Misdiagnosis and underdiagnosis of multiple sclerosis: A systematic review and meta-analysis.

BACKGROUND: Diagnostic errors in multiple sclerosis (MS) impact patients and healthcare systems. OBJECTIVES: This study aimed to determine the prevalence of MS misdiagnosis and underdiagnosis, time delay in reaching a correct diagnosis and potential impact of sex. METHODS: Systematic review and meta-analysis on MS diagnostic errors. RESULTS: Out of 3910 studies, we included 62 for a qualitative synthesis and 24 for meta-analyses. Frequency of misdiagnosis (incorrect assignment of an MS diagnosis) ranged from 5% to 41%, with a pooled proportion based on six studies of 15% (95% CI: 9%-26%, n = 1621). The delay to rectify a misdiagnosis ranged from 0.3 to 15.9 years. Conversely, underdiagnosis (unrecognized diagnosis of MS) ranged from 3% to 58%, with a pooled proportion in four studies of 36% (95% CI: 20%-55%, n = 728). Pooling seven studies comprising 2851 individuals suggested a diagnostic delay to establish a correct MS diagnosis of 17.3 months (95% CI: 11.9-22.7) in patients underdiagnosed. In a meta-analysis of five studies, women were 2.1 times more likely to be misdiagnosed with MS compared to men (odds ratio, 95% CI: 1.53-2.86). CONCLUSION: This study provides summary-level evidence for the high prevalence of MS misdiagnosis and underdiagnosis. Future studies are needed to understand the causes of these diagnostic challenges in MS care.

Musculoskeletal Symptoms and Misdiagnoses in Children With Acute Myeloid Leukaemia: A Nationwide Cohort Study.

OBJECTIVES: Childhood cancer often presents with non-specific signs and symptoms that might mimic non-malignant disorders including musculoskeletal diseases, potentially leading to rheumatic and orthopaedic misdiagnoses. We aimed to compare clinical presentation, diagnostic interval and survival in paediatric acute myeloid leukaemia (AML) with and without initial musculoskeletal symptoms. METHODS: This nationwide retrospective, cohort study reviewed medical records of 144 children below 15 years diagnosed with AML in Denmark from 1996 to 2018. RESULTS: Musculoskeletal symptoms occurred in 29% (42/144) of children with AML and 8% (11/144) received an initial musculoskeletal misdiagnosis, being mainly non-specific and pain-related. The children with and without musculoskeletal symptoms did not differ markedly up to the diagnosis of AML and blood counts were affected equally in both groups. However, the children with prior musculoskeletal symptoms were more likely to have elevated levels of LDH and ferritin. Furthermore, they revealed a tendency towards a longer total interval (median 53 days vs. 32 days, p = 0.07), but the overall survival did not differ. CONCLUSION: AML should be considered as an underlying cause in children with unexplained musculoskeletal symptoms and abnormal blood counts. Concomitant elevation of LDH and ferritin should strengthen the suspicion.

Recommendations for Additional Imaging on Head and Neck Imaging Examinations: Interradiologist Variation and Associated Factors.

