Missed diagnosis of infectious diseases can have serious consequences for patient safety. This article describes a delayed diagnosis of disseminated tuberculosis in a patient with lung cancer and discusses the how cognitive biases and systems failures contributed to the diagnostic error.

Metacognition (e.g., when one reflects on one’s own decision and decision making) is an approach to reducing diagnostic errors. Using data from the Melanoma Pathology Study (M-PATH) and Breast Pathology Study (B-PATH), researchers assed pathologists’ metacognition by examining their diagnostic accuracy and self-confidence. Results showed pathologists with increased metacognition sensitivity were more likely to request a second opinion for incorrect diagnosis than they were for a correct diagnosis.

Studies have shown diagnostic discordance in evaluation of surgical pathology specimens. In this study, pathologists and pathology residents were asked to diagnose surgical pathology or cytopathology cases and provide a diagnosis. Most respondents provided the correct diagnosis for most of the cases; 35% of cases were wholly or partially misdiagnosed. Educational and process changes (e.g., requiring subspecialist over-read for some diagnoses) were implemented in the pathology department in response, resulting in substantial improvement in error rates.

Wrong blood in tube (WBIT) errors can result in serious diagnostic and treatment errors, but may go unrecognized by clinical staff. In this study, machine learning was used to identify potential WBIT errors which were then compared to manual review by laboratory staff. The machine learning models showed higher accuracy, sensitivity, and specificity compared to manual review. 

Black and brown patients have experienced disproportionately poorer outcomes from COVID-19 infection as compared with white patients. This study found that patients who identified as Asian, Black, or Hispanic may not have received timely diagnosis or treatment due to inaccurately measured pulse oximetry (SpO2). These inaccuracies and discrepancies should be considered in COVID outcome research as well as other respiratory illnesses that rely on SpO2 measurement for treatment.

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).

Root cause analysis is a commonly used tool to identify systems-related factors that contributed to an adverse event. This study assessed a system-based approach, (i.e., collaborative case reviews (CCR) co-led by radiology and an institutional patient safety program) to identify contributing factors and explore the strength of recommended actions in the radiology department at a large academic medical center. Stronger action items, such as standardization of processes, were implemented in 41% of events, and radiology had higher completion rates than other hospital departments.

Teleradiology - general radiologists who support several hospitals and read films remotely – can increase off-hours coverage but this approach can result in increased errors. This retrospective review examined errors and discrepancies between teleradiology findings and image interpretation from local facility radiologists. Most errors involved CT scans; the most common errors included missed fractures or dislocations and bleeding.

A shared understanding of terminology is critical to providing appropriate treatment and care. This study assessed pathologist and clinician agreement of commonly-used phrases used to describe diagnostic uncertainty in surgical pathology reports. Phrases with the strongest agreement in meaning were “diagnostic of” and “consistent with”. “Suspicious for” and “compatible with” had the weakest agreement. Standardized diagnostic terms may improve communication.

Artificial intelligence (AI) has been used and studied in multiple healthcare processes, including detecting patient deterioration and surgical decision making. This literature review focuses on studies using AI to detect breast cancer in mammography screening practice. The authors recommend additional prospective studies before using artificial intelligence in clinical practice. 

Misdiagnosis of cardiovascular conditions can lead to serious patient harm. This systematic review found that misdiagnosis of acute myocardial infarction (AMI) occurs in approximately 1-2% of cases, and AMI is commonly diagnosed as other heart conditions, musculoskeletal pain, or gastrointestinal disease. The authors suggest that there are opportunities to reduce cases of missed AMI with better education about atypical symptoms and improved training of electrocardiogram interpretation.

Diagnostic error reduction continues to be a patient safety focus. This article outlines innovative ways clinical laboratory professionals can support diagnostic excellence, such as improved communication between laboratory professionals, providers and patients.

Newly diagnosed cancer patients may request second opinions to confirm diagnosis, treatment, or prognosis. This study evaluated the pathology-specific reimbursement for cases originating at the primary site, a comprehensive cancer center, and cases originating at affiliate sites and referred to the cancer center for second opinions. Results confirmed that second opinions can reduce diagnostic errors and potentially lower costs of subsequent treatment; however, ways to improve the cost and process of receiving a second opinion should be explored.

This retrospective cohort study characterized diagnostic errors among adult patients readmitted to the hospital within 7 days of hospital discharge. Over a 12-month period, 5.6% of readmissions were found to contain at least one diagnostic error during the index admissions. These diagnostic errors were primarily related to clinician diagnostic reasoning, including failure to order needed tests, erroneous interpretation of tests, and failure to consider the correct diagnosis. The majority of the diagnostic errors resulted in some form of clinical impact, including short-term morbidity and readmissions.

This qualitative study explored how clinicians ensure optimal management of diagnostic test results, a major patient safety concern. Thematic analyses identified strategies clinicians use to enhance test result management including paper-based manual processes, cognitive reminders, and adaptive use of electronic medical record functionality.