DIAGNOSTIC ERRORS IN RADIOLOGY: HUMAN, TECHNICAL, AND SYSTEMIC FACTORS

Abstract

DOI: https://doi.org/10.46296/yc.v10i18.0801

Abstract

Introduction: Radiology is a fundamental branch of medicine, and currently, a large part of clinical decisions depend on imaging studies, which is why radiological interpretation must be performed correctly. However, errors are inevitable, but if they are studied properly, they can be mitigated, increasing the safety of both patients and radiologists. Objective: Analyze uptodate information to understand the impact of the main diagnostic errors in radiology and the best strategies to reduce them. Methods: Narrative literature review: the information search period is based on articles published in the last five years (2020-2025) in the following databases: PubMed, PMC, Springer Nature Link, AJR Online, RSNA, Revista Sanitaria de Investigación, Sciencedirect, Elsevier, Scielo. Results:Radiological images help to make a correct medical diagnosis, but they are inevitably accompanied by diagnostic errors. Diagnostic errors are caused by multiple factors such as insufficient reading, misperception, high workload, among others. Knowing the different types of errors and their causes through feedback allows us to generate strategies and provide solutions to mitigate them and provide better quality and accuracy in terms of diagnoses. Conclusions: In radiology, safety and efficacy in diagnosis pose a major challenge due to errors that are inevitable at both the individual and multifactorial levels, such as cognitive and systemic factors. If errors and their causes can be correctly identified, strategies can be developed to reduce errors and improve diagnosis. Artificial intelligence can be of great help if incorporated as an aid in radiology.

Keywords: diagnostic, errors, radiology, classification, solutions, imaging, learning, risks.