The incidence of diagnostic error in medicine

By M. Graber. 2013

570 citations recorded by the source corpus.

A wide variety of research studies suggest that breakdowns in the diagnostic process result in a staggering toll of harm and patient deaths. These include autopsy studies, case reviews, surveys of patient and physicians, voluntary reporting systems, using standardised patients, second reviews, diagnostic testing audits and closed claims reviews. Although these different approaches provide important information and unique insights regarding diagnostic errors, each has limitations and none is well suited to establishing the incidence of diagnostic error in actual practice, or the aggregate rate of error and harm. We argue that being able to measure the incidence of diagnostic error is essential to enable research studies on diagnostic error, and to initiate quality improvement projects aimed at reducing the risk of error and harm. Three approaches appear most promising in this regard: (1) using ‘trigger tools’ to identify from electronic health records cases at high risk for diagnostic error; (2) using standardised patients (secret shoppers) to study the rate of error in practice; (3) encouraging both patients and physicians to voluntarily report errors they encounter, and facilitating this process.

Subfields: Emergency Medical Services, Family Practice, Pharmacy

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Citations in the corpus

Early recognition of multiple sclerosis using natural language processing of the electronic health record (2017, background): “Unfortunately, diagnostic error, which includes delayed, incorrect or missed diagnosis, is common and accounts for a significant proportion of medical error [1, 2].”
Evaluation of symptom checkers for self diagnosis and triage: audit study (2015, background): “33 34 However, in-person physician visits might be the wrong comparison because patients are likely not using symptom checkers to obtain a definitive diagnosis but for quick and accessible guidance.”
Cognitive biases associated with medical decisions: a systematic review (2016, background): “avoidable hospitalizations, complications related to a procedure or medication, request of unnecessary tests, etc) and help attenuate medical errors [3, 68, 69].”
Improving Diagnosis in Health Care (2015, unknown): “What is known Postmortem examinations have been described as an important method for detecting diagnostic errors (Berner and Graber, 2008; Graber, 2013).”
A comparative study of artificial intelligence and human doctors for the purpose of triage and diagnosis (2018, result): “Irrespective of whether the true error rate lies closer to the 10-20% found in autopsy studies [Graber, 2013] or the 44% found in a study analysing the correlation of diagnostic accuracy with doctor confidence [Meyer et al.”