Factors and impact of physicians' diagnostic errors in malpractice claims in Japan

Dropping the baton: Cognitive biases in emergency physicians

INTRODUCTION

Clinical medicine is becoming more complex and increasingly requires a team-based approach to deliver healthcare needs. This dispersion of cognitive reasoning across individuals, teams and systems (termed "distributed cognition") means that our understanding of cognitive biases and errors must expand beyond traditional "in-the-head" individual mental models and focus on a broader "out-in-the-world" context instead. To our knowledge, no qualitative studies thus far have examined cognitive biases in clinical settings from a team-based sociocultural perspective. Our study therefore seeks to explore how cognitive biases and errors among emergency physicians (EPs) arise due to sociocultural influences and lapses in team cognition.

METHODOLOGY

Our study team comprised four EPs of different seniorities from three different institutions and local and international academics who provided qualitative methodological guidance. We adopted a constructivist paradigm and employed a reflexive thematic analysis approach which acknowledged our researcher reflexivity. We conducted seven focus group discussions with 25 EPs who were purposively sampled for maximum variation. Our research question was: How do sociocultural factors lead to cognitive biases and medical errors among EPs?

RESULTS

Our themes coalesce around sociocultural pressures related to team psychology. In theme one, the EP is compelled by sociocultural pressures to blindly trust colleagues. In the second, the EP is obliged by cultural norms to be "nice" and neatly summarise cases into illness scripts during handovers. In the last, the EP is under immense pressure to follow conventional wisdom, comply with clinical protocols and not challenge inpatient specialists.

CONCLUSION

Cognitive biases and errors in clinical decision-making can arise due to lapses in distributed team cognition. Although this study focuses on emergency medicine, these pitfalls in team-based cognition are relevant across the entire continuum of care and across all specialties of medicine. The hyperacute nature of emergency medicine merely exacerbates and condenses these into a compressed timeframe. Indeed, similar relays are run every day in every discipline of medicine, with the same unified goal of doing the best for our patients while not committing cognitive errors and dropping the baton.

Preventable diagnostic errors of lower gastrointestinal perforation: a secondary analysis of a large-scale multicenter retrospective study

BACKGROUND

Lower gastrointestinal perforation (LGP) is an acute abdominal condition associated with a high mortality rate. Timely and accurate diagnosis is crucial. Nevertheless, a diagnostic delay has been estimated to occur in approximately one-third of the cases, and the factors contributing to this delay are yet to be clearly understood. This study aimed to evaluate the diagnostic process for appropriate clinical reasoning and availability of image interpretation in cases of delayed diagnosis of LGP.

METHODS

A secondary data analysis of a large multicenter retrospective study was conducted. This descriptive study analyzed data from a multicenter, observational study conducted across nine hospitals in Japan from January 2015 to December 2019. Out of 439 LGP cases, we included 138 cases of delayed diagnosis, excluding patients with traumatic or iatrogenic perforations, or those secondary to mesenteric ischemia, appendicitis, or diverticulitis. Clinical history and computed tomography (CT) imaging information were collected for 138 cases. Additionally, information on the clinical course of 50 cases, which were incorrectly diagnosed as gastroenteritis, constipation, or small bowel obstruction, was also collected.

RESULTS

In 42 (30.4%) cases of delayed diagnosis of LGP, CT imaging was performed before diagnosis, indicating a missed opportunity for timely diagnosis. Moreover, 33 of the 50 patients initially diagnosed with gastroenteritis, constipation, or small bowel obstruction at the time of initial examination had atypical findings that were not consistent with the initial diagnosis. Of the 138 cases with delayed diagnosis in our study, 67 cases (48.6%) showed problems with either the interpretation of CT scans or with the process of clinical reasoning.

CONCLUSION

Our retrospective study results indicate that approximately half of the cases with delayed diagnosis of LGP were due to problems in interpreting CT images or in clinical reasoning. This finding suggests that clinical reasoning and image interpretation by radiologists are important in improving the diagnostic process for LGP.

Facilitating Trust Calibration in Artificial Intelligence-Driven Diagnostic Decision Support Systems for Determining Physicians' Diagnostic Accuracy: Quasi-Experimental Study

Background

Diagnostic errors are significant problems in medical care. Despite the usefulness of artificial intelligence (AI)-based diagnostic decision support systems, the overreliance of physicians on AI-generated diagnoses may lead to diagnostic errors.

Objective

We investigated the safe use of AI-based diagnostic decision support systems with trust calibration by adjusting trust levels to match the actual reliability of AI.

Methods

A quasi-experimental study was conducted at Dokkyo Medical University, Japan, with physicians allocated (1:1) to the intervention and control groups. A total of 20 clinical cases were created based on the medical histories recorded by an AI-driven automated medical history-taking system from actual patients who visited a community-based hospital in Japan. The participants reviewed the medical histories of 20 clinical cases generated by an AI-driven automated medical history-taking system with an AI-generated list of 10 differential diagnoses and provided 1 to 3 possible diagnoses. Physicians were asked whether the final diagnosis was in the AI-generated list of 10 differential diagnoses in the intervention group, which served as the trust calibration. We analyzed the diagnostic accuracy of physicians and the correctness of the trust calibration in the intervention group. We also investigated the relationship between the accuracy of the trust calibration and the diagnostic accuracy of physicians, and the physicians' confidence level regarding the use of AI.

