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Diagnostic errors in paediatric emergency departments (EDs) continue to pose a significant concern, particularly given the complex and high-pressure nature of emergency care environments. These settings often involve time-sensitive decisions, incomplete information and non-specific clinical presentations, especially in children. Despite the pressing need for improvement, the epidemiology of diagnostic errors in paediatric emergency care remains insufficiently understood.
A recent multicentre study sought to address this gap by applying electronic health record (EHR)-based triggers to identify missed opportunities for improving diagnosis (MOIDs) across five academic paediatric EDs in the United States. The study employed three specific triggers— return ED visits with admission within ten days, escalation to intensive care within 24 hours of hospital admission and death within 24 hours of ED presentation—to determine the frequency, nature and contributing factors of diagnostic errors and their impact on patient outcomes.
Trigger-Based Identification of Diagnostic Errors
To detect potential diagnostic errors, the research applied three established EHR-based electronic triggers to 2019 data from the participating paediatric EDs. These sites were selected for their robust health information systems and experience in paediatric safety and quality. Trigger 1 captured unscheduled return visits that led to inpatient admission within ten days of the original ED presentation. Trigger 2 identified cases where a patient required escalation to a higher level of care, such as the intensive care unit, within 24 hours of hospital admission. Trigger 3 focused on deaths occurring within 24 hours of ED arrival or admission.
A total of 2,937 ED records met at least one of these trigger criteria. Of these, 2,786 records (95%) were determined by clinician reviewers to be very unlikely to represent a missed opportunity for diagnosis. The remaining 151 records (5%) underwent in-depth chart review using the Revised Safer Dx Instrument, a structured tool designed to identify the presence of MOIDs based on clinical documentation and case features. Among the reviewed charts, 76 (50.3%) were found to contain a diagnostic error, resulting in an overall MOID rate of 2.6% in the cohort. MOIDs were most frequent in cases identified by Trigger 1, with a rate of 3.0%, followed by Trigger 2 at 1.9%. No MOIDs were found among the records flagged by Trigger 3.
Nature of Diagnostic Errors and Patient Harm
The types of conditions most commonly missed included brain lesions, infections or haemorrhage, pneumonia and lung abscess and appendicitis. These diagnoses often have nonspecific early symptoms, making timely recognition in a busy ED environment particularly challenging. In over half of the MOID cases (54%), the diagnostic error was associated with harm to the patient, as assessed using a standardised severity classification tool. These findings suggest that diagnostic errors in paediatric emergency settings are not only measurable but also clinically meaningful.
The application of the Revised Safer Dx Instrument allowed reviewers to evaluate whether the correct diagnosis was likely present during the initial visit or whether additional action based on available clinical information might have prevented the missed diagnosis. The study also found that cases with shorter index ED stays were more likely to involve MOIDs, indicating that insufficient time spent during the initial evaluation may contribute to diagnostic oversight. Additionally, among cases meeting Trigger 2 criteria, a greater proportion of MOIDs occurred in visits during the late afternoon or night, suggesting a potential impact of shift timing on diagnostic performance.
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Contributory Factors and Systemic Insights
The study identified a range of factors that contributed to diagnostic errors. Patient–provider interaction issues were the most frequently cited, accounting for over half (52.6%) of contributory factors. These included aspects such as incomplete clinical assessment, communication breakdowns or failure to re-evaluate evolving symptoms. Patient-related factors, such as complex or vague symptomatology, accounted for 21.1% of the cases, while system-level issues—including workflow inefficiencies and data access limitations—contributed to 13.2% of errors. Provider-specific factors, including cognitive errors in clinical reasoning or decision-making, represented 10.5% of the total. The demographic analysis also highlighted disparities; patients with MOIDs were more likely to be covered by Medicaid and more frequently identified as Hispanic.
These findings suggest that social determinants of health and structural factors may influence the likelihood of diagnostic errors. The review process was carefully standardised, and disagreements between reviewers were rare. Only six cases required consensus discussions, and none required adjudication by the broader investigative team. This consistency supports the reliability of the methodology used.
This multicentre investigation demonstrates the effectiveness of electronic triggers in identifying potentially harmful diagnostic errors in paediatric emergency departments. While the overall prevalence of confirmed MOIDs was relatively low, the clinical consequences were significant, with a substantial proportion of cases resulting in patient harm. The findings highlight the diagnostic challenges inherent in paediatric emergency care and the value of structured tools like the Revised Safer Dx Instrument in detecting errors. By focusing on specific trigger-based indicators, health systems can implement more targeted reviews and interventions aimed at improving diagnostic safety. With further refinement, electronic trigger methodologies hold promise as scalable tools for real-time monitoring and quality improvement in emergency departments, enabling better outcomes through earlier recognition of diagnostic shortcomings.
Source: Academic Emergency Medicine
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