Rank Ordered Design Attributes for Healthcare Dashboards including Artificial Intelligence (AI) (Preprint)
Authors: Melina Malkani's Research Group Melina , Madan Eesha 
Published: November 2023

BACKGROUND

To enhance healthcare dashboards worldwide to benefit the public by making better healthcare information available for more informed decisions by the public and to improve population-level healthcare outcomes.[1,2]

OBJECTIVE

To enhance healthcare dashboards worldwide to benefit the public by making better healthcare information available for more informed decisions by the public and to improve population-level healthcare outcomes.[1,2]

METHODS

As a follow-on study, the authors evaluated 250 US government and commercial healthcare dashboards and conducted a survey of healthcare dashboards with 218 individuals identifying the best practices to consider when creating a public healthcare dashboard.
The dates of the survey and data collection were from June 2023 to August 2023.
These features ranked in descending order of importance are (1) easy navigation, (2) historical data, (3) simplicity of design, (4) high usability, (5) use of clear descriptions, (6) consistency of data, (7) use of diverse chart types, (8) compliance with Americans with Disabilities Act, (9) incorporated user feedback, (10) mobile compatibility, (11) comparison data with other entities, (12) storytelling, (13) predictive analytics with Artificial Intelligence (AI), (14) adjustable thresholds, and (15) charts with tabulated data. The prior study on COVID dashboards with 118 participants showed similar results.[3] Both studies validated top attributes of healthcare dashboards as easy navigation, simplicity of design, high usability, use of clear descriptions, and use of diverse chart types. Future studies can extend the research to other types of dashboards such as bioinformatics, financial, and managerial dashboards as well as confirm these top 15 best practices with further evidentiary support.

RESULTS

The authors conducted a survey of 218 (n=218) individuals above the age of 18. The survey consisted of 15 questions. Responses of “yes” counted as one point, while responses of “no” counted as 0 points. The authors calculated a total of 3,259 responses - 2,945 responses of “yes” and 314 responses of “no”. The Use of Charts with Tabulated Data had the lowest percent agreement of “yes” responses of 83%, whereas Easy Navigation had the highest percent agreement of “yes” responses of 96%, and the use of Predictive Analytics using Artificial Intelligence had “yes” responses of 87%, ranking at the 13th most popular attribute (Table 1).

CONCLUSIONS

As technology evolves, the availability of resources and data has become increasingly easier and better. With a click or a quick search, consumers have access to an abundance of healthcare data and data dashboards which aid in making informed healthcare decisions. However, healthcare dashboards may not be of the highest quality or as easily understood. Through our observational review and multiple surveys, we evaluated the effectiveness of healthcare dashboards in the United States in order to better understand and improve their design elements. From our analysis, we were able to develop and confirm the top 15 best practices of healthcare dashboard design from the ease of navigation to the use of predictive analytics. These 15 top best practices were assessed as the most important aspects of a healthcare dashboard’s effectiveness. The studies validated and concluded that the top five attributes of healthcare dashboards, such as easy navigation, simplicity of design, high usability, use of clear descriptions, and use of diverse chart types. As identified and analyzed, the best practices can be incorporated in order to design and disseminate effective healthcare dashboards making valuable healthcare information available to the public. Ultimately, the availability of better healthcare dashboards will help consumers make better and more informed healthcare decisions resulting in better pulsation health outcomes.

CLINICALTRIAL

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