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Researchers suggest thinking in terms of “pitfalls” would improve process.
Efforts to understand and prevent diagnostic errors in medicine usually focus on classifying these errors either as cognitive—such as knowledge gaps or biases—or systemic, such as communication breakdowns. But the authors of a recently-published study suggest that a better way to understand and address such errors is in terms of “diagnostic pitfalls”—situations in which clinicians are most likely to make to miss, delay, or make an incorrect diagnosis.
In a paper published on JAMA Network Open, the authors note the emergence of evidence suggesting most diagnostic errors result from a combination of both systemic and cognitive factors. Consequently, they sought a new framework, one that “bridges this overlap and that may provide practical, disease-specific guidance to help clinicians and organizations anticipate, identify, and mitigate what can go wrong in a diagnosis.”
To develop the framework, the researchers analyzed more than 800 cases involving diagnostic errors from outpatient practices and academic medical centers in Massachusetts from 2004 through 2016. They classified breakdowns in the diagnosis process using two separate taxonomies, one to identify what went wrong in a case and where failure occurred in the diagnostic process, and the other to identify general factors complicating the diagnostic process and the potential reasons for a mistake.
The authors used the resulting data to develop a list of the top 10 missed or delayed diagnosis by specific condition, such as colorectal cancer, myocardial infarction and sepsis, and by bodily system, such as oncology, cardiology and pulmonology. They also compiled a list of 661 “disease-specific pitfalls,” such as, ordering screening, rather than diagnostic mammogram when evaluating a breast lump.
Finally, they developed a list of 21 “generic diagnostic pitfalls” grouped into six categories, including:
Compiling a list of potential diagnostic pitfalls, the authors write, represents “an essential first step” towards enhancing doctors’ and systems’ ability to “anticipate what can go wrong and build strategies to minimize vulnerabilities associated with these pitfalls.”
An example of such a strategy, they say, would be development of decision-support interventions warning doctors in real time to avoid these errors. In addition, “specific pitfalls can be operationally defined to inform the development and deployment of electronic trigger to retrospectively examine and misunderstand their occurrence and an institution’s vulnerability to these types of missteps.”
The paper, “Characteristics of Disease-Specific and Generic Diagnostic Pitfalls” was published January 21 on JAMA Network Open.