Results

Among the 20 physicians assigned to the intervention (n=10) and control (n=10) groups, the mean age was 30.9 (SD 3.9) years and 31.7 (SD 4.2) years, the proportion of men was 80% and 60%, and the mean postgraduate year was 5.8 (SD 2.9) and 7.2 (SD 4.6), respectively, with no significant differences. The physicians' diagnostic accuracy was 41.5% in the intervention group and 46% in the control group, with no significant difference (95% CI -0.75 to 2.55; P=.27). The overall accuracy of the trust calibration was only 61.5%, and despite correct calibration, the diagnostic accuracy was 54.5%. In the multivariate logistic regression model, the accuracy of the trust calibration was a significant contributor to the diagnostic accuracy of physicians (adjusted odds ratio 5.90, 95% CI 2.93-12.46; P<.001). The mean confidence level for AI was 72.5% in the intervention group and 45% in the control group, with no significant difference.

Conclusions

Trust calibration did not significantly improve physicians' diagnostic accuracy when considering the differential diagnoses generated by reading medical histories and the possible differential diagnosis lists of an AI-driven automated medical history-taking system. As this was a formative study, the small sample size and suboptimal trust calibration methods may have contributed to the lack of significant differences. This study highlights the need for a larger sample size and the implementation of supportive measures of trust calibration.

Diagnostic errors and characteristics of patients seen at a general internal medicine outpatient clinic with a referral for diagnosis

OBJECTIVES

Patients referred to general internal medicine (GIM) outpatient clinics may face a higher risk of diagnostic errors than non-referred patients. This difference in risk is assumed to be due to the differences in diseases and clinical presentations between referred and non-referred patients; however, clinical data regarding this issue are scarce. This study aimed to determine the frequency of diagnostic errors and compare the characteristics of referred and non-referred patients visit GIM outpatient clinics.

METHODS

This study included consecutive outpatients who visited the GIM outpatient clinic at a university hospital, with or without referral. Data on age, sex, chief complaints, referral origin, and final diagnosis were collected from medical records. The Revised Safer Dx Instrument was used to detect diagnostic errors.

RESULTS

Data from 534 referred and 599 non-referred patients were analyzed. The diagnostic error rate was higher in the referral group than that in the non-referral group (2.2 % vs. 0.5 %, p=0.01). The prevalence of abnormal test results and sensory disturbances was higher in the chief complaints, and the prevalence of musculoskeletal system disorders, connective tissue diseases, and neoplasms was higher in the final diagnoses of referred patients compared with non-referred patients. Among referred patients with diagnostic errors, abnormal test results and sensory disturbances were the two most common chief complaints, whereas neoplasia was the most common final diagnosis. Problems with data integration and interpretation were found to be the most common factors contributing to diagnostic errors.

CONCLUSIONS

Paying more attention to patients with abnormal test results and sensory disturbances and considering a higher pre-test probability for neoplasms may prevent diagnostic errors in patients referred to GIM outpatient clinics.

Heart failure misdiagnosed as acute cholecystitis: a case report

BACKGROUND

Heart failure is a clinical syndrome characterized by decreased cardiac output, leading to systemic organ hypoxia and resulting in dyspnea, pulmonary edema, organ congestion, and pleural effusion. Owing to the diverse clinical manifestations of heart failure, early diagnosis can be challenging, and misdiagnosis may occur occasionally. The use of echocardiography and blood brain natriuretic peptide can aid in obtaining a more accurate diagnosis.

CASE PRESENTATION

This article presents two case reports of patients who were misdiagnosed with acute cholecystitis. Both patients were young Mongolia males (age 26 and 39 years) who presented to the emergency department with acute upper abdominal pain, abdominal ultrasound revealed gallbladder enlargement, and blood tests suggested mild elevation of bilirubin levels. However, despite the absence of procalcitonin and C-reactive protein elevation, the patients were admitted to the general surgical department with a diagnosis of "acute cholecystitis." Both patients were given treatment for cholecystitis, but their vital signs did not improve, while later examinations confirmed heart failure. After treatment with diuretics and cardiac glycosides, both patients' symptoms were relieved.

CONCLUSION

We aim to highlight the clinical manifestations of heart failure and differentiate it from rare conditions such as acute cholecystitis. Physicians should make accurate diagnoses on the basis of physical examinations, laboratory testing and imaging, and surveys while avoiding diagnostic heuristics or mindsets. By sharing these two case reports, we hope to increase awareness to prevent potential complications and improve patient outcomes.

Risk factor analysis of medical litigation outcomes in obstetrics and gynecology: A retrospective cohort study of 344 claims in Japan

AIM

Medical errors are critical in obstetrics and gynecology (OB/GYN) and contribute to high litigation risks. However, few studies have examined system and diagnostic errors as potential preventable problems. This study aimed to enhance medical safety and reduce litigation by identifying and addressing key contributory factors.

METHODS

We retrospectively searched the national Japanese malpractice claims database for OB/GYN cases between 1961 and 2017. We evaluated provider characteristics and background information of the patients (plaintiffs). The main outcome was litigation (acceptance or rejection) in the final judgment. Using multivariable logistic regression models, we assessed the associations between medical malpractice variables (system and diagnostic errors, facility size, situation, place, time, and clinical outcomes) and litigation outcomes (acceptance).

RESULTS

Overall, 344 malpractice claims were analyzed. Among these, 277 (80.5 %) were obstetric, and 67 (19.5 %) were gynecological. Of the obstetric cases, 193 were perinatal, and 84 were maternal. Malpractice claims were accepted (OB-GYN losses) in 185 cases (53.8 %). In multivariable analyses, system errors (odds ratio 97.4, 95 % confidence interval 35.2-270.0), diagnostic errors (odds ratio 4.5, 95 % confidence interval 1.8-11.3), and clinic (odds ratio 2.7, 95 % confidence interval 1.2-4.8) had a significant statistical association with accepted claims.

