The incidence of diagnostic error in medicine

Abstract

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.

Challenges and opportunities from the Agency for Healthcare Research and Quality (AHRQ) research summit on improving diagnosis: a proceedings review

“…A variety of methods and data sources have been used to establish incidence (e.g. autopsies, medical records, diagnostic testing audits, case reviews, malpractice claims, and voluntary reports from patients and clinicians) [1,10]. Unique insights can be gleaned from each data source; however, limitations of each preclude the possibility of deriving broader population-based estimates or ranges of diagnostic error on a national scale.…”

Use of an Expedited Review Tool to Screen for Prior Diagnostic Error in Emergency Department Patients

“…Recent studies harness the power of electronic health records (EHRs) by using "triggers" to filter data into subsets enriched with cases of diagnostic error, through selecting cases considered at higher risk for such errors [9][10][11][12][13][14]. By applying these screens to ambulatory EHRs they increased the prevalence of cases of error from 2.1% at baseline to 5.4%-20.9% in groups using screening triggers such as an unexpected return visit or hospitalization.…”

“…This last barrier limits the extensive review of records in research, with one study of diagnostic errors reporting a mean review time of 1.4 hours per record [5]. An ED based study found that 86% of the diagnostic error uncovered were preventable, suggesting that errors of this nature could be reduced significantly, if not eliminated [10].Recent studies harness the power of electronic health records (EHRs) by using "triggers" to filter data into subsets enriched with cases of diagnostic error, through selecting cases considered at higher risk for such errors [9][10][11][12][13][14]. By applying these screens to ambulatory EHRs they increased the prevalence of cases of error from 2.1% at baseline to 5.4%-20.9% in groups using screening triggers such as an unexpected return visit or hospitalization.…”

“…Claims for misdiagnosis are the leading cause of malpractice cases [3][4][5][6][7], but determining their true incidence remains difficult for multiple reasons. These include lack of agreement on definitions for diagnostic errors, or even whether these should be described more neutrally, as in "diagnostic discrepancies"; the subjective nature of determining whether a diagnosis could and should have been made earlier, with significant concerns regarding hindsight and outcome bias [8]; poor feedback systems, where diagnoses made in one encounter frequently are not connected to prior or future patient outcomes; the insensitivity of traditional approaches such as random case review, autopsy review, and malpractice claims in finding diagnostic error; and the typically time-intensive process of reviewing patient charts to identify diagnosis errors or delays [9]. This last barrier limits the extensive review of records in research, with one study of diagnostic errors reporting a mean review time of 1.4 hours per record [5].…”

Diagnostic error, overconfidence and self-knowledge

“…One analysis concludes that "while the exact prevalence of diagnostic error remains unknown, data from autopsy series spanning several decades conservatively and consistently reveal error rates of 10%-15%" (Schiff et al, 2009(Schiff et al, : 1881. Since autopsies are rare in many countries other methods of tracking diagnostic error rates have had to be employed but the overall picture is the same: diagnostic error is relatively common (Kuhn, 2002;Graber, 2013;Singh et al, 2013).…”