BACKGROUND. A paucity of relevant guidelines may lead to pronounced variation among radiologists in issuing recommendations for additional imaging (RAI) for head and neck imaging. OBJECTIVE. The purpose of this article was to explore associations of RAI for head and neck imaging examinations with examination, patient, and radiologist factors and to assess the role of individual radiologist-specific behavior in issuing such RAI. METHODS. This retrospective study included 39,200 patients (median age, 58 years; 21,855 women, 17,315 men, 30 with missing sex information) who underwent 39,200 head and neck CT or MRI examinations, interpreted by 61 radiologists, from June 1, 2021, through May 31, 2022. A natural language processing (NLP) tool with manual review of NLP results was used to identify RAI in report impressions. Interradiologist variation in RAI rates was assessed. A generalized mixed-effects model was used to assess associations between RAI and examination, patient, and radiologist factors. RESULTS. A total of 2943 (7.5%) reports contained RAI. Individual radiologist RAI rates ranged from 0.8% to 22.0% (median, 7.1%; IQR, 5.2-10.2%), representing a 27.5-fold difference between minimum and a maximum values and 1.8-fold difference between 25th and 75th percentiles. In multivariable analysis, RAI likelihood was higher for CTA than for CT examinations (OR, 1.32), for examinations that included a trainee in report generation (OR, 1.23), and for patients with self-identified race of Black or African American versus White (OR, 1.25); was lower for male than female patients (OR, 0.90); and was associated with increasing patient age (OR, 1.09 per decade) and inversely associated with radiologist years since training (OR, 0.90 per 5 years). The model accounted for 10.9% of the likelihood of RAI. Of explainable likelihood of RAI, 25.7% was attributable to examination, patient, and radiologist factors; 74.3% was attributable to radiologist-specific behavior. CONCLUSION. Interradiologist variation in RAI rates for head and neck imaging was substantial. RAI appear to be more substantially associated with individual radiologist-specific behavior than with measurable systemic factors. CLINICAL IMPACT. Quality improvement initiatives, incorporating best practices for incidental findings management, may help reduce radiologist preference-sensitive decision-making in issuing RAI for head and neck imaging and associated care variation.

Time-dependent characteristics of analytical measurands.

OBJECTIVES: Biological variation is a relevant component of diagnostic uncertainty. In addition to within-subject and between-subject variation, preanalytical variation also includes components that contribute to biological variability. Among these, daily recurring, i.e., diurnal physiological variation is of particular importance, as it contains both a random and a non-random component if the exact time of blood collection is not known. METHODS: We introduce four time-dependent characteristics (TDC) of diurnal variations for measurands to assess the relevance and extent of time dependence on the evaluation of laboratory results. RESULTS: TDC address (i) a threshold for considering diurnality, (ii) the expected relative changes per time unit, (iii) the permissible time interval between two blood collections at different daytimes within which the expected time dependence does not exceed a defined analytical uncertainty, and (iv) a rhythm-expanded reference change value. TDC and their importance will be exemplified by the measurands aspartate aminotransferase, creatine kinase, glucose, thyroid stimulating hormone, and total bilirubin. TDCs are calculated for four time slots that reflect known blood collection schedules, i.e., 07:00-09:00, 08:00-12:00, 06:00-18:00, and 00:00-24:00. The amplitude and the temporal location of the acrophase are major determinates impacting the diagnostic uncertainty and thus the medical interpretation, especially within the typical blood collection time from 07:00 to 09:00. CONCLUSIONS: We propose to check measurands for the existence of diurnal variations and, if applicable, to specify their time-dependent characteristics as outlined in our concept.

Analytical interference of intravascular contrast agents with clinical laboratory tests: a joint guideline by the ESUR Contrast Media Safety Committee and the Preanalytical Phase Working Group of the EFLM Science Committee.

The Contrast Media Safety Committee of the European Society of Urogenital Radiology has, together with the Preanalytical Phase Working Group of the EFLM Science Committee, reviewed the literature and updated its recommendations to increase awareness and provide insight into these interferences.

Cognitive Bias in the Patient Encounter: Part I. Background and significance.

Cognitive bias may lead to diagnostic error in the patient encounter. There are hundreds of different cognitive biases, but certain biases are more likely to affect patient diagnosis and management. As during morbidity and mortality rounds, retrospective evaluation of a given case, with comparison to an optimal diagnosis, can pinpoint errors in judgment and decision-making. The study of cognitive bias also illuminates how we might improve the diagnostic process. In Part 1 of this series, cognitive bias is defined and placed within the background of dual process theory, emotion, heuristics, and the more neutral term judgment and decision-making bias.

Impact of performance and information feedback on medical interns' confidence-accuracy calibration.

