All Content

Understanding human causes of diagnostic errors can lead to more specific targeted, specific recommendations and interventions. Using three classification instruments, researchers examined a series of serious adverse events related to diagnostic errors in the emergency department. Most of the human errors were based on intended actions and could be classified as mistakes or violations. Errors were more frequently made during the assessment and testing phases of the diagnostic process.

Diagnostic safety is an essential component of medical training. In this study, medical interns reviewed six clinical cases in which the referral letters from the general practitioner suggested a correct diagnosis, an incorrect diagnosis, or lacked a diagnostic suggestion. Researchers found that diagnostic suggestions in the referral letter did not influence subsequent diagnostic accuracy but did reduce the number of diagnoses considered.  

Diagnostic uncertainty can arise in complex clinical scenarios. This qualitative study explored how physicians in pediatric emergency and inpatient settings mitigate diagnostic uncertainty. Participants discussed common mitigation strategies, such as employing a “diagnostic pause.” The authors also noted outstanding gaps regarding communicating diagnostic uncertainty to families.

Tall Man lettering (TML) is a recommended strategy to reduce look-alike or sound-alike medication errors. This simulation study used eye tracking to investigate how of ‘tall man lettering’ impacts medication administration tasks. The researchers found that TML of prelabeled syringes led to a significant decrease in misidentified syringes and improved visual attention.

Cognitive biases can compromise decision making and contribute to poor care. In this study, nurses were provided two patient vignettes as well as associated clinical notes written using either biased or neutral language and asked to make clinical decisions regarding PRN (“as needed”) medication administration for sleep. The study identified a relationship between biased language and clinical decision-making (such as omitting patient education when administering PRN medications).

Diagnostic errors in radiology can result in treatment delays and contribute to patient harm. This article provides an overview of the common cognitive biases encountered in diagnostic radiology that can contribute to diagnostic error, and strategies to avoid these biases, such as the use of a cognitive bias mitigation strategy checklist, peer feedback, promoting a just culture, and technology approaches including artificial intelligence (AI).

Overtreatment and overuse can have unanticipated consequences, ranging from patient anxiety while awaiting test results to medical complications. The authors identify several factors that can contribute to patient overtreatment (fear of uncertainty, cognitive bias, applying low-quality evidence, and overfocusing on diagnosis). Interventions to overcome these issues include educating clinicians that uncertainty is a part of medicine and shifting to a focus on patient-centered management rather than focusing on identifying a diagnosis.

Standardized and virtual patient encounters are often used to develop medical and nursing students’ diagnostic reasoning. Through educational interventions including virtual patients, medical students increased their diagnostic accuracy compared to baseline and the completeness and efficiency in the differential diagnosis increased.

The uncertainty and pressure of the COVID-19 pandemic can introduce cognitive biases leading to diagnostic errors. Researchers asked primary care providers taking care of COVID-19 adult patients to describe cases when their clinical reasoning was “disrupted” due to the pandemic. The most common cognitive biases were anchoring bias, confirmation bias, availability bias, and cognitive dissonance.

Improving diagnosis is a patient safety priority. Using data from patient safety incident reports, malpractice claims, morbidity and mortality reports, and focus group responses, this study sought to identify “diagnostic pitfalls,” defined as clinical situations vulnerable to errors which may lead to diagnostic errors. The authors identified 21 generic diagnostic pitfall categories involving six different aspects of the clinical interaction – diagnosis and assessment, history and physical, testing, communication, follow-up, and other pitfalls (e.g., problems with inappropriate referral, urgency of the clinical situation not appreciated). The authors suggest that these findings can inform education and quality improvement efforts to anticipate and prevent future errors.

Simulation training is often used to develop clinical and nontechnical skills as part of nursing education.  This systematic review found that repeated simulation exposures can lead to gains in clinical reasoning and critical thinking. Two emerging concepts – situation awareness and teamwork – can enhance clinical reasoning within simulation. With more nursing schools turning to simulation to replace clinical site placement, which is in short supply, understanding of simulation in training is critical.

While many studies have been conducted on implicit bias in healthcare, a gap exists in nurse-specific bias and impact on disparities. This scoping review identified 215 research reports on nurse bias and/or care disparities. Most were descriptive in nature and only 12 included evaluating an intervention designed to reduce nurse-related bias. Recommendations for future research include development and testing of interventions designed to reduce nurse-related bias.

A common type of diagnostic error is availability bias, or diagnosing a patient based on experiences with past similar cases. This study examined whether an emergency physician’s recent experience of a patient presenting with shortness of breath and diagnosed with pulmonary embolism increased subsequent pulmonary embolism diagnoses. While pulmonary embolism diagnosis did increase over the following ten days, that effect did not persist over the 50 days following the first 10 days.