Background Diagnostic errors are a major source of preventable harm but the science of reducing them remains underdeveloped. Objective To identify and prioritize research questions to advance the field of diagnostic safety in the next 5 years. Participants Ninety-seven researchers and 42 stakeholders were involved in the identification of the research priorities. Design We used systematic prioritization methods based on the Child Health and Nutrition Research Initiative (CHNRI) methodology. We first invited a large international group of expert researchers in various disciplines to submit research questions while considering five prioritization criteria: (1) usefulness, (2) answerability, (3) effectiveness, (4) potential for translation, and (5) maximal potential for effect on diagnostic safety. After consolidation, these questions were prioritized at an in-person expert meeting in April 2019. Top-ranked questions were subsequently reprioritized through scoring on the five prioritization criteria using an online questionnaire. We also invited non-research stakeholders to assign weights to the five criteria and then used these weights to adjust the final prioritization score for each question. Key Results Of the 207 invited researchers, 97 researchers responded and 78 submitted 333 research questions which were then consolidated. Expert meeting participants (n = 21) discussed questions in different breakout sessions and prioritized 50, which were subsequently reduced to the top 20 using the online questionnaire. The top 20 questions addressed mostly system factors (e.g., implementation and evaluation of information technologies), teamwork factors (e.g., role of nurses and other health professionals in the diagnostic process), and strategies to engage patients in the diagnostic process. Conclusions Top research priorities for advancing diagnostic safety in the short-term include strengthening systems and teams and engaging patients to support diagnosis. High-priority areas identified using these systematic methods can inform an actionable research agenda for reducing preventable diagnostic harm.
BackgroundPreventable diagnostic errors are a large burden on healthcare. Cognitive reasoning tools, that is, tools that aim to improve clinical reasoning, are commonly suggested interventions. However, quantitative estimates of tool effectiveness have been aggregated over both workplace-oriented and educational-oriented tools, leaving the impact of workplace-oriented cognitive reasoning tools alone unclear. This systematic review and meta-analysis aims to estimate the effect of cognitive reasoning tools on improving diagnostic performance among medical professionals and students, and to identify factors associated with larger improvements.MethodsControlled experimental studies that assessed whether cognitive reasoning tools improved the diagnostic accuracy of individual medical students or professionals in a workplace setting were included. Embase.com, Medline ALL via Ovid, Web of Science Core Collection, Cochrane Central Register of Controlled Trials and Google Scholar were searched from inception to 15 October 2021, supplemented with handsearching. Meta-analysis was performed using a random-effects model.ResultsThe literature search resulted in 4546 articles of which 29 studies with data from 2732 participants were included for meta-analysis. The pooled estimate showed considerable heterogeneity (I2=70%). This was reduced to I2=38% by removing three studies that offered training with the tool before the intervention effect was measured. After removing these studies, the pooled estimate indicated that cognitive reasoning tools led to a small improvement in diagnostic accuracy (Hedges’ g=0.20, 95% CI 0.10 to 0.29, p<0.001). There were no significant subgroup differences.ConclusionCognitive reasoning tools resulted in small but clinically important improvements in diagnostic accuracy in medical students and professionals, although no factors could be distinguished that resulted in larger improvements. Cognitive reasoning tools could be routinely implemented to improve diagnosis in practice, but going forward, more large-scale studies and evaluations of these tools in practice are needed to determine how these tools can be effectively implemented.PROSPERO registration numberCRD42020186994.
IntroductionHuman error plays a vital role in diagnostic errors in the emergency department. A thorough analysis of these human errors, using information-rich reports of serious adverse events (SAEs), could help to better study and understand the causes of these errors and formulate more specific recommendations.MethodsWe studied 23 SAE reports of diagnostic events in emergency departments of Dutch general hospitals and identified human errors. Two researchers independently applied the Safer Dx Instrument, Diagnostic Error Evaluation and Research Taxonomy, and the Model of Unsafe acts to analyze reports.ResultsTwenty-one reports contained a diagnostic error, in which we identified 73 human errors, which were mainly based on intended actions (n = 69) and could be classified as mistakes (n = 56) or violations (n = 13). Most human errors occurred during the assessment and testing phase of the diagnostic process.DiscussionThe combination of different instruments and information-rich SAE reports allowed for a deeper understanding of the mechanisms underlying diagnostic error. Results indicated that errors occurred most often during the assessment and the testing phase of the diagnostic process. Most often, the errors could be classified as mistakes and violations, both intended actions. These types of errors are in need of different recommendations for improvement, as mistakes are often knowledge based, whereas violations often happen because of work and time pressure. These analyses provided valuable insights for more overarching recommendations to improve diagnostic safety and would be recommended to use in future research and analysis of (serious) adverse events.
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