Diagnostic errors are a major, largely preventable, patient safety concern. Error interventions cannot feasibly be implemented for every patient that is seen. To identify cases at high risk of error, clinicians should have a good calibration between their perceived and actual accuracy. This experiment studied the impact of feedback on medical interns' calibration and diagnostic process. In a two-phase experiment, 125 medical interns from Dutch University Medical Centers were randomized to receive no feedback (control), feedback on their accuracy (performance feedback), or feedback with additional information on why a certain diagnosis was correct (information feedback) on 20 chest X-rays they diagnosed in a feedback phase. A test phase immediately followed this phase and had all interns diagnose an additional 10 X-rays without feedback. Outcome measures were confidence-accuracy calibration, diagnostic accuracy, confidence, and time to diagnose. Both feedback types improved overall confidence-accuracy calibration (R2No Feedback = 0.05, R2Performance Feedback = 0.12, R2Information Feedback = 0.19), in line with the individual improvements in diagnostic accuracy and confidence. We also report secondary analyses to examine how case difficulty affected calibration. Time to diagnose did not differ between conditions. Feedback improved interns' calibration. However, it is unclear whether this improvement reflects better confidence estimates or an improvement in accuracy. Future research should examine more experienced participants and non-visual specialties. Our results suggest that feedback is an effective intervention that could be beneficial as a tool to improve calibration, especially in cases that are not too difficult for learners.

Evaluation of a Natural Language Processing Approach to Identify Diagnostic Errors and Analysis of Safety Learning System Case Review Data: Retrospective Cohort Study.

BACKGROUND: Diagnostic errors are an underappreciated cause of preventable mortality in hospitals and pose a risk for severe patient harm and increase hospital length of stay. OBJECTIVE: This study aims to explore the potential of machine learning and natural language processing techniques in improving diagnostic safety surveillance. We conducted a rigorous evaluation of the feasibility and potential to use electronic health records clinical notes and existing case review data. METHODS: Safety Learning System case review data from 1 large health system composed of 10 hospitals in the mid-Atlantic region of the United States from February 2016 to September 2021 were analyzed. The case review outcome included opportunities for improvement including diagnostic opportunities for improvement. To supplement case review data, electronic health record clinical notes were extracted and analyzed. A simple logistic regression model along with 3 forms of logistic regression models (ie, Least Absolute Shrinkage and Selection Operator, Ridge, and Elastic Net) with regularization functions was trained on this data to compare classification performances in classifying patients who experienced diagnostic errors during hospitalization. Further, statistical tests were conducted to find significant differences between female and male patients who experienced diagnostic errors. RESULTS: In total, 126 (7.4%) patients (of 1704) had been identified by case reviewers as having experienced at least 1 diagnostic error. Patients who had experienced diagnostic error were grouped by sex: 59 (7.1%) of the 830 women and 67 (7.7%) of the 874 men. Among the patients who experienced a diagnostic error, female patients were older (median 72, IQR 66-80 vs median 67, IQR 57-76; P=.02), had higher rates of being admitted through general or internal medicine (69.5% vs 47.8%; P=.01), lower rates of cardiovascular-related admitted diagnosis (11.9% vs 28.4%; P=.02), and lower rates of being admitted through neurology department (2.3% vs 13.4%; P=.04). The Ridge model achieved the highest area under the receiver operating characteristic curve (0.885), specificity (0.797), positive predictive value (PPV; 0.24), and F1-score (0.369) in classifying patients who were at higher risk of diagnostic errors among hospitalized patients. CONCLUSIONS: Our findings demonstrate that natural language processing can be a potential solution to more effectively identifying and selecting potential diagnostic error cases for review and therefore reducing the case review burden.

Teaching medical students to apply deliberate reflection.

