Using a context-sensitive ranking method to organize reversible causes of cardiac arrest in a digital cognitive aid

Abstract

Medical doctors typically identify reversible causes associated with cardiac arrest by recalling them from memory, using a mnemonic. External techniques, such as cognitive aids (e.g., iPad-based applications), have been shown to produce an increase in performance in medical diagnosis. We studied two alternative approaches to the traditional method of using mnemonics to identify reversible causes of cardiac arrest. One approach displayed the causes in alphabetical order (alphabetical scheme) while the other approach displayed causes ordered by their relevance to the patient-context (context-sensitive scheme). We recorded performance and usability measures for these two approaches in two simulated cardiac arrest scenarios for each group. It took significantly longer for the participants to identify the causes using the context- sensitive scheme. However, the context-sensitive scheme resulted in significantly fewer unnecessary keystrokes. The two schemes did not differ significantly in terms of their usability ratings.