CONCLUSION

System errors, diagnostic errors, and clinics were significantly associated with acceptance claims. These findings underscore the necessity of addressing modifiable factors at the physician level and within the healthcare management system to enhance patient safety and reduce litigation risks, thereby ensuring a safer and more reliable healthcare environment for patients and medical professionals.

The Big Three diagnostic errors through reflections of Japanese internists

OBJECTIVES

To analyze the Big Three diagnostic errors (malignant neoplasms, cardiovascular diseases, and infectious diseases) through internists' self-reflection on their most memorable diagnostic errors.

METHODS

This secondary analysis study, based on a web-based cross-sectional survey, recruited participants from January 21 to 31, 2019. The participants were asked to recall the most memorable diagnostic error cases in which they were primarily involved. We gathered data on internists' demographics, time to error recognition, and error location. Factors causing diagnostic errors included environmental conditions, information processing, and cognitive bias. Participants scored the significance of each contributing factor on a Likert scale (0, unimportant; 10, extremely important).

RESULTS

The Big Three comprised 54.1 % (n=372) of the 687 cases reviewed. The median physician age was 51.5 years (interquartile range, 42-58 years); 65.6 % of physicians worked in hospital settings. Delayed diagnoses were the most common among malignancies (n=64, 46 %). Diagnostic errors related to malignancy were frequent in general outpatient settings on weekdays and in the mornings and were not identified for several months following the event. Environmental factors often contributed to cardiovascular disease-related errors, which were typically identified within days in emergency departments, during night shifts, and on holidays. Information gathering and interpretation significantly impacted infectious disease diagnoses.

CONCLUSIONS

The Big Three accounted for the majority of cases recalled by Japanese internists. The most relevant contributing factors were different for each of the three categories. Addressing these errors may require a unique approach based on the disease associations.

Diagnostic Errors in Obstetric Morbidity and Mortality: Methods for and Challenges in Seeking Diagnostic Excellence

Pregnancy-related morbidity and mortality remain high across the United States, with the majority of deaths being deemed preventable. Misdiagnosis and delay in diagnosis are thought to be significant contributors to preventable harm. These diagnostic errors in obstetrics are understudied. Presented here are five selected research methods to ascertain the rates of and harm associated with diagnostic errors and the pros and cons of each. These methodologies include clinicopathologic autopsy studies, retrospective chart reviews based on clinical criteria, obstetric simulations, pregnancy-related harm case reviews, and malpractice and administrative claim database research. We then present a framework for a future study of diagnostic errors and the pursuit of diagnostic excellence in obstetrics: (1) defining and capturing diagnostic errors, (2) targeting bias in diagnostic processes, (3) implementing and monitoring safety bundles, (4) leveraging electronic health record triggers for case reviews, (5) improving diagnostic skills via simulation training, and (6) publishing error rates and reduction strategies. Evaluation of the effectiveness of this framework to ascertain diagnostic error rates, as well as its impact on patient outcomes, is required.

Effect of contextual factors on the prevalence of diagnostic errors among patients managed by physicians of the same specialty: a single-centre retrospective observational study

BACKGROUND

There has been growing recognition that contextual factors influence the physician's cognitive processes. However, given that cognitive processes may depend on the physicians' specialties, the effects of contextual factors on diagnostic errors reported in previous studies could be confounded by difference in physicians.

OBJECTIVE

This study aimed to clarify whether contextual factors such as location and consultation type affect diagnostic accuracy.

METHODS

We reviewed the medical records of 1992 consecutive outpatients consulted by physicians from the Department of Diagnostic and Generalist Medicine in a university hospital between 1 January and 31 December 2019. Diagnostic processes were assessed using the Revised Safer Dx Instrument. Patients were categorised into three groups according to contextual factors (location and consultation type): (1) referred patients with scheduled visit to the outpatient department; (2) patients with urgent visit to the outpatient department; and (3) patients with emergency visit to the emergency room. The effect of the contextual factors on the prevalence of diagnostic errors was investigated using logistic regression analysis.

RESULTS

Diagnostic errors were observed in 12 of 534 referred patients with scheduled visit to the outpatient department (2.2%), 3 of 599 patients with urgent visit to the outpatient department (0.5%) and 13 of 859 patients with emergency visit to the emergency room (1.5%). Multivariable logistic regression analysis showed a significantly higher prevalence of diagnostic errors in referred patients with scheduled visit to the outpatient department than in patients with urgent visit to the outpatient department (OR 4.08, p=0.03), but no difference between patients with emergency and urgent visit to the emergency room and outpatient department, respectively.

CONCLUSION

Contextual factors such as consultation type may affect diagnostic errors; however, since the differences in the prevalence of diagnostic errors were small, the effect of contextual factors on diagnostic accuracy may be small in physicians working in different care settings.

Definitions and Measurements for Atypical Presentations at Risk for Diagnostic Errors in Internal Medicine: Protocol for a Scoping Review

BACKGROUND

Atypical presentations have been increasingly recognized as a significant contributing factor to diagnostic errors in internal medicine. However, research to address associations between atypical presentations and diagnostic errors has not been evaluated due to the lack of widely applicable definitions and criteria for what is considered an atypical presentation.

OBJECTIVE

The aim of the study is to describe how atypical presentations are defined and measured in studies of diagnostic errors in internal medicine and use this new information to develop new criteria to identify atypical presentations at high risk for diagnostic errors.