PURPOSE: Deliberate reflection on initial diagnosis has been found to repair diagnostic errors. We investigated the effectiveness of teaching students to use deliberate reflection on future cases and whether their usage would depend on their perception of case difficulty. METHOD: One-hundred-nineteen medical students solved cases either with deliberate-reflection or without instructions to reflect. One week later, all participants solved six cases, each with two equally likely diagnoses, but some symptoms in the case were associated with only one of the diagnoses (discriminating features). Participants provided one diagnosis and subsequently wrote down everything they remembered from it. After the first three cases, they were told that the next three would be difficult cases. Reflection was measured by the proportion of discriminating features recalled (overall; related to their provided diagnosis; related to alternative diagnosis). RESULTS: The deliberate-reflection condition recalled more features for the alternative diagnosis than the control condition (p = .013) regardless of described difficulty. They also recalled more features related to their provided diagnosis on the first three cases (p = .004), but on the last three cases (described as difficult), there was no difference. CONCLUSION: Learning deliberate reflection helped students engage in more reflective reasoning when solving future cases.

Enabling diagnostic excellence in the real world: Managing complexity, uncertainty and clinical responsibility.

Diagnostic error is a significant category within preventable patient harm, and it takes many years of effort to develop proficiency in diagnostic reasoning. One of the key challenges medical schools must address is preparing students for the complexity, uncertainty and clinical responsibility in going from student to doctor. Recognising the importance of both cognitive and systems-related factors in diagnostic accuracy, we designed the QUID Prompt (Questions to Use for Improving Diagnosis) for students to refer to at the bedside. This set of questions prompts careful consideration, analysis, and signposting of decision-making processes, to assist students in transitioning from medical school to the real-world of work and achieving diagnostic excellence in clinical settings.

Cystic Fibrosis and the Law: The Ramifications of New Treatments.

Until the discovery of the gene for cystic fibrosis (CF) in 1989, diagnostic developments were limited, and treatment focused on symptom alleviation. However, following the genetic breakthrough, some 2,000 mutations of the gene have been identified. More recently CF transmembrane conductance regulator modulator triple therapy (CFTRm) has been introduced in the form of triple therapy with ivacaftor, lumacaftor and tezacaftor (ETI), in the United States from 2019, Europe from 2020 and then Australia from 2021. The new treatment option has revolutionised both the quality of life and life expectancy of many persons diagnosed with CF. This editorial reviews major developments in the clinical care that can now be provided to patients, and reflects on the legal and ethical ramifications of the improved situation for many patients in the contexts of medical negligence, damages assessment, family law and criminal law. It also considers the difficult issues of access and equity caused by the limited availability of the triple therapy in low- and middle-income countries.

Assessing the Assessment-Developing and Deploying a Novel Tool for Evaluating Clinical Notes' Diagnostic Assessment Quality.

BACKGROUND: Ambulatory diagnostic errors are increasingly being recognized as an important quality and safety issue, and while measures of diagnostic quality have been sought, tools to evaluate diagnostic assessments in the medical record are lacking. OBJECTIVE: To develop and test a tool to measure diagnostic assessment note quality in primary care urgent encounters and identify common elements and areas for improvement in diagnostic assessment. DESIGN: Retrospective chart review of urgent care encounters at an urban academic setting. PARTICIPANTS: Primary care physicians. MAIN MEASURES: The Assessing the Assessment (ATA) instrument was evaluated for inter-rater reliability, internal consistency, and findings from its application to EHR notes. KEY RESULTS: ATA had reasonable performance characteristics (kappa 0.63, overall Cronbach's alpha 0.76). Variability in diagnostic assessment was seen in several domains. Two components of situational awareness tended to be well-documented ("Don't miss diagnoses" present in 84% of charts, red flag symptoms in 87%), while Psychosocial context was present only 18% of the time. CONCLUSIONS: The ATA tool is a promising framework for assessing and identifying areas for improvement in diagnostic assessments documented in clinical encounters.

Misdiagnosis in multiple sclerosis in a Brazilian reference center: Clinical, radiological, laboratory profile and failures in the diagnostic process-Cohort study.

