The term "well-becoming" is not new, but is not routinely used in our everyday language or in research in public health economics. It has been applied in early years research. Well-becoming can be thought of as our multitude of life-journeys toward meaning and purposefulness. Objective: To develop a new infographic in the spirit of the Dahlgren and Whitehead rainbow infographic of social determinants of health. The purpose being to redefine well-being as a process of growth through life, articulated as well-becoming. Methods: A rapid review of life-course stage appropriate models of well-being was undertaken with stages of the life-course as defined as: preconception and birth; early years; adolescence; working, parenting and caring; older age, and death. Infographics in this area were identified and the information above was used to design a new infographic with the concept of well-being and well-becoming at its center. Results: A new infographic reflecting an underlying concept of "the wheel of life" is presented. It shows movement through the life-course at its center, with concentric rings summarizing personal, local, and national and global factors that have an impact on well-being and well-becoming of individuals through the life-course. Of note, is the inclusion of death, which is a topic often avoided. Prepared during 2021-22, the infographic reflects the role of pandemic and war within the national and global ring of influential factors. I reflect on three ways in which health economists are currently using a life-course approach and the concept of well-becoming in the economic evaluation of individual programs and at a population level of government policy. Conclusion: Moving from solely focusing on a concept of well-being to a concept of well-being and well-becoming acknowledges the influence that socioeconomic and other conditions in a particular life-course stage have on subsequent life-course stages, and the cost-effectiveness of intervening across the life-course.

Understanding Women's Cardiovascular Health Using MyStrengths+MyHealth: A Patient-Generated Data Visualization Study of Strengths, Challenges, and Needs Differences.

PURPOSE: The purpose of this data visualization study was to identify patterns in patient-generated health data (PGHD) of women with and without Circulation signs or symptoms. Specific aims were to (a) visualize and interpret relationships among strengths, challenges, and needs of women with and without Circulation signs or symptoms; (b) generate hypotheses based on these patterns; and (c) test hypotheses generated in Aim 2. DESIGN: The design of this visualization study was retrospective, observational, case controlled, and exploratory. METHODS: We used existing de-identified PGHD from a mobile health application, MyStrengths+MyHealth (N = 383). From the data, women identified with Circulation signs or symptoms (n = 80) were matched to an equal number of women without Circulation signs or symptoms. Data were analyzed using data visualization techniques and descriptive and inferential statistics. FINDINGS: Based on the patterns, we generated nine hypotheses, of which four were supported. Visualization and interpretation of relationships revealed that women without Circulation signs or symptoms compared to women with Circulation signs or symptoms had more strengths, challenges, and needs-specifically, strengths in connecting; challenges in emotions, vision, and health care; and needs related to info and guidance. CONCLUSIONS: This study suggests that visualization of whole-person health including strengths, challenges, and needs enabled detection and testing of new health patterns. Some findings were unexpected, and perspectives of the patient would not have been detected without PGHD, which should be valued and sought. Such data may support improved clinical interactions as well as policies for standardization of PGHD as sharable and comparable data across clinical and community settings. CLINICAL RELEVANCE: Standardization of patient-generated whole-person health data enabled clinically relevant research that included the patients' perspective.

Using causal forests to assess heterogeneity in cost-effectiveness analysis.

We develop a method for data-driven estimation and analysis of heterogeneity in cost-effectiveness analyses (CEA) with experimental or observational individual-level data. Our implementation uses causal forests and cross-fitted augmented inverse probability weighted learning to estimate heterogeneity in incremental outcomes, costs and net monetary benefits, as well as other parameters relevant to CEA. We also show how the results can be visualized in relevant ways for the analysis of heterogeneity in CEA, such as using individual-level cost effectiveness planes. Using a simulated dataset and an R package implementing our methods, we show how the approach can be used to estimate the average cost-effectiveness in the entire sample or in subpopulations, explore and analyze the heterogeneity in incremental outcomes, costs and net monetary benefits (and their determinants), and learn policy rules from the data.