Integrating Diversity, Equity, Inclusion, and Accessibility into a Data Storytelling Model for Health Informatics Education

Abstract

Background  Health informatics education is pivotal in integrating diversity, equity, inclusion, and accessibility (DEIA) principles into curricula and leveraging data with equity considerations. Integrating clinically driven data with other datasets is crucial to comprehensive understanding of patient care demographics, experiences, and outcomes to create equity-minded data storytelling. Publicly available Healthy People 2030 (HP2030) resources complement academic electronic health records, supporting tailored learning activities in informatics education to enhance educational utility through a DEIA lens.

Objectives  This case report describes the expansion of an existing diversity, equity, and inclusion (DEI) checklist to an updated DEIA checklist for preparing future informaticians to collect and critically evaluate DEIA features using this checklist in creating equity-minded data storytelling.

Methods  The DEI-Oriented Data Storytelling Model and the HP2030 framework were utilized to develop the DEIA checklist. We employed an informal cognitive walkthrough to expand the DEIA checklist and evaluate the DEIA measures or characteristics within datasets from the HP2030 social determinants of health (SDOH) five topics using this checklist.

Results  We reviewed 76 available SDOH-related datasets and added six measures to “demographics” and seven to “skills, abilities, and accessibility” of the DEIA checklist. Our evaluation of the DEIA checklist verified HP2030's inclusion of all measures, except “religions/beliefs.” All DEIA measures were linked to equity and accessibility, one in inclusion, and the inclusion of three characteristics comprising the category “language” and six characteristics comprising the category “images.”

Conclusion  Results highlighted the accessibility and comprehensiveness of HP2030 demographic data resources, considering SDOH factors and promoting inclusive data representation to address health disparities. The DEIA checklist provides a structured tool in facilitating unbiased data collection and visualization of SDOH-related data through an equity-informed lens. Integrating an equity-minded data storytelling with frameworks like HP2030 enriches health informatics education, broadens students' understanding of health disparities, and supports evidence-based interventions for improved health outcomes.

Background and Significance

Mindful consideration of potential biases when interpreting data are essential. 1 Health informatics education is pivotal in equipping the next generation of informaticians to mitigate biases by teaching students to incorporate diversity, equity, inclusion, and accessibility (DEIA) principles when collecting and visualizing data. Systematic tools incorporating DEIA principles can facilitate more equitable and unbiased data analysis and interpretation. 2

Diversity encompasses myriad human characteristics crucial for identifying health care disparities. 3 Health equity aims to achieve fair health outcomes for all by eliminating systemic barriers. 4 Inclusion refers to creating health care environments where individuals and groups feel a sense of belonging and uniqueness and embracing diverse health care experiences, perceptions, and feelings. 5 Accessibility ensures that all individuals, regardless of ability or experience, have equal access to opportunities, resources, and health care. 5 Valuing these DEIA principles is instrumental to informatics education as it helps students collect and visualize data comprehensively and representatively to effectively communicate actionable insights through equity-minded data storytelling. 2

Despite the importance of these principles, available academic electronic health record (EHR) platforms—modified versions of clinical information systems tailored to suit educational needs—often lack comprehensive DEIA features to assist students in exploring and understanding diverse and inclusive datasets. 2 6 To bridge this gap and adequately teach the importance of equity-minded data collection and visualization, informatics educators should consider using additional data platforms with sufficient DEIA-related data and implementing structured, equity-minded tools, or checklists.

Cognitive Walkthrough Overview

A cognitive walkthrough is a formal, structured usability assessment. An informal cognitive walkthrough (ICW) is a less structured, flexible usability assessment that involves (1) a brief exploration of a user interface (UI) to understand how users interact with and navigate a platform and (2) the identification of potential usability issues, facilitating the evaluator in providing content suggestions to enhance the UI. 7

Data Storytelling Model and Diversity, Equity, And Inclusion Checklist Overview

Gao's diversity, equity, and inclusion (DEI)-oriented data storytelling model comprising four components (data characters, datasetting, data plot, and data resolution) informed the creation of the original DEI checklist (hereafter, DEI checklist) with two components (DEI-informed data collection and DEI-enhanced data visualization). 2 This checklist provides a systematic approach to integrating equity-minded principles. In alignment with the storytelling framework, both “data characters” and “data setting” relate to data collection of the checklist, setting the stage for data characters or unique data points within a health care context or setting in data storytelling. Data storytelling progresses with “data plot” of the data visualization component where analytics chart the storyline and visualizations illustrate it, leading to actionable insights for decision-making. The data collection component comprises three categories and related data points/measures (hereafter, measures), whereas the data visualization component comprises two categories and associated characteristics. The equity-minded storytelling model and DEI checklist are valuable to informatics curricula, as they ensure students to be well-equipped to diminish biases when collecting, visualizing, and addressing biases in data storytelling.