BACKGROUND: Multiple sclerosis misdiagnosis remains a problem despite the well-validated McDonald 2017. For proper evaluation of errors in the diagnostic process that lead to misdiagnosis, it is adequate to incorporate patients who are already under regular follow-up at reference centers of demyelinating diseases. OBJECTIVES: To evaluate multiple sclerosis misdiagnosis in patients who are on follow-up at a reference center of demyelinating diseases in Brazil. METHODS: We designed an observational study including patients in regular follow-up, who were diagnosed with multiple sclerosis at our specialized outpatient clinic in the Hospital of Clinics in the University of Sao Paulo, from 1996 to 2021, and were reassessed for misdiagnosis in 2022. We evaluated demographic information, clinical profile, and complementary exams and classified participants as "established multiple sclerosis," "non-multiple sclerosis, diagnosed," and "non-multiple sclerosis, undiagnosed." Failures in the diagnostic process were assessed by the modified Diagnostic Error Evaluation and Research tool. RESULTS: A total of 201 patients were included. After analysis, 191/201 (95.02%) participants were confirmed as "established multiple sclerosis," 5/201 (2.49%) were defined as "non-multiple sclerosis, diagnosed," and 5/201 (2.49%) were defined as "non-multiple sclerosis, undiagnosed." CONCLUSIONS: Multiple sclerosis misdiagnosis persists in reference centers, emphasizing the need for careful interpretation of clinical findings to prevent errors.

Analytical interference of intravascular contrast agents with clinical laboratory tests: a joint guideline by the ESUR Contrast Media Safety Committee and the Preanalytical Phase Working Group of the EFLM Science Committee.

The Contrast Media Safety Committee of the European Society of Urogenital Radiology has, together with the Preanalytical Phase Working Group of the EFLM Science Committee, reviewed the literature and updated its recommendations to increase awareness and provide insight into these interferences. CLINICAL RELEVANCE STATEMENT: Contrast Media may interfere with clinical laboratory tests. Awareness of potential interference may prevent unwanted misdiagnosis. KEY POINTS: • Contrast Media may interfere with clinical laboratory tests; therefore awareness of potential interference may prevent unwanted misdiagnosis. • Clinical Laboratory tests should be performed prior to radiological imaging with contrast media or alternatively, blood or urine collection should be delayed, depending on kidney function.

Learning deliberate reflection in medical diagnosis: does learning-by-teaching help?

Deliberate reflection has been found to foster diagnostic accuracy on complex cases or under circumstances that tend to induce cognitive bias. However, it is unclear whether the procedure can also be learned and thereby autonomously applied when diagnosing future cases without instructions to reflect. We investigated whether general practice residents would learn the deliberate reflection procedure through 'learning-by-teaching' and apply it to diagnose new cases. The study was a two-phase experiment. In the learning phase, 56 general-practice residents were randomly assigned to one of two conditions. They either (1) studied examples of deliberate reflection and then explained the procedure to a fictitious peer on video; or (2) solved cases without reflection (control). In the test phase, one to three weeks later, all participants diagnosed new cases while thinking aloud. The analysis of the test phase showed no significant differences between the conditions on any of the outcome measures (diagnostic accuracy, p = .263; time to diagnose, p = .598; mental effort ratings, p = .544; confidence ratings, p = .710; proportion of contradiction units (i.e. measure of deliberate reflection), p = .544). In contrast to findings on learning-by-teaching from other domains, teaching deliberate reflection to a fictitious peer, did not increase reflective reasoning when diagnosing future cases. Potential explanations that future research might address are that either residents in the experimental condition did not apply the learned deliberate reflection procedure in the test phase, or residents in the control condition also engaged in reflection.

Diagnostic consistency between admission and discharge of pediatric cases in a tertiary teaching hospital in China.

