Louise Brown, CMC Connect, IPG Health Medical Communications, UK; Faith DiBiasi, AstraZeneca, USA; Caroline Halford, Springer Healthcare, UK; Catherine Skobe, Pfizer, USA; Jodie Macoun, CMC Connect, IPG Health Medical Communications, Canada; Caroline Shepherd, CMC Connect, IPG Health Medical Communications, UK
Disclaimer
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Key Takeaways
Data visualization in peer-reviewed publications is a powerful way to communicate science to broad audiences. When used effectively, data visualization can make information easier to understand and remember, thereby increasing the likelihood of data being used to guide clinical practice with evidence-based decisions. It is essential that the pharmaceutical industry, medical communications agencies, and scientific publishers collaborate to support authors to plan, develop, and publish impactful and credible data visualizations.
Key actions that industry, agencies, and publishers can take to leverage data visualization in industry-sponsored scientific publications are supported by shared communication, collaboration, and advocacy
In this article, we explore opportunities, challenges, and solutions to successfully leverage data visualizations in publications. We provide perspectives from authors, medical writers, the pharmaceutical industry, and publishers, with a common goal of determining what we can do today, to improve patient care tomorrow.
What is Data Visualization in Today’s World?
Data visualization represents facts and figures through graphs, charts, or illustrations. This concept has spanned history, from ancient mapping of the earth and stars, through the ‘invention’ of the bar chart in the 18th century [1-3], to the plethora of visuals we see used across modern industries [4]. While technical sectors (e.g., software and intelligence) have a well-established application of visualization to data management, analysis, and processes [4], today it’s also common to see data visualization used by companies and communications outlets to tell stories of demographics, business, economics, politics, sports, education, climate, and health [4-8].
Focusing on health, data visualization is not only booming, but essential to the point of informing life and death decisions, as most recently exemplified by the COVID-19 pandemic [4, 9-11]. Live tracking and visualization of cases and deaths by health organizations [12-14] and news channels [15-17], informed national mandates, influenced individual behavior, and spurred on vaccine research [9, 18-20].
Experience from the COVID-19 pandemic emphasized the core purpose of data visualization, which is to make information easier to understand, remember, and mean something, such that it guides evidence-based choices and actions. It also highlighted the importance of getting data visualization right, with many visuals critiqued for being misleading on the severity and trends of the pandemic [19, 21-24]. Other events have also taught us how bad data visualization can be downright dangerous [footnote: an incomplete graph played a role in the Challenger space shuttle disaster [25]]. We must take learnings about the power of data visualization, and the importance of getting it right, into our world of publications.
Why Should We Consider Use of Data Visualization in Industry-Sponsored Publications?
Data visualization offers additional opportunities for authors to educate busy healthcare professionals who struggle to keep up with both their practice and medical research [26-30]. It also provides avenues to tailor content for different levels of health and data literacy [31-33], which can facilitate information exchange with and between healthcare professionals, patients, advocates, families, and the public. More broadly, data visualization supports the potential within publications for data democratization (making information understandable for all, e.g., with a data visualization that clearly illustrates a trend in a complex dataset); localization (providing options for different people and places, e.g., with a data visualization that is customized for cultural understanding); and accessibility (providing options for different abilities, needs, or preferences, e.g., with a data visualization with colors suitable for visual impairments) [34-41].
Effective data visualization is content-driven, rather than design-driven, meaning that visuals should serve to represent the data, rather than be aesthetic without meaning. It should be informed by sound scientific objectives, audience needs, purpose (e.g., to educate, engage, inspire), accurate and relevant data, and delivery channel. In our world of industry-sponsored publications, visualization is bound by guardrails of transparent and balanced data sharing. Yet, data visualization may be used within and shared via publication content considered core (e.g., main article figures), extended (e.g., supplementary information behind a QR code), and enhanced (e.g., infographic or video summaries).
Examples of different types of data visualization that may be used in industry-sponsored scientific publications
Research tells us that visual information, in general, improves understanding and engagement in publications:
- Visualizing data can support healthcare professionals in interpretation and understanding of information to inform clinical decisions and patient care [42-47]; which, in turn, can support patient understanding and decisions [48]
- Visualizing data can better communicate the risks of a treatment [43, 49]
- Infographic and visual abstracts are preferred [50], and receive more views and engagement on social media [51-56] versus text content
How Can We Incorporate Data Visualization in Publications Planning and Delivery?