Healthy People 2030 Overview

The DEI checklist aligns with the Healthy People 2030 (HP2030) initiative to promote health equity through comprehensive strategies and resources. The vision of HP2030 is to enhance the health and well-being of all by eliminating health disparities, achieving health equity, and promoting healthy lifestyles and behaviors. 8 The initiative encourages leaders to improve public health through comprehensive strategies and measurable objectives.

Utilizing clinical and public health-facing data provides a comprehensive view of patient health and well-being. The HP2030 initiative includes five measurable objectives: health conditions, health behaviors, populations, settings and systems, and social determinants of health (SDOH). 9 The SDOH objective is most related to DEIA principles, as its five topics (economic stability; education access and quality; health care access and quality; neighborhood and built environment; and social and community context) directly address the underlying systemic factors influencing health equity and outcomes. 9

The HP2030 Web site is a publicly accessible electronic data platform featuring nationally representative and high-quality data. 10 The Web site includes extensive equity-minded resources and tools aligning with the evolving state of public health, health informatics science, and DEIA principles. The Web site's SDOH-related datasets enable users to explore and understand demographic characteristics and other health-related factors. 11 Thus, the HP2030 Web site is an ideal platform for health informatics educators interested in incorporating DEIA principles into curricula.

Objectives

The goal of this case report was to advance health informatics education by using an ICW of the HP2030 Web site to build upon Gao's data storytelling model by expanding the DEI checklist 2 to the DEIA checklist. We aimed to (1) update the data collection component of the DEI checklist by incorporating new accessibility-related features and (2) evaluate all measures and characteristics of the DEIA checklist.

Methods

To ensure a rigorous approach and reliability of all new measures in the data collection component of the checklist, we used two evaluators (G.G. and C.L.M.), both informatics educators. Specifically, to update the “demographics” measures in data collection, one evaluator examined DEIA-related data elements ( n  = 29) among available datasets ( n  = 76) within the five SDOH topics and related objectives ( n  = 95; Table 1 ). 9 See Supplementary Appendices A and B for a detailed list of HP2030 SDOH-related topics and objectives.

Table 1. Summary of healthy people 2030 web site's topics, objectives, and datasets ^a .

SDOH-related topics	HP2030 topics	HP2030-related objectives ( n )	SDOH-related datasetsa ( n )
Economic stability	General	4	4
	Health behaviors	2	2
	Health conditions	1	1
	Settings and systems	2	1
Education access and quality	Populations	9	3
	Settings and systems	1	1
Health care access and quality	General	2	2
	Health behaviors	6	5
	Health conditions	21	17
	Populations	3	2
	Settings and systems	15	7
Neighborhood and built environment	General	3	2
	Health behaviors	7	6
	Health conditions	9	5
	Populations	1	1
	Settings and systems	9	8
Social and community context	General	3	2
	Health behaviors	1	1
	Populations	7	5
	Settings and systems	2	1
Total		95	76

Abbreviations: HP2030, Healthy People 2030; SDOH, social determinants of health.

^aThere were 29 diversity, equity, inclusion, and accessibility-related data elements among the 76 datasets.

To update the “skills and abilities” category and measures, “accessibility” was added to the category, and the same evaluator explored accessibility-related measures found within the HP2030 Web site's mission and vision 8 and other relevant pages. A second evaluator double-checked the additional accessibility-related measures. Both evaluators agreed on the new and existing categories and measures of data collection of the DEIA checklist. Given its subjective features, we did not update the “inclusion” category of data collection in this iteration.

Next, to evaluate all features of the DEIA checklist, we evaluated each of the two components of the checklist. To assess all measures on the DEIA data collection, the first evaluator checked their presence or absence across the available SDOH datasets. To assess the culturally relevant aspects of the existing data visualization component, the first evaluator examined the inclusion of the data visualization categories and respective characteristics across the same datasets. We only used the first evaluator for the assessment since, besides being an informatics educator, they created the original checklist and have expertise in data visualization.

Results

The 29 data elements across SDOH-related datasets ( Fig. 1 ) informed the addition of six new measures (education, employment, health insurance, income, obesity status, and sex) in the “demographics” category of data collection of the DEIA checklist ( Table 2 ). The accessibility-related content across the various pages of the Web site informed seven new accessibility-related measures (access, food security, health literacy, neighborhood, physical activity, special health care needs, and transportation”) in the category of “skills, abilities, and accessibility” of the checklist. See Supplementary Appendix C for the DEIA checklist.

Fig. 1.

Data elements of Demographic Group in Healthy People 2030 social determinants of health datasets.

Table 2. Data collection features of diversity, equity, and inclusion checklist and diversity, equity, inclusion, and accessibility checklist.

