Emergency department use of an electronic differential diagnosis generator in the evaluation of critically ill patients

BackgroundAccurate diagnosis is an essential component of managing critically ill emergency department (ED) patients. Electronic diagnosis generators (EDGs) are software tools which assist clinicians in their diagnosis generation; however, they have not been evaluated for use for critical ED patients. We aimed to evaluate the use of an EDG for this population to determine its impact on diagnosis generation and diagnostic testing.MethodsWe performed an observational study on usage of an EDG in the high-acuity area of a tertiary care ED. The EDG was used by residents evaluating each patient in the area. The resident used the EDG when the case was felt to have diagnostic uncertainty and completed a data collection tool. Data were summarized by frequencies. Chi-squared or Fisher's exact tests were used to assess the association of added value of the EDG for diagnosis generation and diagnostic testing.Affiliations: Journal instruction requires a country for affiliations; however, this is missing in all affiliations. Please verify if the provided country is correct and amend if necessary.Country provided is correctResultsOver the 8-month study period, the EDG was utilized to evaluate 98 critical ED patients, of whom 60% were female, 7% were pediatric, and 46% were elderly. It was used most commonly for gastroenterological, infectious disease/immunologic, metabolic/renal, and neuropsychiatric presentations, and was least used for trauma presentations. Use of the EDG led to a diagnosis not initially considered in 47% of cases and led to additional diagnostic testing in 4% of cases.ConclusionEDGs have some potential to improve diagnosis in critical EM patients by expanding the differential diagnosis and, to a lesser extent, altering diagnostic testing.

Automated summary

An observational study on the usage of an electronic diagnosis generator (EDG) in a high-acuity area of a tertiary care emergency department showed that it can play a role in improving diagnosis and guiding diagnostic testing for critically ill patients, especially for cases with uncertainty.