To realize the opportunity of data visualization, industry, agencies, and publishers must take action to effectively plan and deliver such content. Critically, these actions should be underpinned by knowledge sharing and active collaboration among all stakeholders, including authors.
Opportunities to be realized with data visualization in scientific publications
Call to action: pharmaceutical industry
Call to action: medical communications agencies
Call to action: scientific publishers
What is Data Visualization in Tomorrow’s World?
Healthcare professionals have been consistently inconsistent in their preferences for how they want to receive information. Expand this concept to include patients and their families, and there will never be a ‘one size fits all’ presentation of information. Utilizing Artificial Intelligence in the creation of original data visuals, supported by appropriate fact-checking, could streamline the development of multiple formats of the same data supported by a single source. Accessing this information may require an expansion of capabilities for digital content on publisher platforms, or alternative platforms to house similar formats of content could become the norm. With algorithms already designed to determine individuals’ preferences for content, endless opportunities exist to notify end users of new data available in healthcare, which can be shared with colleagues or in patient consultations, all backed up with the appropriate link to the source.
The digital age has provided us with the ability to track interaction with content. However, beyond counting clicks, the true impact of data visualization will be seen in improved healthcare – earlier diagnosis, increased use of targeted treatments, and better quality of life for patients. Meaningful metrics should look at the bigger picture (pun intended) and endeavor to quantify how data visuals can change the practice of healthcare.
Acknowledgments
Editing support was provided by Bernadette Watkins, CMC Connect, IPG Health Medical Communications.
Disclosures
L. Brown, C. Shepherd, and J. Macoun are employees of CMC Connect, IPG Health Medical Communications. F. DiBiasi is an employee of AstraZeneca and holds stocks in the company. C. Halford is an employee of Springer Healthcare, part of the Springer Nature group. C. Skobe is an employee of Pfizer and holds stocks in the company.
References
1. Mackinlay JD, Winslow K. The history of data visualizations – from cave drawings to Tableau 2019. https://www.tableau.com/whitepapers/designing-great-visualization Accessed July 12, 2023.
2. Hillery A. The evolution of data visualization Chartio. 2020. https://chartio.com/blog/the-evolution-of-data-visualization/ Accessed July 12, 2023.
3. Proctor A. Five charts that changed the world – BBC Ideas 2023. https://www.bbc.co.uk/ideas/videos/five-charts-that-changed-the-world/p0fb69c1 Accessed July 12, 2023.
4. Tratz M. Which industries use data visualization as part of their service – and who is next? . 2022. https://www.linkedin.com/pulse/which-industries-use-data-visualizations-part-service-matthias-tratz/ Accessed July 12, 2023.
5. BBC Visual and Data Journalism. How the BBC Visual and Data Journalism team works with graphics in R 2019. https://medium.com/bbc-visual-and-data-journalism/how-the-bbc-visual-and-data-journalism-team-works-with-graphics-in-r-ed0b35693535 Accessed July 13, 2023.
6. The Guardian. Data visualisations. The Guardian. 2023. https://www.theguardian.com/technology/data-visualisation.
7. NBC News. NBC News Graphics – Explaining the news through visualizations and data analysis from the NBC News Digital Data/Graphics team https://www.nbcnews.com/datagraphics Accessed July 12, 2023.
8. CNBC. Data Visualizations 2023. https://www.cnbc.com/data-visualizations/ Accessed July 12, 2023.
9. Abayowa J. Visualizing healthcare data with infographics to save lives 2021. https://venngage.com/blog/healthcare-data-visualization/ Accessed July 13, 2023.
10. Dunskiy I. Healthcare data visualization: examples and key benefits 2021. https://demigos.com/blog-post/healthcare-data-visualization/ Accessed July 13, 2023.
11. Zhang Y, Sun Y, Padilla L, Barua S, Bertini E, Parker AG. Mapping the landscape of COVID-19 crisis visualizations [Abstract]. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems; Yokohama, Japan: Association for Computing Machinery; 2021Article 608.
12. Berkley A, Letzing J. The COVID-19 pandemic in data visualizations – World Economic Forum 2023. https://www.weforum.org/agenda/2021/09/the-covid-19-pandemic-in-visuals/ Accessed July 13, 2023.
13. Johns Hopkins University of Medicine Coronavirus Resource Center. COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU) 2023. https://coronavirus.jhu.edu/map.html Accessed July 12, 2023.