DEI checklist		DEIA checklist
DEI-informed data collection		DEIA-informed data collection
Category	Data point/measure	Category	Data point/measure
Demographics	Address/geographic location	Demographics	Address/geographic location
	Age		Age
	Ethnicity		Ethnicity
	Gender identity		Gender identity
	Language preference		Language preference
	Race		Race
	Religious/beliefs		Religious/beliefs
	Sexual orientation		Sexual orientation
	Veteran status		Veteran status
			a Education
			a Employment
			a Health insurance
			a Income
			a Obesity status
			a Sex
Skills and abilities	Disability status	Skills, abilities, and accessibility	Disability status
			a Access
			a Food security
			a Health literacy
			a Neighborhood
			a Physical activity
			a Special health care needs
			a Transportation

Abbreviations: DEI, diversity, equity, and inclusion; DEIA, diversity, equity, inclusion, and accessibility.

^aNew data points/measures.

The evaluation of all measures of the DEIA data collection component verified the inclusion of all measures except “religion/beliefs.” All DEIA measures were linked to equity and accessibility, one in inclusion. The evaluation of all characteristics of the existing data visualization component verified the inclusion of three (labels, texts, and titles) of the five characteristics comprising the category “language” and six (charts, colors, diagrams, figures, icons, tables) of the eight characteristics comprising the category “images” ( Table 2 ).

The available HP2030 SDOH datasets segmented data elements throughout different demographic groups arranged alphabetically ( Table 3 ). Labels accompanied figures and graphs. Icons or notations were used to illustrate and enhance clarity. Interactive figures were displayed based on filtered selections including timeframe, using neutral colors with predominantly white backgrounds contrasted with words, line, or bar graphs in black and gray. Bar graphs displayed neutral colors or blue tones to facilitate additional comparisons based on selected scenarios.

Table 3. Appraisal of healthy people 2030 web site using the diversity, equity, inclusion, and accessibility checklist.

DEIA-informed data collection
Category	Data point/measure	Yes	No	NA	Other
Demographics	Address/geographic location	✓
	Age	✓
	Education	✓
	Employment	✓
	Ethnicity	✓
	Gender identity	✓
	Health insurance status	✓
	Income	✓
	Language preference	✓
	Obesity status	✓
	Race	✓
	Religion/beliefs		✓
	Sex	✓
	Sexual orientation	✓
	Veteran status	✓
Skills, abilities, and accessibility	Access	✓
	Disability status	✓
	Food security	✓
	Health literacy	✓
	Neighborhood	✓
	Physical activity	✓
	Special health care needs	✓
	Transportation	✓
Inclusion	Experiences	✓
	Feelings		✓
	Perceptions		✓
DEIA-enhanced data visualization
Category	Characteristics	Yes	No	NA	Other
Language	Dashboards		✓
	Labels	✓
	Storyboards		✓
	Texts	✓
	Titles	✓
Images	Charts	✓
	Colors	✓
	Dashboards		✓
	Diagrams	✓
	Figures	✓
	Icons	✓
	Storyboards		✓
	Tables	✓

Abbreviations: DEIA, diversity, equity, inclusion, and accessibility; NA, not applicable.

Clusion, and accessibility; NA, not applicable.

Discussion

This case report advances health informatics education by facilitating more equitable data collection and visualization. Using an equity-minded data storytelling model and an ICW, we updated the data collection component of the DEI checklist to include accessibility-related features in the DEIA checklist. We also evaluated the measures and characteristics of the DEIA checklist by checking their presence on the HP2030 Web site.

The HP2030 Web site includes DEIA-related data elements and content, offering a holistic view of patient characteristics and outcomes. Access to representative, high-quality data sources like HP2030 enhances equity-minded data storytelling and aligns with the National Institute of Health's DEIA Plan 12 and the American Medical Informatics Association's DEI initiative. 13 Promoting equitable and unbiased data collection and visualization fosters informed and equitable data use.

Equity-minded data are being incorporated into clinical tools. 14 Electronic platforms with diverse data sources improve equity-minded skills among students and advance DEIA-informed science, given the implications of big data in research. Once collected and visualized, DEIA-informed big data are essential in advancing data-driven policies that are diverse, equitable, inclusive, and accessible. The DEIA checklist assists health informatics educators in ensuring data representation aligning with equity-minded principles in guiding students creating equity-minded data storytelling by incorporating essential DEIA elements for data collection and visualization. 2 DEIA data foster more equitable data analysis and decision-making among policymakers, informaticians, researchers, and patients. 15

The fact that there are 95 objectives described across the SDOH five topics highlights the breadth of topics. The corresponding 76 datasets demonstrate a concerted effort to provide comprehensive DEIA-informed publicly available data. The diverse demographic data sources show inclusive data representation of SDOH factors in addressing health disparities, for example, the inclusion of various age groups, ethnicities, socioeconomic statuses, and geographic locations. Responsible data collection ensures accurate, inclusive data representation and fosters equity-minded data analyses and visualizations. 15

The identification of DEIA features across diverse data underscores the importance of considering factors such as race, ethnicity, gender, and socioeconomic status in health interventions and policies. However, given that certain data elements, such as “religion/beliefs,” are not commonly represented may warrant further exploration to ensure a comprehensive understanding of social determinants. Underrepresentation of these elements limits our understanding of how diverse social factors may impact health behaviors, outcomes, and patient–provider interactions. Future work should focus on integrating these elements more thoroughly and developing standardized measures that account for diverse cultural and belief systems.