METHODS

This study will follow an established framework for conducting scoping reviews. Inclusion criteria are developed according to the participants, concept, and context framework. This review will consider studies that fulfill all of the following criteria: include adult patients (participants); explore the association between atypical presentations and diagnostic errors using any definition, criteria, or measurement to identify atypical presentations and diagnostic errors (concept); and focus on internal medicine (context). Regarding the type of sources, this scoping review will consider quantitative, qualitative, and mixed methods study designs; systematic reviews; and opinion papers for inclusion. Case reports, case series, and conference abstracts will be excluded. The data will be extracted through MEDLINE, Web of Science, CINAHL, Embase, Cochrane Library, and Google Scholar searches. No limits will be applied to language, and papers indexed from database inception to December 31, 2023, will be included. Two independent reviewers (YH and RK) will conduct study selection and data extraction. The data extracted will include specific details about the patient characteristics (eg, age, sex, and disease), the definitions and measuring methods for atypical presentations and diagnostic errors, clinical settings (eg, department and outpatient or inpatient), type of evidence source, and the association between atypical presentations and diagnostic errors relevant to the review question. The extracted data will be presented in tabular format with descriptive statistics, allowing us to identify the key components or types of atypical presentations and develop new criteria to identify atypical presentations for future studies of diagnostic errors. Developing the new criteria will follow guidance for a basic qualitative content analysis with an inductive approach.

RESULTS

As of January 2024, a literature search through multiple databases is ongoing. We will complete this study by December 2024.

CONCLUSIONS

This scoping review aims to provide rigorous evidence to develop new criteria to identify atypical presentations at high risk for diagnostic errors in internal medicine. Such criteria could facilitate the development of a comprehensive conceptual model to understand the associations between atypical presentations and diagnostic errors in internal medicine.

TRIAL REGISTRATION

Open Science Framework; www.osf.io/27d5m.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/56933.

Effects of a 60-Minute Lecture About Diagnostic Errors for Medical Students: A Single-Center Interventional Study

INTRODUCTION

The danger of diagnostic errors exists in daily medical practice, and doctors are required to avoid such errors as much as possible. Although various factors, including cognitive, system-related, and patient-related factors, are involved in the occurrence of diagnostic errors, the percentage of doctors with insufficient medical knowledge among those factors is extremely low. Therefore, lectures on diagnostic errors might also be useful for medical students without experience working as doctors. This study investigated whether a 60-minute lecture on diagnostic errors would enable Japanese medical students to consider the factors involved in diagnostic errors and how their perceptions of diagnostic errors change.

METHODS AND MATERIALS

This single-center interventional study was conducted in October 2022 among fourth-year medical students at the Faculty of Medicine, Saga University. A questionnaire survey was conducted before and immediately after the lecture to investigate changes in the perceptions of medical students regarding diagnostic errors. One mock case question was given on an exam the day after the lecture, and the number of responses to cognitive biases and system-related and patient-related factors involved in diagnostic errors were calculated.

RESULTS

A total of 83 students were analyzed. After the lecture, medical students were significantly more aware of the existence of the concept of diagnostic error, the importance of learning about it, their willingness to continue learning about it, and their perception that learning about diagnostic errors improves their clinical skills. They were also significantly less likely to feel blame or shame over diagnostic errors. The mean numbers of responses per student for cognitive bias, system-related factors, and patient-related factors were 1.9, 3.4, and 0.9, respectively. The mean number of responses per student for all factors was 5.6.

CONCLUSION

A 60-minute lecture on diagnostic errors among medical students is beneficial because it significantly changes their perception of diagnostic errors. The results of the present study also suggest that lectures may enable Japanese medical students to consider the factors involved in diagnostic errors.

Japanese Internists' Most Memorable Diagnostic Error Cases: A Self-reflection Survey

Objective The etiologies of diagnostic errors among internal medicine physicians are unclear. To understand the causes and characteristics of diagnostic errors through reflection by those involved in them. Methods We conducted a cross-sectional study using a web-based questionnaire in Japan in January 2019. Over a 10-day period, a total of 2,220 participants agreed to participate in the study, of whom 687 internists were included in the final analysis. Participants were asked about their most memorable diagnostic error cases, in which the time course, situational factors, and psychosocial context could be most vividly recalled and where the participant provided care. We categorized diagnostic errors and identified contributing factors (i.e., situational factors, data collection/interpretation factors, and cognitive biases). Results Two-thirds of the identified diagnostic errors occurred in the clinic or emergency department. Errors were most frequently categorized as wrong diagnoses, followed by delayed and missed diagnoses. Errors most often involved diagnoses related to malignancy, circulatory system disorders, or infectious diseases. Situational factors were the most cited error cause, followed by data collection factors and cognitive bias. Common situational factors included limited consultation during office hours and weekends and barriers that prevented consultation with a supervisor or another department. Conclusion Internists reported situational factors as a significant cause of diagnostic errors. Other factors, such as cognitive biases, were also evident, although the difference in clinical settings may have influenced the proportions of the etiologies of the errors that were observed. Furthermore, wrong, delayed, and missed diagnoses may have distinctive associated cognitive biases.

