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bioRxiv · 10.1101/415414

Evaluating the effects of data visualisation techniques on interpretation and preference in clinical quality reports: A cross-sectional study.

Koh, H. J. W.·Earnest, A.·Davis, I. D.·Loh, E.·Evans, S. M.
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Abstract

ObjectiveTo evaluate the different methods of data visualisation and how it affects preference and data interpretation.\n\nDesignA cross-sectional survey, assessing interpretation and preference for four methods of data presentation, was distributed to participants.\n\nSettingMelbourne, Victoria\n\nParticipantsMembers of Prostate Cancer Outcome Registry-Victoria (PCOR-Vic) and senior hospital staff in three metropolitan Victorian hospitals.\n\nInterventionsDifferent methods of data visualisation. Mainly, funnel plots, league charts, risk adjusted sequential probability ratio test (RASPRT) charts and dashboard.\n\nMain Outcome MeasureInterpretation scores assessed capacity by participants to identify outliers and poor performers. Preference was based on a 9-point Likert-scale (0 - 9).\n\nResultsIn total, 113 participants responded to the online survey (16/58 urologists and 97/297 senior hospital staff, response rate 32%). Respondents reported that funnel plots were easier to interpret compared to league charts (mean interpretability score difference of 28% (95% CI: 19.2% - 37.0%, P<0.0001). Predictors of worse interpretability of charts in the adjusted model were being a hospital executive compared to a urologist (coefficient= -2.50, 95% CI = -3.82, - 1.18, P<0.01) and having no statistical training compared to those with statistical training (coefficient = -1.71, 95% CI=-2.85, -0.58, P=0.003). Participants preferred funnel plots and dashboards compared to league charts and RASPRT charts (median score 7/9 vs 5/9), and preferred charts which were traffic-light coloured versus greyscale charts (43/60 (71.6%) vs 17/60 (28.3%)).\n\nConclusionWhen developing reports for clinicians and hospitals, consideration should be given to preference of end-users and ability of groups to interpret the graphs.

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Koh, H. J. W., Earnest, A., Davis, I. D., Loh, E., Evans, S. M.. 2018-09-12. Evaluating the effects of data visualisation techniques on interpretation and preference in clinical quality reports: A cross-sectional study.. https://doi.org/10.1101/415414

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