Diagnostic Errors in Hospitalized Adults Who Died or Were Transferred to Intensive Care

Abstract

ImportanceDiagnostic errors contribute to patient harm, though few data exist to describe their prevalence or underlying causes among medical inpatients.ObjectiveTo determine the prevalence, underlying cause, and harms of diagnostic errors among hospitalized adults transferred to an intensive care unit (ICU) or who died.Design, Setting, and ParticipantsRetrospective cohort study conducted at 29 academic medical centers in the US in a random sample of adults hospitalized with general medical conditions and who were transferred to an ICU, died, or both from January 1 to December 31, 2019. Each record was reviewed by 2 trained clinicians to determine whether a diagnostic error occurred (ie, missed or delayed diagnosis), identify diagnostic process faults, and classify harms. Multivariable models estimated association between process faults and diagnostic error. Opportunity for diagnostic error reduction associated with each fault was estimated using the adjusted proportion attributable fraction (aPAF). Data analysis was performed from April through September 2023.Main Outcomes and MeasuresWhether or not a diagnostic error took place, the frequency of underlying causes of errors, and harms associated with those errors.ResultsOf 2428 patient records at 29 hospitals that underwent review (mean [SD] patient age, 63.9 [17.0] years; 1107 [45.6%] female and 1321 male individuals [54.4%]), 550 patients (23.0%; 95% CI, 20.9%-25.3%) had experienced a diagnostic error. Errors were judged to have contributed to temporary harm, permanent harm, or death in 436 patients (17.8%; 95% CI, 15.9%-19.8%); among the 1863 patients who died, diagnostic error was judged to have contributed to death in 121 (6.6%; 95% CI, 5.3%-8.2%). In multivariable models examining process faults associated with any diagnostic error, patient assessment problems (aPAF, 21.4%; 95% CI, 16.4%-26.4%) and problems with test ordering and interpretation (aPAF, 19.9%; 95% CI, 14.7%-25.1%) had the highest opportunity to reduce diagnostic errors; similar ranking was seen in multivariable models examining harmful diagnostic errors.Conclusions and RelevanceIn this cohort study, diagnostic errors in hospitalized adults who died or were transferred to the ICU were common and associated with patient harm. Problems with choosing and interpreting tests and the processes involved with clinician assessment are high-priority areas for improvement efforts.

Diagnostic reasoning in the age of artificial intelligence: Synergy or opposition?

“…15 Envision an integration of this generated ranked list of diagnoses that would exist in line with clinicians' current workflow, appearing as an optional, editable block of text while writing the "assessment and plan" section of a note. This could hint to a hospitalist of late-onset medication adverse effect, such as those from immunotherapy given months prior or add consideration to salicylate toxicity in a patient presenting with gastrointestinal bleed from nonsteroidal antiinflammatory overuse, a recently highlighted diagnostic miss in Auerbach et al 16 It is our opinion that this collaborative approach between human clinicians and AI will be synergistic and will improve diagnostic accuracy and enhance patient care overall. AI will undoubtedly change how clinicians practice as it is incorporated into healthcare.…”

Influence of a Large Language Model on Diagnostic Reasoning: A Randomized Clinical Vignette Study

“…Medical diagnosis is a high-stakes cognitive process that takes place in time-constrained and stressful clinical environments. Diagnostic errors are common and contribute to significant patient harm 1,2,3,4,5,6 .…”

“…Medical diagnosis is a high-stakes cognitive process that takes place in time-constrained and stressful clinical environments. Diagnostic errors are common and contribute to significant patient harm 1,2,3,4,5,6 . Strategies to reduce diagnostic errors include a variety of educational, reflective, and team-based practices.…”