Graphics help patients distinguish between urgent and non-urgent deviations in laboratory test results

Abstract

Objective: Most electronic health record systems provide laboratory test results to patients in table format. We tested whether presenting such results in visual displays (number lines) could improve understanding. Materials and Methods: We presented 1620 adults recruited from a demographically diverse Internet panel with hypothetical results from several common laboratory tests, first showing near-normal results and then more extreme values. Participants viewed results in either table format (with a "standard range" provided) or one of 3 number line formats: a simple 2-color format, a format with diagnostic categories such as "borderline high" indicated by colored blocks, and a gradient format that used color gradients to smoothly represent increasing risk as values deviated from standard ranges. We measured respondents' subjective sense of urgency about each test result, their behavioral intentions, and their perceptions of the display format. Results: Visual displays reduced respondents' perceived urgency and desire to contact health care providers immediately for near-normal test results compared to tables but did not affect their perceptions of extreme values. In regression analyses controlling for respondent health literacy, numeracy, and graphical literacy, gradient line displays resulted in the greatest sensitivity to changes in test results. Discussion: Unlike tables, which only tell patients whether test results are normal or not, visual displays can increase the meaningfulness of test results by clearly defining possible values and leveraging color cues and evaluative labels. Conclusion: Patient-facing displays of laboratory test results should use visual displays rather than tables to increase people's sensitivity to variations in their results.

Methods for Patient-Centered Interface Design of Test Result Display in Online Portals

“…Though there has been mention of the importance for user-centered design when developing patient-facing applications within EHRs [11] (such as patient portals), few studies have managed to carry-out the user-centered design process [12] in its entirety. The majority of studies on patient-centered design have explored patients’ information needs when interpreting their test results and how appropriate informatics tools can improve patient comprehension of health concepts [1314151617]. However, few published studies have attempted to take the next steps to use these information requirements to propose new designs for patient-facing interfaces or tools that promote patients’ comprehension of test results and to test these interfaces with patients [16].…”

Supporting Collaborative Health Tracking in the Hospital

“…Regarding benchmarks, Zikmund-Fisher et al demonstrated that visualizations of benchmark ranges for test results can help patients interpret data and distinguish near-normal from atypical results [60]. However, Wilcox et al point out that clinicians sometimes object to the presentation of reference ranges because they are not appropriate in all cases [56].…”

“…However, thus far researchers have largely focused on data collected by patients or their family members. Although researchers have begun to explore better ways to present data provided to patients by health care organizations [22,60], much work remains to be done on how to support patient-provider collaboration in the hospital, where clinicians collect and control the bulk of patient data. Thus far, studies in this space have shown that hospitalized patients value the ability to ask their clinicians questions electronically [57], “triage” their inquiries [57], and set personalized health goals [10].…”

Report formatting in laboratory medicine – a call for harmony

“…As stated above, there have been a number of proponents of more graphical formats, both in the medical literature [12,13] and in the wider public arena [14]. Proposed tools include the use of graphical outputs with colour shaded areas to indicate risk [12,13], miniature graphical tools (sparklines) [12] and tools to highlight changes within an individual in addition to as well as absolute values of results [15].…”