14. World Health Organization. WHO Coronavirus (COVID-19) Dashboard https://covid19.who.int/ Accessed July 13, 2023.
15. BBC. Coronavirus: UK spread in maps and charts 2020. https://www.bbc.co.uk/news/uk-51768274 Accessed July 25, 2023.
16. NBC News. Covid Data Dashboard 2023. https://www.nbcnews.com/covid-data-dashboard Accessed August 1, 2023.
17. The New York Times. Coronavirus in the U.S.: Latest Map and Case Count 2021. https://www.nytimes.com/interactive/2021/us/covid-cases.html Accessed July 12, 2023.
18. Padilla L, Hosseinpour H, Fygenson R, Howell J, Chunara R, Bertini E. Impact of COVID-19 forecast visualizations on pandemic risk perceptions. Scientific Reports 2022;12:2014.
19. Lee C, Yang T, Inchoco GB, Jones GM, Satyanarayan A. Viral visualizations: How coronavirus skeptics use orthodox data practices to promote unorthodox science online. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems; Yokohama, Japan: Association for Computing Machinery; 2021Article 607.
20. Leung CK, Chen Y, Hio CSH, Shang S, Wen Y, Cuzzocrea A, editors. Big data visualization and visual analytics of COVID-19 data. 24th International Conference Information Visualisation (IV); 2020; Melbourne, Australia.
21. Foley KE. How bad Covid-19 data visualizations mislead the public. Quartz. 2020. https://qz.com/1872980/how-bad-covid-19-data-visualizations-mislead-the-public Accessed July 13, 2023.
22. Engeldowl C, Weiland T. Data (mis)representation and COVID-19: leveraging misleading data visualizations for developing statistical literacy across Grades 6–16. Journal of Statistics and Data Science Education 2021;29:160-4.
23. Tracy S. COVID-19 in charts: examples of good & bad data visualization 2020. https://www.linkedin.com/pulse/covid-19-charts-examples-good-bad-data-visualization-stephen-tracy/?articleId=6662515411176828928 Accessed July 13, 2023.
24. Cotgreave A. What the BBC got wrong in their COVID-19 visualization. Tableau. 2020. https://www.tableau.com/blog/covid-19-resources-data-viz-best-practices Accessed July 13, 2023.
25. Dixon R. The Challenger space shuttle disaster: a case study in the analysis of binary data using scatter diagrams and logit regression [Abstract]. The Australian Economic Review 2021;54:294-305.
26. Alper B. How much effort is needed to keep up with the literature relevant for primary care? J Med Libr Assoc 2004;92:429-37.
27. Sinsky C, Colligan L, Li L, Prgomet M, Reynolds S, Goeders L, et al. Allocation of physician time in ambulatory practice: a time and motion study in 4 specialties [Abstract]. Ann Intern Med 2016;165:753-60.
28. Peters E. Survey: how doctors read and what it means to patients. Business Wire. 2014. https://www.businesswire.com/news/home/20140722005535/en/Survey-Doctors-Read-Means-Patients#:~:text=%E2%80%9CMedicine%20has%20a%20TL%3BDR%20problem%20%28Too%20Long%3B%20Didn%E2%80%99t Accessed July 13, 2023.
29. Royal College of Physicians. Lack of time greatest barrier to doing research, say doctors. Royal College of Physicians News. 2016. https://www.rcplondon.ac.uk/news/lack-time-greatest-barrier-doing-research-say-doctors.
30. Porter J, Boyd C, Skandari MR, Laiteerapong N. Revisiting the time needed to provide adult primary care. J Gen Intern Med 2023;38:147-55.
31. Dodson S, Good S. Health literacy toolkit for low- and middle-income countries 2014. https://www.who.int/publications/i/item/9789290224754 Accessed July 13, 2023.
32. Centers for Disease Control and Prevention. Understanding health literacy 2019. https://www.cdc.gov/healthliteracy/learn/Understanding.html Accessed July 13, 2023.
33. NHS England. Enabling people to make informed health decisions 2022. https://www.england.nhs.uk/personalisedcare/health-literacy/ Accessed July 13, 2023.
34. Bert A, Hayes LM. Making charts accessible for people with visual impairments 2018. https://www.elsevier.com/connect/making-charts-accessible-for-people-with-visual-impairments Accessed July 13, 2023.
35. Careri W. Designing for neurodivergent audiences. Nightingale – Journal of the Data Visualization Society. 2022. https://nightingaledvs.com/designing-for-neurodivergent-audiences/#:~:text=For%20those%20in%20this%20community%2C%20having%20a%20visual Accessed July 13, 2023.
36. Gaskin J. Accessible fonts: A guide to design for accessibility – Vengage 2022. https://venngage.com/blog/accessible-fonts/ Accessed July 13, 2023.
