The emergency department is a place of risk and errors. Those who work in the ED are acutely aware of this, and it conjures up tremendous cognitive pressures on staff every shift.
Every ED clinician knows the most benign-appearing triage complaint may obfuscate lurking catastrophe. The vision changes that are actually an acute aortic dissection. A sore shoulder that is necrotizing fasciitis. The list goes on. If some are to be believed, hundreds of thousands are being killed each year by diagnostic errors in the ED. The reality is much lower, but still nontrivial.
But, the net effect becomes – the ED is a focus for patient safety research. In modern parlance, “diagnostic errors” become “missed opportunities for diagnosis” (MODs), and well-meaning researchers are devising further methods to shine bright lights upon our inadequacies.
This most recent publication looks at “e-Triggers” – effectively, combinations of both patient features and patient outcomes meant to retrospectively identify cohorts in which substantial numbers of patients can be found to have MODs. For example, in this paper, the authors use an “e-Trigger” modelled around posterior circulation stroke – in which the data warehouse is queried for elderly patients presenting with dizziness, at least two cerebrovascular risk factors, and whom, after initial discharge from the ED, suffered a stroke within 30 days.
When the authors dredged 8M records from the Veterans Affairs system for this, they identified 203 such instances, and manually reviewed 100 of these using a structured framework to characterize any diagnostic error present. For this “stroke” example, 47 of the 100 patients reviewed were identified to have had MODs. Per the review of records, the most common missed opportunity stemmed from inadequate physical examination and insufficient ordering of diagnostic tests. As a result, most of the patients reviewed suffered moderate or severe harms as a result of these MODs.
There is good news and bad news from this “e-Trigger” method shown here. The good news is primarily of interest to patient safety researchers, indicating this is probably a reasonable method to use for enriching populations for review to further describe the types of error occurring in specific clinical scenarios. This could lead to identification of generalizable knowledge gaps, cognitive biases, or system factors. It is also, probably, too unwieldy and labor intensive for routine punitive use targeting individual clinicians.
The bad news is primarily patient-centered. The fundamental nature of the e-Trigger structure requires a pairing of a cohort at risk and a subsequent unfortunate outcome. Thus, the harm has already reached the patient. It seems plausible suitably high-risk cohorts could be determined relatively contemporaneously, but the challenge would be finding a mechanism to detect a MOD with sufficient specificity to be deployable in clinical workflow. However, with the ability to potentially replace some previously human review steps with AI, this idea may be imminently achievable – watch this space!
“Implementation of Electronic Triggers to Identify Diagnostic Errors in Emergency Departments”
https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2827341