CODEX Digest 02.26.26

Patient views on safety reveal important aspects of diagnostic performance. This single-center cross-sectional study found generally positive perceptions but identified key disparities by gender, age, and emergency department stay length, suggesting improved communication is needed for nurses to address patient understanding and safety.

AI can enhance diagnostic accuracy, but direct comparisons with radiologists are limited. This study reviews cohorts from the Netherlands and US, finding that AI significantly outperformed radiologists in detecting pancreatic ductal adenocarcinoma on routine CT scans, suggesting potential for earlier cancer detection and better patient outcomes.

Chronic obstructive pulmonary disease (COPD) is often misdiagnosed, but little is known about its long-term outcomes. This retrospective Chinese study using US survey data finds that patients with both underdiagnosis and overdiagnosis of COPD had higher disease burden and mortality. The authors recommend spirometry as a standard screening approach that supports diagnostic accuracy.

Clinical reasoning involves the application and reinterpretation of data and information throughout the diagnostic process to determine a patient’s condition. This textbook provides an entryway into factors affecting clinical reasoning for health professions students and educators. It discusses the future of the study of clinical reasoning and educational strategies to embed the skills needed in learners and assessment methods.

Inconsistent measurement hampers disease detection, surveillance, and public health readiness. This evidence analysis of 13 studies finds that the World Health Organization (WHO) 2014 severe acute respiratory infection (SARI) case definitions have lower sensitivity but higher specificity in children of younger ages, indicating SARI-based diagnostic accuracy may underestimate pediatric disease burden particularly for infants.

Missing ovarian cancer can seriously harm patients. In this UK study of premenopausal women with symptoms or abnormal tests, researchers compared several ways to estimate cancer risk. The commonly used method missed many cancers. The IOTA ADNEX model found far more cases, though with more false alarms, and was recommended for practice.

Tuberculosis (TB) is the world’s deadliest infectious disease. Using data reported to the World Health Organization from 111 countries, this study finds that many people tested for TB are diagnosed incorrectly. In 2023, about 2 million people may have been told they had TB when they did not, while about 1 million with TB were missed. Improving accuracy will likely require better bacteriological tests and less trust in symptoms assessment alone.

Diagnostic errors are a major issue in healthcare, and cognitive biases contribute to their occurrence. This Brazilian survey shows that experience and specialization influence practitioner vulnerability to availability bias. The findings underscore how knowledge and feedback help reduce bias, highlighting the importance of expertise built over time through real-life exposure to clinical challenges.

Lung cancer survival and mortality rates vary by social status. This qualitative systematic review examines qualitative evidence on how low socio-economic status contributes to delays in lung cancer diagnosis in high-income countries, focusing on societal, psychological, and systemic barriers affecting timely diagnosis.

While patients appreciate access to medical reports online, complex terminology may hinder its usefulness. This vignette study finds that AI simplification of radiology reports into plain language boosted patient comprehension and confidence, despite some trust issues and 60% still preferred the original versus AI-generated reports.

AI scribes transcribe ambient audio into organized records and should lessen clerical tasks and allow clinicians to focus more on patients. This pilot project identifies shortcomings in AI scribe content, which among others, negatively impact diagnostic prioritization, differential diagnosis specificity, and uncertainty documentation. The authors suggest seven best practices to ensure AI scribes promote thoughtful clinical practice in learners and encourage educators to help guide effective AI use.

Diagnostic confidence is understudied. This mixed-methods research finds that physicians often maintain strong confidence in their diagnostic strategies even amid uncertainty, and higher confidence correlates with improved well-being.

LLMs can accurately diagnose a broad range of conditions in simulated studies where they are provided with a clinical summary of patient information, but this study tested how well LLMs performed when patients inputted their symptoms. The researchers found that while the LLM provided an accurate differential diagnosis and triage advice on its own, the accuracy dropped dramatically when humans users provided the information.