37. Wu K, Petersen E, Ahmad T, Burlinson D, Tanis S, Szafir DA. Understanding data accessibility for people with intellectual and developmental disabilities. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems; Yokohama, Japan: Association for Computing Machinery; 2021Article 606.
38. Zewe A. Making data visualization more accessible for blind and low-vision individuals. MIT News 2022. https://news.mit.edu/2022/data-visualization-accessible-blind-0602 Accessed July 13, 2023.
39. UW–Madison Information Technology. Accessible data visualizations 2021. https://it.wisc.edu/learn/make-it-accessible/accessible-data-visualizations/ Accessed July 13, 2023.
40. Schwabish J, Feng A. Do no harm guide: Applying equity awareness in data visualisation 2021. https://www.urban.org/sites/default/files/publication/104296/do-no-harm-guide.pdf Accessed July 13, 2023.
41. Mixson E. Make data accessible to everyone with data democratization 2021. https://www.aidataanalytics.network/data-democratization/articles/making-data-accessible-to-everyone-with-data-democratization Accessed July 13, 2023.
42. Backonja U, Haynes SC, Kim KK. Data visualizations to support health practitioners’ provision of personalized care for patients with cancer and multiple chronic conditions: user-centered design study. JMIR Hum Factors 2018;5:e11826.
43. Tung J, Bodkin RJ, Laughton T, Neat C, Benjamin S, An H, et al. Efficiency and effectiveness of geriatric drug infographics: A randomized, controlled trial. Journal of the American Geriatrics Society 2021;69:2355-8.
44. Ledesma A, Bidargaddi N, Strobel J. Health timeline: an insight-based study of a timeline visualization of clinical data. BMC Med Inform Decis Mak 2019;19:170.
45. Ibrahim AM, Lillemoe KD, Klingensmith ME, Dimick JB. Visual abstracts to disseminate research on social media: A prospective, case-control crossover study. Annals of Surgery 2017;266:e46-e8.
46. Park S, Bekemeier B, Flaxman AD. Understanding data use and preference of data visualization for public health professionals: A qualitative study. Public Health Nursing 2021;38:531-41.
47. Park S, Bekemeier B, Flaxman A, Schultz M. Impact of data visualization on decision-making and its implications for public health practice: a systematic literature review. Informatics for Health and Social Care 2022;47:175-93.
48. Shaffer VA, Wegier P, Valentine KD, Belden JL, Canfield SM, Popescu M, et al. Use of enhanced data visualization to improve patient judgments about hypertension control. Medical Decision Making 2020;40:785-96.
49. Qureshi R, Chen X, Goerg C, Mayo-Wilson E, Dickinson S, Golzarri-Arroyo L, et al. Comparing the value of data visualization methods for communicating harms in clinical trials. Epidemiologic Reviews 2022;44:55-66.
50. Martin LJ, Turnquist A, Groot B, Huang SYM, Kok E, Thoma B, et al. Exploring the role of infographics for summarizing medical literature. Health Professions Education 2019;5:48-57.
51. Chisari E, Gouda Z, Abdelaal M, Shileds J, Stambough JB, Bellamy J, et al. A crossover randomized trial of visual abstracts versus plain-text tweets for disseminating orthopedics research. The Journal of Arthroplasty 2021;36:3010-4.
52. Oska S, Lerma E, Topf J. A picture is worth a thousand views: a triple crossover trial of visual abstracts to examine their impact on research dissemination. J Med Internet Res 2020;22:e22327.
53. Hoffberg AS, Huggins J, Cobb A, Forster JE, Bahraini N. Beyond journals—visual abstracts promote wider suicide prevention research dissemination and engagement: a randomized crossover trial Frontiers in Research Metrics and Analytics 2020;5:564193.
54. Spicer JO, Coleman CG. Creating effective infographics and visual abstracts to disseminate research and facilitate medical education on social media. Clinical Infectious Diseases 2022;74:e14-e22.
55. Chapman SJ, Grossman RC, FitzPatrick RR, Brady RRW. Randomized controlled trial of plain English and visual abstracts for disseminating surgical research via social media. British Journal of Surgery 2019;106:1611–6.
56. Kunze KN, Vadhera A, Purbey R, Singh H, Kazarian GS, Chahla J. Infographics are more effective at increasing social media attention in comparison with original research articles: an altmetrics-based analysis. Arthroscopy: The Journal of Arthroscopic and Related Surgery 2021;37:2591-7.