Characteristics and trends of medical malpractice claims in Japan between 2006 and 2021

Classification and analysis of existing data on medical malpractice lawsuits are useful in identifying the root causes of medical errors and considering measures to prevent recurrence. No study has shown the actual prevalence of all closed malpractice claims in Japan, including the number of cases and their trial results. In this study, we illustrated the recent trends of closed malpractice claims by medical specialty, the effects of the acceptance rates and the settlements and clarified the trends and characteristics. This was a descriptive study of all closed malpractice claims data from the Supreme Court in Japan from 2006-2021. Trends and the characteristics in closed malpractice claims by medical specialty and the outcomes of the claims, including settlements and judgments, were extracted. The total number of closed medical malpractice claims was 13,340 in 16 years, with a high percentage ending in settlement (7,062, 52.9%), and when concluding in judgment (4,734, 35.3%), the medical profession (3,589, 75.8%) was favored. When compared by medical specialty, plastic surgery and obstetrics/gynecology were more likely resolved by settlement. By contrast, psychiatry cases exhibited a lower likelihood of settlement, and the percentage of cases resulting in unfavorable outcomes for patients was notably high. Furthermore, there has been a decline in the number of closed medical malpractice claims in Japan in recent years compared to the figures observed in 2006. In particular, the number of closed medical malpractice claims in obstetrics/gynecology and the number of closed medical malpractice claims per 1,000 physicians decreased significantly compared to other specialties. In conclusion, half of the closed malpractice claims were settled, and a low percentage of patients won their cases. Closed medical malpractice claims in Japan have declined in most medical specialties since 2006. Additionally, obstetrics/gynecology revealed a significant decrease since introducing the Obstetrics/Gynecology Medical Compensation System in 2009.

Diagnostic Errors in Japanese Community Hospitals and Related Factors: A Retrospective Cohort Study

Diagnostic error has recently become a crucial clinical problem and an area of intense research. However, the reality of diagnostic errors in regional hospitals remains unknown. This study aimed to clarify the reality of diagnostic errors in regional hospitals in Japan. A 10-month retrospective cohort study was conducted from January to October 2021 at the emergency room of Oda Municipal Hospital in central Shimane Prefecture, Japan. Participants were divided into groups with or without diagnostic errors, and independent variables of patient, physician, and environmental factors were analyzed using Fisher's exact test, univariate (Student's t-test and Welch's t-test), and logistic regression analyses. Diagnostic errors accounted for 13.1% of all eligible cases. Remarkably, the proportion of patients treated without oxygen support and the proportion of male patients were significantly higher in the group with diagnostic errors. Sex bias was present. Additionally, cognitive bias, a major factor in diagnostic errors, may have occurred in patients who did not require oxygen support. Numerous factors contribute to diagnostic errors; however, it is important to understand the trends in the setting of each healthcare facility and plan and implement individualized countermeasures.

The impact of system and diagnostic errors for medical litigation outcomes in orthopedic surgery

BACKGROUND

Medical litigation resulting from medical errors has a negative impact on health economics for both patients and medical practitioners. In medical litigation involving orthopedic surgeons, we aimed to identify factors contributing to plaintiff victory (orthopedic surgeon loss) through a comprehensive assessment.

METHODS

This retrospective study included 166 litigation claims against orthopedic surgeons using a litigation database in Japan. We evaluated the sex and age of the patient (plaintiff), initial diagnosis, diagnostic error, system error, the time and place of each claim that led to malpractice litigation, the institution's size, and clinical outcomes. The main outcome was the litigation outcome (acceptance or rejection) in the final judgment. Acceptance meant that the orthopedic surgeon lost the malpractice lawsuit. We conducted multivariable logistic regression analyses to examine the association of factors with an accepted claim.

RESULTS

The median age of the patients was 42 years, and 65.7% were male. The litigation outcome of 85 (51.2%) claims was acceptance. The adjusted median indemnity paid was $151,818. The multivariable analysis showed that diagnostic error, system error, sequelae, inadequate medical procedure, and follow-up observation were significantly associated with the orthopedic surgeon losing the lawsuit. In particular, claims involving diagnostic errors were more likely to be acceptance claims, in which the orthopedic surgeon lost (adjusted odds ratio 16.7, 95% confidence intervals: 4.7 to 58.0, p < 0.001). All of the claims in which the orthopedic surgeon lost were associated with a diagnostic or system error, with the most common one being system error.

CONCLUSIONS

System errors and diagnostic errors were significantly associated with acceptance claims (orthopedic surgeon losses). Since these are modifiable factors, it is necessary to take measures not only for individual physicians but also for the overall medical management system to enhance patient safety and reduce the litigation risk of orthopedic surgeons.

Medical Malpractice and Diagnostic Errors in Japanese Emergency Departments

INTRODUCTION

Emergency departments (ED) are unpredictable and prone to diagnostic errors. In addition, non-emergency specialists often provide emergency care in Japan due to a lack of certified emergency specialists, making diagnostic errors and associated medical malpractice more likely. While several studies have investigated the medical malpractice related to diagnostic errors in EDs, only a few have focused on the conditions in Japan. This study examines diagnostic error-related medical malpractice lawsuits in Japanese EDs to understand how various factors contribute to diagnostic errors.

METHODS

We retrospectively examined data on medical lawsuits from 1961-2017 to identify types of diagnostic errors and initial and final diagnoses from non-trauma and trauma cases.

RESULTS

We evaluated 108 cases, of which 74 (68.5%) were diagnostic error cases. Twenty-eight of the diagnostic errors were trauma-related (37.8%). In 86.5% of these diagnostic error cases, the relevant errors were categorized as either missed or diagnosed incorrectly; the others were attributable to diagnostic delay. Cognitive factors (including faulty perception, cognitive biases, and failed heuristics) were associated with 91.7% of errors. Intracranial hemorrhage was the most common final diagnosis of trauma-related errors (42.9%), and the most common initial diagnoses of non-trauma-related errors were upper respiratory tract infection (21.7%), non-bleeding digestive tract disease (15.2%), and primary headache (10.9%).

CONCLUSION

In this study, the first to examine medical malpractice errors in Japanese EDs, we found that such claims are often developed from initial diagnoses of common diseases, such as upper respiratory tract infection, non-hemorrhagic gastrointestinal diseases, and headaches.

