High cholesterol is a risk factor for developing Atherosclerotic Cardiovascular Disease. Poorly designed health data displays cause an undue cognitive burden on clinicians. Simplified line graphs (i.e., sparklines) could support efficient cognitive processing and interpretation of lipid panel results. Clinical concepts for cognitive tasks assessing low-density lipoprotein laboratory results were analyzed according to their internal representations and data scale types. A sparkline external representation aligns more closely with the internal representations for mental tasks associated with identifying abnormalities and assessing trends compared to traditional tabular displays. By simplifying the health data display with sparklines, faster cognitive processing is theoretically supported.
Keywords: data visualization; human-computer interaction; qualitative methods; user-centered design methods.