BACKGROUND: Patient-centered, high-quality health care relies on accurate and timely diagnosis. Diagnosis is a complex, error-prone process. Prevention of errors involves understanding the cause of errors. This study investigated diagnostic discordance between admission and discharge in pediatric cases. METHODS: We retrospectively reviewed the electronic medical records of 5381 pediatric inpatients during 2017-2018 in a tertiary teaching hospital. We analyzed diagnostic consistency by comparing the first 4 digits of admission and discharge ICD-10 codes of the cases and classified them as concordant for "complete and partial match" or discordant for "no match". RESULTS: Diagnostic discordance was observed in 49.2% with the highest prevalence in infections of the nervous and respiratory systems (Ps < 0.001). Multiple (multivariable) logistic regression analysis predicted a lower risk of diagnostic discordance with older children (aOR, 95%CI: 0.94, 0.93-0.96) and a higher risk with infectious diseases (aOR, 95%CI: 1.49, 1.33-1.66) and admission by resident and attending pediatricians (aOR, 95%CI: 1.41, 1.30-1.54). Discordant cases had a higher rate of antibiotic prescription (OR, 95%CI: 2.09, 1.87-2.33), a longer duration of antibiotic use (P = 0.02), a longer length of hospital stay (P < 0.001), and higher medical expenses (P < 0.001). CONCLUSIONS: This study denotes a considerably high rate of discordance between admission and discharge diagnoses with an associated higher and longer prescription of antibiotics, a longer length of stay, and higher medical expenses among Chinese pediatric inpatient cases. Infectious diseases were identified as high-risk clinical conditions for discordance. Considering potential diagnostic and coding errors, departmental investigation of preventable diagnostic discordance is suggested for quality health care and preventing potential medicolegal consequences.

Promoting Best Practices in Assisted Human Reproduction.

OBJECTIVES: Assisted human reproduction (AHR) is a complex process of clinical, laboratory, and organizational activities that involve risk and safety. The regulation of the Canadian fertility industry is a mix of federal and provincial/territorial responsibility. Oversight of care is fragmented as patients, donors, and surrogates may each live in different jurisdictions. The Canadian Medical Protective Association (CMPA) undertook a retrospective analysis of CMPA medico-legal data to identify the contributing factors to medico-legal risks for Canadian physicians providing AHR services. METHODS: Experienced CMPA medical analysts, reviewed information from closed cases. A previously reported medical coding methodology was applied to a 5-year retrospective descriptive analysis of CMPA cases closed between 2015 and 2019, involving physicians caring for patients with infertility seeking AHR. Class action legal cases were excluded. All contributing factors were analyzed using the CMPA Contributing Factor Framework.1 Cases were de-identified and reported at the aggregate level for analysis to ensure confidentiality for both patients and health care providers. RESULTS: There were 860 gynaecology cases with comprehensive information and peer expert review. Of these, 43 cases involved patients seeking AHR. Due to the small sample size, the results presented are for descriptive purposes only. AHR cases had an unfavourable outcome for the physician in 29 cases. Diagnostic error was noted in 10 cases. The most common patient allegations were related to a breakdown in communication. Peer experts were critical of patient care in 34 cases. These were divided among provider, team, and system factors. CONCLUSIONS: Diagnostic error was the most common clinical concern. Deficient clinical decision-making and communication breakdown with the patient contributed to these errors. Enhanced clinical decision-making, through heightened situational awareness, strengthened diagnostic test follow-up, and improved communication with the health care team may reduce medico-legal complaints related to AHR and improve patient safety.

Diagnostic errors in musculoskeletal oncology and possible mitigation strategies.

