Association of Health Record Visualizations With Physicians' Cognitive Load When Prioritizing Hospitalized Patients.

Question Can information visualization tools within electronic health records reduce the cognitive workload for physicians when identifying which patients have the highest-priority care needs? Findings In this cross-sectional study of 29 physicians, information visualization tools that identified and highlighted clinically meaningful patterns were associated with a significantly lower cognitive workload compared with tools that required physicians to spend more time searching for similar information. Meaning Electronic health records that use well-designed information visualization tools have the potential to reduce cognitive workload among physicians. This cross-sectional study assesses the association of different design features of an electronic health record-based information visualization tool with the cognitive load of physicians during the clinical prioritization process. Importance Current electronic health records (EHRs) contribute to increased physician cognitive workload when completing clinical tasks. Objective To assess the association of different design features of an EHR-based information visualization tool with the cognitive load of physicians during the clinical prioritization process. Design, Setting, and Participants This cross-sectional study included a convenience sample of 29 attending physicians at Seattle Children's Hospital, a large tertiary academic pediatric hospital. Data collection took place from August 2017 through October 2017, and analysis occurred from August to October 2018. Exposure Physician participants used 3 prototypes with novel visualizations of simulated EHR data that highlighted 1 of 3 key patient characteristics, as follows: (1) acuity, (2) clinical problem list, and (3) clinical change. Main Outcomes and Measures Cognitive workload was measured using the NASA Task Load Index (TLX) scale (range, 1-100, with lower scores indicating lower cognitive workload). Cognitive workload was assessed for the 2 following clinical prioritization tasks: (1) finding information for a specific patient and (2) comparing results among patients for each prototype. Participants ranked 5 hypothetical patients from having the highest to the lowest priority in each design. Results A total of 29 physician participants (15 [52%] men; 14 [48%] women; mean [range] age, 43 [35-58] years; mean [range] time in practice, 11 [3-30] years) completed the study. For task 1, the prototype highlighting clinical change was associated with lower median (interquartile range) NASA TLX scores compared with the prototype highlighting acuity (30.3 [15.2-41.6] vs 48.5 [18.7-59.3]; P = .02). For task 2, the prototype highlighting clinical change was associated with lower median (interquartile range) NASA TLX scores compared with the prototype highlighting the clinical problem list (29.1 [16.3-50.8] vs 43.5 [26.6-55.9]; P = .02). The prototype highlighting clinical change had the lowest TLX score in 17 of 29 rankings (59%) for task 1 (chi(2)(4) = 24.4; P < .001) and 18 of 29 rankings (62%) for task 2 (chi(2)(4) = 17.2; P = .002). Conclusions and Relevance In this study, well-designed EHR-based information visualizations that highlighted and featured clinically meaningful information patterns significantly reduced physician cognitive workload when prioritizing patient needs.