Common contributing factors of diagnostic error: A retrospective analysis of 109 serious adverse event reports from Dutch hospitals.

INTRODUCTION: Although diagnostic errors have gained renewed focus within the patient safety domain, measuring them remains a challenge. They are often measured using methods that lack information on decision-making processes given by involved physicians (eg, record reviews). The current study analyses serious adverse event (SAE) reports from Dutch hospitals to identify common contributing factors of diagnostic errors in hospital medicine. These reports are the results of thorough investigations by highly trained, independent hospital committees into the causes of SAEs. The reports include information from involved healthcare professionals and patients or family obtained through interviews. METHODS: All 71 Dutch hospitals were invited to participate in this study. Participating hospitals were asked to send four diagnostic SAE reports of their hospital. Researchers applied the Safer Dx Instrument, a Generic Analysis Framework, the Diagnostic Error Evaluation and Research (DEER) taxonomy and the Eindhoven Classification Model (ECM) to analyse reports. RESULTS: Thirty-one hospitals submitted 109 eligible reports. Diagnostic errors most often occurred in the diagnostic testing, assessment and follow-up phases according to the DEER taxonomy. The ECM showed human errors as the most common contributing factor, especially relating to communication of results, task planning and execution, and knowledge. Combining the most common DEER subcategories and the most common ECM classes showed that clinical reasoning errors resulted from failures in knowledge, and task planning and execution. Follow-up errors and errors with communication of test results resulted from failures in coordination and monitoring, often accompanied by usability issues in electronic health record design and missing protocols. DISCUSSION: Diagnostic errors occurred in every hospital type, in different specialties and with different care teams. While clinical reasoning errors remain a common problem, often caused by knowledge and skill gaps, other frequent errors in communication of test results and follow-up require different improvement measures (eg, improving technological systems).

Patient generated research priorities to improve diagnostic safety: A systematic prioritization exercise.

BACKGROUND: Most people experience a diagnostic error at least once in their lifetime. Patients' experiences with their diagnosis could provide important insights when setting research priorities to reduce diagnostic error. OBJECTIVE: Our objective was to engage patients in research agenda setting for improving diagnosis. PATIENT INVOLVEMENT: Patients were involved in generating, discussing, prioritizing, and ranking of research questions for diagnostic error reduction. METHODS: We used the prioritization methodology based on the Child Health and Nutrition Research Initiative (CHNRI). We first solicited research questions important for diagnostic error reduction from a large group of patients. Thirty questions were initially prioritized at an in-person meeting with 8 patients who were supported by 4 researchers. The resulting list was further prioritized by patients who scored questions on five predefined criteria. We then applied previously determined weights to these prioritization criteria to adjust the final prioritization score for each question, resulting in 10 highest priority research questions. RESULTS: Forty-one patients submitted 171 research questions. After prioritization, the highest priority topics included better care coordination across the diagnostic continuum and improving care transitions, improved identification and measurement of diagnostic errors and attention for implicit bias towards patients who are vulnerable to diagnostic errors. DISCUSSION: We systematically identified the top-10 patient generated research priorities for diagnostic error reduction using transparent and objective methods. Patients prioritized different research questions than researchers and therefore complemented an agenda previously generated by researchers. PRACTICAL VALUE: Research priorities identified by patients can be used by funders and researchers to conduct future research focused on reducing diagnostic errors. FUNDING: This project was funded by the Gordon and Betty Moore Foundation.

Effect on diagnostic accuracy of cognitive reasoning tools for the workplace setting: systematic review and meta-analysis.

BACKGROUND: Preventable 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. METHODS: Controlled 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. RESULTS: The 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. CONCLUSION: Cognitive 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 NUMBER: CRD42020186994.

What Can We Learn From In-Depth Analysis of Human Errors Resulting in Diagnostic Errors in the Emergency Department: An Analysis of Serious Adverse Event Reports.

INTRODUCTION: Human 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. METHODS: We 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. RESULTS: Twenty-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. DISCUSSION: The 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.

Advancing Diagnostic Safety Research: Results of a Systematic Research Priority Setting Exercise.

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.