TRA-1-1 TEST RESULTS IN LINE GRAPHS INSTEAD OF TABLES: LESS CONFUSION WITHOUT DISTORTION

Monday, October 19, 2015: 10:00 AM
Grand Ballroom BC (Hyatt Regency St. Louis at the Arch)

Brian J. Zikmund-Fisher, PhD1, Aaron M. Scherer, PhD1, Angela Fagerlin, PhD2, Predrag Klasjna, PhD1, Beth A. Tarini, MD1, Nicole L. Exe, MPH1, Knoll Larkin, MPH1 and Holly Witteman, PhD3, (1)University of Michigan, Ann Arbor, MI, (2)VA Ann Arbor Healthcare System & University of Michigan, Ann Arbor, MI, (3)Université Laval, Quebec City, QC, Canada
Purpose: Patients can increasingly access and view laboratory test results directly via patient portals to electronic health record systems. At present, virtually all such systems display test results in a tabular format that provides a standard range (either with or without high / low markers). Unfortunately, recently published research shows that many people cannot identify out-of-range results in such tables and that confusion is particularly common among the less numerate and literate.

Method: We conducted an online survey experiment in which participants imagined receiving hemoglobin A1c test results in-between clinical visits for management of Type 2 diabetes. Adults (N=1,785) viewed their mock results in one of three formats: (1) standard table that included the test result and a standard range, (2) table with an indicator for whether a result was high or low, or (3) a horizontal line graph that visually showed the test result and standard range. We also varied whether A1c was within the standard range (5.4%), or one of three higher levels (6.4%, 7.1%, or 8.4%). Our primary outcome measure was participants’ ratings of how good or bad they thought the test value was (or whether they marked “don’t know”). Secondary measures included 4 questions related to graph preferences. We also assessed participant numeracy using both subjective and objective scales as well as graphical literacy.

Result: Controlling for numeracy and graphical literacy, significantly more respondents marked “don’t know” for how good or bad the test result was when they viewed the table without markers (OR=2.42, p<.001) or table with markers (OR=2.23, p<.001) than when they viewed the line graph. Subjective numeracy strongly predicted “don’t know” responses (p<.001), but neither objective numeracy (p=.09) nor graphical literacy (p=.14) were significant predictors. Mean risk perceptions varied by A1c level (p<.001) and were significantly predicted by subjective numeracy, objective numeracy, and graphical literacy (all p’s<.001), but were not significantly different across formats. The 4 graph perception questions were highly correlated (Cronbach’s alpha=0.89), and respondents significantly preferred the line graphs compared to either table format (p=.003).

Conclusion: Presenting laboratory test results in the commonly-used table formats, even those with high/low markers, can confuse patients. Visual line graph displays improve patient understanding and satisfaction and could be easily implemented into patient electronic health record portals.