The objective of this paper is to explore sources of diagnostic error in musculoskeletal oncology and potential strategies for mitigating them using case examples. As musculoskeletal tumors are often obvious, the diagnostic errors in musculoskeletal oncology are frequently cognitive. In our experience, the most encountered cognitive biases in musculoskeletal oncologic imaging are as follows: (1) anchoring bias, (2) premature closure, (3) hindsight bias, (4) availability bias, and (5) alliterative bias. Anchoring bias results from failing to adjust an early impression despite receiving additional contrary information. Premature closure is the cognitive equivalent of "satisfaction of search." Hindsight bias occurs when we retrospectively overestimate the likelihood of correctly interpreting the examination prospectively. In availability bias, the radiologist judges the probability of a diagnosis based on which diagnosis is most easily recalled. Finally, alliterative bias occurs when a prior radiologist's impression overly influences the diagnostic thinking of another radiologist on a subsequent exam. In addition to cognitive biases, it is also important for radiologists to acknowledge their feelings when making a diagnosis to recognize positive and negative impact of affect on decision making. While errors decrease with radiologist experience, the lack of application of medical knowledge is often the primary source of error rather than a deficiency of knowledge, emphasizing the need to foster clinical reasoning skills and assist cognition. Possible solutions for reducing error exist at both the individual and the system level and include (1) improvement in knowledge and experience, (2) improvement in clinical reasoning and decision-making skills, and (3) improvement in assisting cognition.

Design, implementation, and evaluation of the computer-aided clinical decision support system based on learning-to-rank: collaboration between physicians and machine learning in the differential diagnosis process.

BACKGROUND: We are researching, developing, and publishing the clinical decision support system based on learning-to-rank. The main objectives are (1) To support for differential diagnoses performed by internists and general practitioners and (2) To prevent diagnostic errors made by physicians. The main features are that "A physician inputs a patient's symptoms, findings, and test results to the system, and the system outputs a ranking list of possible diseases". METHOD: The software libraries for machine learning and artificial intelligence are TensorFlow and TensorFlow Ranking. The prediction algorithm is Learning-to-Rank with the listwise approach. The ranking metric is normalized discounted cumulative gain (NDCG). The loss functions are Approximate NDCG (A-NDCG). We evaluated the machine learning performance on k-fold cross-validation. We evaluated the differential diagnosis performance with validated cases. RESULTS: The machine learning performance of our system was much higher than that of the conventional system. The differential diagnosis performance of our system was much higher than that of the conventional system. We have shown that the clinical decision support system prevents physicians' diagnostic errors due to confirmation bias. CONCLUSIONS: We have demonstrated that the clinical decision support system is useful for supporting differential diagnoses and preventing diagnostic errors. We propose that differential diagnosis by physicians and learning-to-rank by machine has a high affinity. We found that information retrieval and clinical decision support systems have much in common (Target data, learning-to-rank, etc.). We propose that Clinical Decision Support Systems have the potential to support: (1) recall of rare diseases, (2) differential diagnoses for difficult-to-diagnoses cases, and (3) prevention of diagnostic errors. Our system can potentially evolve into an explainable clinical decision support system.

The impact and prevention of systemic and diagnostic errors in surgical malpractice claims in Japan: a retrospective cohort study.

The Surgical Patient Safety System (SURPASS) has been proven to improve patient outcomes. However, few studies have evaluated the details of litigation and its prevention in terms of systemic and diagnostic errors as potentially preventable problems. The present study explored factors associated with accepted claims (surgeon-loss). We retrospectively searched the national Japanese malpractice claims database between 1961 and 2017. Using multivariable logistic regression models, we assessed the association between medical malpractice variables (systemic and diagnostic errors, facility size, time, place, and clinical outcomes) and litigation outcomes (acceptance). We evaluated whether or not the factors associated with litigation could have been prevented with the SURPASS checklist. We identified 339 malpractice claims made against general surgeons. There were 159 (56.3%) accepted claims, and the median compensation paid was 164,381 USD. In multivariable analyses, system (odds ratio, 27.2 95% confidence interval 13.8-53.5) and diagnostic errors (odds ratio 5.3, 95% confidence interval 2.7-10.5) had a significant statistical association with accepted claims. The SURPASS checklist may have prevented 7% and 10% of the accepted claims and systemic errors, respectively. It is unclear what proportion of accepted claims indicated that general surgeon loses should be prevented from performing surgery if the SURPASS checklist were used. In conclusion, systemic and diagnostic errors were associated with accepted claims. Surgical teams should adhere to the SURPASS checklist to enhance patient safety and reduce surgeon risk.