Context matters: toward a multilevel perspective on context in clinical reasoning and error

Context in diagnosis and management of patients is a vexing phenomenon in medicine and health professions education that can lead to unwanted variation in clinical reasoning performance and even errors that cause patient harm. Studies have examined individual-, team-, and system-level contextual factors, but the ways in which multiple contextual factors can interact, how both distracting and enabling factors can impact performance and error, and the boundaries between context and content information are not well understood. In this paper, we use a theory-based approach to enhance our understanding of context. We introduce a multilevel perspective on context that extends prior models of clinical reasoning and propose a micro-meso-macro framework to provide a more integrated understanding of how clinical reasoning is both influenced by and emerges from multiple contextual factors. The multilevel approach can also be used to study other social phenomena in medicine such as professionalism, learning, burnout, and implicit bias. We call for a new paradigm in clinical reasoning research and education that uses multilevel theory and analysis to enhance clinical reasoning performance expertise and improve the quality of patient care.

Defining Diagnostic Error: A Scoping Review to Assess the Impact of the National Academies' Report Improving Diagnosis in Health Care

BACKGROUND

Standards for accurate and timely diagnosis are ill-defined. In 2015, the National Academies of Science, Engineering, and Medicine (NASEM) committee published a landmark report, Improving Diagnosis in Health Care , and proposed a new definition of diagnostic error, "the failure to ( a ) establish an accurate and timely explanation of the patient's health problem(s) or ( b ) communicate that explanation to the patient."

OBJECTIVE

This study aimed to explore how researchers operationalize the NASEM's definition of diagnostic error with relevance to accuracy, timeliness, and/or communication in peer-reviewed published literature.

METHODS

Using the Arskey and O'Malley's framework framework, we identified published literature from October 2015 to February 2021 using Medline and Google Scholar. We also conducted subject matter expert interviews with researchers.

RESULTS

Of 34 studies identified, 16 were analyzed and abstracted to determine how diagnostic error was operationalized and measured. Studies were grouped by theme: epidemiology, patient focus, measurement/surveillance, and clinician focus. Nine studies indicated using the NASEM definition. Of those, 5 studies also operationalized with existing definitions proposed before the NASEM report. Four studies operationalized the components of the NASEM definition and did not cite existing definitions. Three studies operationalized error using existing definitions only. Subject matter experts indicated that the NASEM definition functions as foundation for researchers to conceptualize diagnostic error.

CONCLUSIONS

The NASEM report produced a common understanding of diagnostic error that includes accuracy, timeliness, and communication. In recent peer-reviewed literature, most researchers continue to use pre-NASEM report definitions to operationalize accuracy and timeliness. The report catalyzed the use of patient-centered concepts in the definition, resulting in emerging studies focused on examining errors related to communicating diagnosis to patients.

Medical Dispute Cases Caused by Errors in Clinical Reasoning: An Investigation and Analysis

Studies that examine medical dispute cases (MDC) due to clinical reasoning (CR) are scarce in Taiwan. A retrospective analysis was undertaken to review MDC filed at four hospitals in Taiwan between 2011 and 2015. Cases were examined for the healthcare professionals involved, their relevance to CR errors, clinical specialties, and seniority. Seventy-eight MDC were identified and 57.7% of which were determined to be related to CR errors (n = 45). Among the 45 cases associated with CR errors, 82.2% (37) and 22.2% (10) were knowledge- and skill-related errors, respectively. The healthcare professionals with the most MDC were obstetrician-gynecologists (10/90, 11.1%), surgeons (8/90, 8.9%), and emergency physicians (7/90, 7.8%). The seniority of less than 5 years or lower had the highest number of attending physicians to be associated with MDC. In contrast, the highest seniority (>25 years) in the physician group and year 6 in the resident group are both shown with zero MDC. In our study, the larger hospitals had a significantly higher incidence of MDC compared to the smaller hospitals (Pearson Correlation Coefficient = 0.984, p = 0.016). An examination of MDC reveals the frequency and nature of medical errors in Taiwanese hospitals. Having identified that CR errors contributed a substantial fraction to the overall MDC, strategies to promote reasoning skills and hence reduce medico-legal issues help safeguard both patients and healthcare professionals.

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.

Cognitive biases encountered by physicians in the emergency room

Background

Diagnostic errors constitute an important medical safety problem that needs improvement, and their frequency and severity are high in emergency room settings. Previous studies have suggested that diagnostic errors occur in 0.6-12% of first-time patients in the emergency room and that one or more cognitive factors are involved in 96% of these cases. This study aimed to identify the types of cognitive biases experienced by physicians in emergency rooms in Japan.

Methods

We conducted a questionnaire survey using Nikkei Medical Online (Internet) from January 21 to January 31, 2019. Of the 159,519 physicians registered with Nikkei Medical Online when the survey was administered, those who volunteered their most memorable diagnostic error cases in the emergency room participated in the study. EZR was used for the statistical analyses.

Results

A total of 387 physicians were included. The most common cognitive biases were overconfidence (22.5%), confirmation (21.2%), availability (12.4%), and anchoring (11.4%). Of the error cases, the top five most common initial diagnoses were upper gastrointestinal disease (22.7%), trauma (14.7%), cardiovascular disease (10.9%), respiratory disease (7.5%), and primary headache (6.5%). The corresponding final diagnoses for these errors were intestinal obstruction or peritonitis (27.3%), overlooked traumas (47.4%), other cardiovascular diseases (66.7%), cardiovascular disease (41.4%), and stroke (80%), respectively.