The ability to filter HP2030 data by demographic groups or time periods enables tailored analysis of diverse population subsets or temporal trends. It also captures the complexity of social determinants and their impact on health outcomes. To devise meaningful measures for informatics education, a systematic approach should be adopted to identify key health indicators or modifiable determinants of health and methods for comparing these indicators across different social strata. 11 16 Such a systematic approach can be integrated into academic informatics education that uses health or health-related indicators to develop data-related learning activities. For example, to identify trends, evaluate the impact of health interventions and propose data-driven solutions through a DEIA lens, scenario-based informatics learning activities incorporating DEIA-informed platforms, like HP2030, can be built into curricula where students work with real-world health datasets, reinforcing DEIA principles and equipping students with practical data analysis and interpretation skills.

Even though the alphabetical arrangement of demographic data enhances accessibility, purposeful ordering, and freedom from biases in naming, 15 there is a need to ensure that this data arrangement remains unbiased and does not inadvertently prioritize certain factors over others. Interactive figures based on filter selections enable users to visualize trends and patterns and facilitate a broader data view.

Using neutral colors and contrasting visual elements in an interactive data display enhances clarity and accessibility for users. Intuitive design principles, such as color contrast and iconography, make data more engaging and understandable. This approach is essential for effectively conveying complex information and promoting user engagement with the data. While neutral colors and contrasting visual elements enhance clarity and accessibility, there is a risk of misinterpretation or oversimplification of complex data. Providing clear explanations and context alongside visualizations could mitigate this risk.

This case report has certain limitations. While the HP2030 framework is comprehensive, it may not encompass all relevant DEIA considerations. Exploring additional frameworks or datasets could provide a more holistic approach to understanding and addressing health disparities and promoting health equity. Future research should focus on integrating the DEIA checklist with datasets beyond HP2030 to encourage the creation of equity-minded data storytelling. Developing technological tools that incorporate the DEIA checklist will facilitate its implementation in academic EHRs and automate the evaluation of datasets for DEIA features. These approaches provide opportunities to educate informatics students on the implications of DEIA-oriented data analysis and storytelling and influence health care delivery and policy decisions.

Conclusion

The DEIA checklist is a comprehensive tool for evaluating DEIA features in datasets. This checklist facilitates accessing, analyzing, and interpreting unbiased data collection and the visualization through an equity-informed lens. By prioritizing DEIA principles and unbiased data presentation and interpretation, equity-minded data storytelling can inform evidence-based interventions and policies to address health inequities and improve clinical and population health outcomes. Integrating DEIA into data storytelling models enhances academic informatics education, broadens students' understanding of health disparities, and promotes interventions for improved health outcomes for all.

Clinical Relevance Statement

Incorporating DEIA principles into health informatics education is critical for equipping health care professionals to effectively address health disparities and promote equitable patient care practice and outcomes. By applying an equity-minded data storytelling model and DEIA checklist to informatics education, informatics students can develop data storytelling perspectives and skills using a DEIA lens to gain insights into social determinants of health and tailor interventions to improve equitable patient and population health outcomes.

Multiple-Choice Questions

1. What data collection components are included in the DEIA-oriented data storytelling model in developing DEIA-informed data storytelling?

   1. Data character and data resolution

   2. Datasetting and data resolution

   3. Datasetting and data plot

   4. Data character and datasetting

   Correct Answer : The correct answer is option d. According to the referred model, data characters and datasettings lay the groundwork for DEIA informed data collection.

2. What HP2030 data measures were incorporated into the DEIA checklist to evaluate DEIA features in data collection for a DEIA-oriented data storytelling?

   1. Healthy equity, health literacy, and social determinants of health

   2. Healthy, health literacy, and social determinants of health

   3. Healthy equity, well-being, and social determinants of health

   4. Healthy, well-being, and health literacy

   Correct Answer : The correct answer is option a. The DEIA checklist incorporated data measures of healthy equity, health literacy, and social determinants of health in Healthy People 2030.

Funding Statement

Funding The project was supported by the Veterans Affairs Quality Scholars (VAQS) fellowship. The content is solely the responsibility of the authors and does not necessarily represent the official views of the VAQS program or the Department of Veterans Affairs.