A Systematic Method for Exploring Data Attributes in Preparation for Designing Tailored Infographics of Patient Reported Outcomes

Abstract

Context:Tailored visualizations of patient reported outcomes (PROs) are valuable health communication tools to support shared decision making, health self-management, and engagement with research participants, such as cohorts in the NIH Precision Medicine Initiative. The automation of visualizations presents some unique design challenges. Efficient design processes depend upon gaining a thorough understanding of the data prior to prototyping.Case Description:We present a systematic method to exploring data attributes, with a specific focus on application to self-reported health data. The method entails a) determining the meaning of the variable to be visualized, b) identifying the possible and likely values, and c) understanding how values are interpreted.Findings:We present two case studies to illustrate how this method affected our design decisions particularly with respect to outlier and non-missing zero values.Major Themes:The use of a systematic method made our process of exploring data attributes easily manageable. The limitations of the data can narrow design options but can also prompt creative solutions and innovative design opportunities.Conclusion:A systematic method of exploration of data contributes to an efficient design process, uncovers design opportunities, and alerts the designer to design challenges.

Leveraging Patient-Reported Outcomes Using Data Visualization

“…This is consistent with previous research that brief text descriptions combined with visualizations perform better than either alone. 23,38,40 Additionally, most patients in our study failed to comprehend graphs. This is consistent with previous research that inadequate graph literacy is prevalent, around 40% of the U.S. population.…”

“…46,47 Previous studies have primarily displayed PRO data for patients with graphs. [20][21][22][23] Given our results and the prevalence of inadequate graph literacy, exploration of additional visualization strategies beyond graphs is warranted. When displaying PRO data over time, avoiding graphs is potentially difficult.…”

“…2, panels 1-4). 23,[38][39][40] With validated surveys like PROMIS Table 3 Health-ITUES scores for the mi.Symptoms mockup (scores range from 1 to 5, lowest to highest)…”

“…Previously studied strategies to display results for patients primarily used graphs. [20][21][22][23] Additional strategies to aid patient's comprehension of their PRO data remain to be explored.…”

Promoting Latino self-management through use of information visualizations: A case study in New York City

“…Phase 2: Understanding the data is critical to an efficient design process as well as the identification of design opportunities and challenges [12]. It involves three major components: (a) determining the meaning of the variable to be visualized; (b) identifying the possible and likely values; and (c) understanding how values are interpreted.…”