Conclusions

A comparison of the initial and final diagnoses of cases with diagnostic errors shows that there were more cases with diagnostic errors caused by overlooking another disease in the same organ or a disease in a closely related organ.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12873-022-00708-3.

Impact of System and Diagnostic Errors on Medical Litigation Outcomes: Machine Learning-Based Prediction Models

No prediction models using use conventional logistic models and machine learning exist for medical litigation outcomes involving medical doctors. Using a logistic model and three machine learning models, such as decision tree, random forest, and light-gradient boosting machine (LightGBM), we evaluated the prediction ability for litigation outcomes among medical litigation in Japan. The prediction model with LightGBM had a good predictive ability, with an area under the curve of 0.894 (95% CI; 0.893–0.895) in all patients’ data. When evaluating the feature importance using the SHApley Additive exPlanation (SHAP) value, the system error was the most significant predictive factor in all clinical settings for medical doctors’ loss in lawsuits. The other predictive factors were diagnostic error in outpatient settings, facility size in inpatients, and procedures or surgery settings. Our prediction model is useful for estimating medical litigation outcomes.

Association of Patients' Past Misdiagnosis Experiences with Trust in Their Current Physician Among Japanese Adults

BACKGROUND

Previous qualitative research has described that previous misdiagnoses may reduce patient and their families' trust in healthcare.

OBJECTIVE

To quantify the associations between patients or family members' misdiagnosis experiences and trust in their physician.

DESIGN

Cross-sectional study.

PARTICIPANTS

Adult Japanese people with non-communicable diseases (cancer, diabetes, depression, heart disease, and connective tissue disease), recruited using a web-based panel survey.

MAIN MEASURES

Surveys assessed the patient and the patient's family's experience with misdiagnosis. Trust in the respondent's current physician was measured using the Japanese version of the 11-item Trust in Physician Scale.

KEY RESULTS

Among 661 patients (response rate 30.1%), 23.2% had a personal history of misdiagnosis and 20.4% had a family history of misdiagnosis. In a multivariable-adjusted general linear model, patients or a family members' misdiagnosis experiences were associated with lower confidence in their current physician (mean difference -4.3, 95%CI -8.1 to -0.49 and -3.2, 95%CI -6.3 to -0.05, respectively). The impact of having a personal and a family member's experience of misdiagnosis on trust was additive, with no evidence of interaction (P for interaction = 0.494).

CONCLUSIONS

The patient's or family members' misdiagnosis experiences reduced trust in the patient's current physicians. Interventions specifically targeting misdiagnosed patients are needed to restore trust.

Diagnostic error rates and associated factors for lower gastrointestinal perforation

Lower gastrointestinal perforation is rare and challenging to diagnose in patients presenting with an acute abdomen. However, no study has examined the frequency and associated factors of diagnostic errors related to lower gastrointestinal perforation. This large-scale multicenter retrospective study investigated the frequency of diagnostic errors and identified the associated factors. Factors at the level of the patient, symptoms, situation, and physician were included in the analysis. Data were collected from nine institutions, between January 1, 2015 and December 31, 2019. Timely diagnosis was defined as diagnosis at the first visit in computed tomography (CT)-capable facilities or referral to an appropriate medical institution immediately following the first visit to a non-CT-capable facility. Cases not meeting this definition were defined as diagnostic errors that resulted in delayed diagnosis. Of the 439 cases of lower gastrointestinal perforation identified, delayed diagnosis occurred in 138 cases (31.4%). Multivariate logistic regression analysis revealed a significant association between examination by a non-generalist and delayed diagnosis. Other factors showing a tendency with delayed diagnosis included presence of fever, absence of abdominal tenderness, and unavailability of urgent radiology reports. Initial misdiagnoses were mainly gastroenteritis, constipation, and small bowel obstruction. In conclusion, diagnostic errors occurred in about one-third of patients with a lower gastrointestinal perforation.

Incidence of diagnostic errors in unplanned hospitalized patients using an automated medical history-taking system with differential diagnosis generator: retrospective observational study (Preprint)

Background

Automated medical history–taking systems that generate differential diagnosis lists have been suggested to contribute to improved diagnostic accuracy. However, the effect of these systems on diagnostic errors in clinical practice remains unknown.

Objective

This study aimed to assess the incidence of diagnostic errors in an outpatient department, where an artificial intelligence (AI)–driven automated medical history–taking system that generates differential diagnosis lists was implemented in clinical practice.

Methods

We conducted a retrospective observational study using data from a community hospital in Japan. We included patients aged 20 years and older who used an AI-driven, automated medical history–taking system that generates differential diagnosis lists in the outpatient department of internal medicine for whom the index visit was between July 1, 2019, and June 30, 2020, followed by unplanned hospitalization within 14 days. The primary endpoint was the incidence of diagnostic errors, which were detected using the Revised Safer Dx Instrument by at least two independent reviewers. To evaluate the effect of differential diagnosis lists from the AI system on the incidence of diagnostic errors, we compared the incidence of these errors between a group where the AI system generated the final diagnosis in the differential diagnosis list and a group where the AI system did not generate the final diagnosis in the list; the Fisher exact test was used for comparison between these groups. For cases with confirmed diagnostic errors, further review was conducted to identify the contributing factors of these errors via discussion among three reviewers, using the Safer Dx Process Breakdown Supplement as a reference.

Results

A total of 146 patients were analyzed. A final diagnosis was confirmed for 138 patients and was observed in the differential diagnosis list from the AI system for 69 patients. Diagnostic errors occurred in 16 out of 146 patients (11.0%, 95% CI 6.4%-17.2%). Although statistically insignificant, the incidence of diagnostic errors was lower in cases where the final diagnosis was included in the differential diagnosis list from the AI system than in cases where the final diagnosis was not included in the list (7.2% vs 15.9%, P=.18).

