ObjectiveIn this study, we used human factors (HF) methods and principles to design a clinical decision support (CDS) that provides cognitive support to the pulmonary embolism (PE) diagnostic decision-making process in the emergency department. We hypothesised that the application of HF methods and principles will produce a more usable CDS that improves PE diagnostic decision-making, in particular decision about appropriate clinical pathway.Materials and methodsWe conducted a scenario-based simulation study to compare a HF-based CDS (the so-called CDS for PE diagnosis (PE-Dx CDS)) with a web-based CDS (MDCalc); 32 emergency physicians performed various tasks using both CDS. PE-Dx integrated HF design principles such as automating information acquisition and analysis, and minimising workload. We assessed all three dimensions of usability using both objective and subjective measures: effectiveness (eg, appropriate decision regarding the PE diagnostic pathway), efficiency (eg, time spent, perceived workload) and satisfaction (perceived usability of CDS).ResultsEmergency physicians made more appropriate diagnostic decisions (94% with PE-Dx; 84% with web-based CDS; p<0.01) and performed experimental tasks faster with the PE-Dx CDS (on average 96 s per scenario with PE-Dx; 117 s with web-based CDS; p<0.001). They also reported lower workload (p<0.001) and higher satisfaction (p<0.001) with PE-Dx.ConclusionsThis simulation study shows that HF methods and principles can improve usability of CDS and diagnostic decision-making. Aspects of the HF-based CDS that provided cognitive support to emergency physicians and improved diagnostic performance included automation of information acquisition (eg, auto-populating risk scoring algorithms), minimisation of workload and support of decision selection (eg, recommending a clinical pathway). These HF design principles can be applied to the design of other CDS technologies to improve diagnostic safety.
Background Activity trackers may motivate individuals to engage in healthy behaviors. They are also used in research and may help manage chronic conditions related to lifestyle (1). Traditional trackers that require a separate chest strap and work like an electrocardiograph are being supplemented with other types of trackers. One type is a wrist-worn tracker with a lightemitting diode. It measures the heart rate from tiny changes in skin blood volume by using light reflected from the skin. These new devices are unobtrusive and appropriate for continuous, long-term wear. Although previous studies have shown that they are generally accurate for measuring the number of steps a person takes, less is known about their accuracy when measuring heart rate (2-4). Objective To determine the accuracy of the heart rate measured by light-emitting diode-dependent, wrist-worn activity trackers. Methods We studied 4 commercial, wrist-worn activity trackers that measure the heart rate by using light-emitting diodes. Study participants were 40 healthy consenting adults aged 30 to 65 years without cardiovascular conditions. For each participant, we placed 2 trackers on each wrist in random order by right versus left wrist and by proximal versus distal location on the
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