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Diagnostic AEs represent an important error type, and the consequences of DAEs are severe. The causes of DAEs were mostly human, with the main causes being knowledge-based mistakes and information transfer problems. Prevention strategies should focus on training physicians and on the organization of knowledge and information transfer.

BackgroundPatient record review is believed to be the most useful method for estimating the rate of adverse events among hospitalised patients. However, the method has some practical and financial disadvantages. Some of these disadvantages might be overcome by using existing reporting systems in which patient safety issues are already reported, such as incidents reported by healthcare professionals and complaints and medico-legal claims filled by patients or their relatives. The aim of the study is to examine to what extent the hospital reporting systems cover the adverse events identified by patient record review.MethodsWe conducted a retrospective study using a database from a record review study of 5375 patient records in 14 hospitals in the Netherlands. Trained nurses and physicians using a method based on the protocol of The Harvard Medical Practice Study previously reviewed the records. Four reporting systems were linked with the database of reviewed records: 1) informal and 2) formal complaints by patients/relatives, 3) medico-legal claims by patients/relatives and 4) incident reports by healthcare professionals. For each adverse event identified in patient records the equivalent was sought in these reporting systems by comparing dates and descriptions of the events. The study focussed on the number of adverse event matches, overlap of adverse events detected by different sources, preventability and severity of consequences of reported and non-reported events and sensitivity and specificity of reports.ResultsIn the sample of 5375 patient records, 498 adverse events were identified. Only 18 of the 498 (3.6%) adverse events identified by record review were found in one or more of the four reporting systems. There was some overlap: one adverse event had an equivalent in both a complaint and incident report and in three cases a patient/relative used two or three systems to complain about an adverse event. Healthcare professionals reported relatively more preventable adverse events than patients.Reports are not sensitive for adverse events nor do reports have a positive predictive value.ConclusionsIn order to detect the same adverse events as identified by patient record review, one cannot rely on the existing reporting systems within hospitals.

Diagnostic errors have emerged as a serious patient safety problem but they are hard to detect and complex to define. At the research summit of the 2013 Diagnostic Error in Medicine 6th International Conference, we convened a multidisciplinary expert panel to discuss challenges in defining and measuring diagnostic errors in real-world settings. In this paper, we synthesize these discussions and outline key research challenges in operationalizing the definition and measurement of diagnostic error. Some of these challenges include 1) difficulties in determining error when the disease or diagnosis is evolving over time and in different care settings, 2) accounting for a balance between underdiagnosis and overaggressive diagnostic pursuits, and 3) determining disease diagnosis likelihood and severity in hindsight. We also build on these discussions to describe how some of these challenges can be addressed while conducting research on measuring diagnostic error.

Background Diagnostic errors occur frequently, especially in the emergency room. Estimates about the consequences of diagnostic error vary widely and little is known about the factors predicting error. Our objectives thus was to determine the rate of discrepancy between diagnoses at hospital admission and discharge in patients presenting through the emergency room, the discrepancies’ consequences, and factors predicting them. Methods Prospective observational clinical study combined with a survey in a University-affiliated tertiary care hospital. Patients’ hospital discharge diagnosis was compared with the diagnosis at hospital admittance through the emergency room and classified as similar or discrepant according to a predefined scheme by two independent expert raters. Generalized linear mixed-effects models were used to estimate the effect of diagnostic discrepancy on mortality and length of hospital stay and to determine whether characteristics of patients, diagnosing physicians, and context predicted diagnostic discrepancy. Results 755 consecutive patients (322 [42.7%] female; mean age 65.14 years) were included. The discharge diagnosis differed substantially from the admittance diagnosis in 12.3% of cases. Diagnostic discrepancy was associated with a longer hospital stay (mean 10.29 vs. 6.90 days; Cohen’s d 0.47; 95% confidence interval 0.26 to 0.70; P = 0.002) and increased patient mortality (8 (8.60%) vs. 25(3.78%); OR 2.40; 95% CI 1.05 to 5.5 P = 0.038). A factor available at admittance that predicted diagnostic discrepancy was the diagnosing physician’s assessment that the patient presented atypically for the diagnosis assigned (OR 3.04; 95% CI 1.33–6.96; P = 0.009). Conclusions Diagnostic discrepancies are a relevant healthcare problem in patients admitted through the emergency room because they occur in every ninth patient and are associated with increased in-hospital mortality. Discrepancies are not readily predictable by fixed patient or physician characteristics; attention should focus on context. Trial registration https://bmjopen.bmj.com/content/6/5/e011585 Electronic supplementary material The online version of this article (10.1186/s13049-019-0629-z) contains supplementary material, which is available to authorized users.

BackgroundNon-technical skills, such as task management, leadership, situational awareness, communication and decision-making refer to cognitive, behavioural and social skills that contribute to safe and efficient team performance. The importance of these skills during cardiopulmonary resuscitation (CPR) is increasingly emphasised. Nonetheless, the relationship between non-technical skills and technical performance is poorly understood. We hypothesise that non-technical skills become increasingly important under stressful conditions when individuals are distracted from their tasks, and investigated the relationship between non-technical and technical skills under control conditions and when external stressors are present.MethodsIn this simulator-based randomised cross-over study, 30 anaesthesiologists and anaesthesia residents from the VU University Medical Center, Amsterdam, the Netherlands, participated in two different CPR scenarios in random order. In one scenario, external stressors (radio noise and a distractive scripted family member) were added, while the other scenario without stressors served as control condition. Non-technical performance of the team leader and technical performance of the team were measured using the ‘Anaesthetists’ Non-technical Skill’ score and a recently developed technical skills score. Analysis of variance and Pearson correlation coefficients were used for statistical analyses.ResultsNon-technical performance declined when external stressors were present (adjusted mean difference 3.9 points, 95% CI 2.4 to 5.5 points). A significant correlation between non-technical and technical performance scores was observed when external stressors were present (r=0.67, 95% CI 0.40 to 0.83, p<0.001), while no evidence for such a relationship was observed under control conditions (r=0.15, 95% CI −0.22 to 0.49, p=0.42). This was equally true for all individual domains of the non-technical performance score (task management, team working, situation awareness, decision-making).ConclusionsDuring CPR with external stressors, the team’s technical performance is related to the non-technical skills of the team leader. This may have important implications for training of CPR teams.

BackgroundMany authors have implicated cognitive biases as a primary cause of diagnostic error. If this is so, then physicians already familiar with common cognitive biases should consistently identify biases present in a clinical workup. The aim of this paper is to determine whether physicians agree on the presence or absence of particular biases in a clinical case workup and how case outcome knowledge affects bias identification.MethodsWe conducted a web survey of 37 physicians. Each participant read eight cases and listed which biases were present from a list provided. In half the cases the outcome implied a correct diagnosis; in the other half, it implied an incorrect diagnosis. We compared the number of biases identified when the outcome implied a correct or incorrect primary diagnosis. Additionally, the agreement among participants about presence or absence of specific biases was assessed.ResultsWhen the case outcome implied a correct diagnosis, an average of 1.75 cognitive biases were reported; when incorrect, 3.45 biases (F=71.3, p<0.00001). Individual biases were reported from 73% to 125% more often when an incorrect diagnosis was implied. There was no agreement on presence or absence of individual biases, with κ ranging from 0.000 to 0.044.InterpretationIndividual physicians are unable to agree on the presence or absence of individual cognitive biases. Their judgements are heavily influenced by hindsight bias; when the outcome implies a diagnostic error, twice as many biases are identified. The results present challenges for current error reduction strategies based on identification of cognitive biases.