Conclusions

The incidence of diagnostic errors among patients in the outpatient department of internal medicine who used an automated medical history–taking system that generates differential diagnosis lists seemed to be lower than the previously reported incidence of diagnostic errors. This result suggests that the implementation of an automated medical history–taking system that generates differential diagnosis lists could be beneficial for diagnostic safety in the outpatient department of internal medicine.

Malpractice Claims of Internal Medicine Involving Diagnostic and System Errors in Japan

Objectives Medical litigation resulting from diagnostic errors leads to lawsuits that are time-consuming, expensive, and psychologically burdensome. Few studies have focused on internists, who are more likely to make diagnostic errors than others, with assessments of litigation in terms of system and diagnostic errors. This study explored factors contributing to internists losing lawsuits and examined whether system or diagnostic errors were more important on the outcome. Methods Data regarding 419 lawsuits against internists closed between 1961 and 2017 were extracted from a public Japanese database. Factors affecting litigation outcomes were identified by comparative analysis focusing on system and diagnostic errors, environmental factors, and differences in initial diagnoses. Results Overall, 419 malpractice claims against internists were analyzed. The rate of lawsuits being decided against internists was high (50.1%). The primary cause of litigation was diagnostic errors (213, 54%), followed by system errors (188, 45%). The foremost initial diagnostic error was "no abnormality" (17.2%) followed by ischemic heart disease (9.6%) and malignant neoplasm (8.1%). Following cause-adjustment for loss, system errors were 21.37 times more likely to lead to a loss. Losses were 6.26 times higher for diagnostic error cases, 2.49 times higher for errors occurring at night, and 3.44 times higher when "malignant neoplasm" was the first diagnosis. Conclusions This study found that system errors strongly contributed to internists' losses. Diagnostic errors, night shifts, and initial diagnoses of malignant neoplasms also significantly affected trial outcomes. Administrators must focus on both system errors and diagnostic errors to enhance the safety of patients and reduce internists' risk exposure.

"There's got to be a better way": Global Perspectives of Medicolegal Environment and Neurosurgical Socioeconomics

Neurosurgery is considered to have one of the greatest risks of medical malpractice claims. However, medicolegal issues in neurosurgery are often disregarded and underrated worldwide. Medical errors in the neurosurgical field can be attributed to multiple factors, including highly morbid pathologies, the technical difficulty of neurosurgical procedures, and the involvement and interaction of a multidisciplinary team in the care of neurosurgical patients. Health care providers worldwide are at risk of lawsuits, sometimes even when no deviation from the standard of care had occurred in a given case. Often, governments use additional tactics to decrease the burden on compensators and extrajudicial institutions and to decrease the court's flow of irrational litigation. Continuous amendments to health care acts and newer reforms to address these issues have materialized worldwide. In the present narrative review, we have reviewed the global perspectives of medicolegal issues, with a focus on neurosurgical discipline.

Efficacy of Artificial-Intelligence-Driven Differential-Diagnosis List on the Diagnostic Accuracy of Physicians: An Open-Label Randomized Controlled Study

Background: The efficacy of artificial intelligence (AI)-driven automated medical-history-taking systems with AI-driven differential-diagnosis lists on physicians’ diagnostic accuracy was shown. However, considering the negative effects of AI-driven differential-diagnosis lists such as omission (physicians reject a correct diagnosis suggested by AI) and commission (physicians accept an incorrect diagnosis suggested by AI) errors, the efficacy of AI-driven automated medical-history-taking systems without AI-driven differential-diagnosis lists on physicians’ diagnostic accuracy should be evaluated. Objective: The present study was conducted to evaluate the efficacy of AI-driven automated medical-history-taking systems with or without AI-driven differential-diagnosis lists on physicians’ diagnostic accuracy. Methods: This randomized controlled study was conducted in January 2021 and included 22 physicians working at a university hospital. Participants were required to read 16 clinical vignettes in which the AI-driven medical history of real patients generated up to three differential diagnoses per case. Participants were divided into two groups: with and without an AI-driven differential-diagnosis list. Results: There was no significant difference in diagnostic accuracy between the two groups (57.4% vs. 56.3%, respectively; p = 0.91). Vignettes that included a correct diagnosis in the AI-generated list showed the greatest positive effect on physicians’ diagnostic accuracy (adjusted odds ratio 7.68; 95% CI 4.68–12.58; p < 0.001). In the group with AI-driven differential-diagnosis lists, 15.9% of diagnoses were omission errors and 14.8% were commission errors. Conclusions: Physicians’ diagnostic accuracy using AI-driven automated medical history did not differ between the groups with and without AI-driven differential-diagnosis lists.

Characteristics and Burden of Diagnostic Error-Related Malpractice Claims in Neurosurgery

BACKGROUND

Neurosurgery is a specialty associated with high risk of malpractice claims, which can be influenced by quality and safety of care. Diagnostic errors have gained increasing attention as a potentially preventable problem. Despite the burden of diagnostic errors, few studies have analyzed diagnostic errors in neurosurgery. We aimed to delineate the effect of diagnostic errors on malpractice claims involving a neurosurgeon.

METHODS

This retrospective study used the national Japanese malpractice claims database and included cases closed between 1961 and 2017. To examine the effect of diagnostic errors in neurosurgery, we compared diagnostic error-related claims (DERCs) with non-DERCs in indemnity, clinical outcomes, and factors relating to neurosurgeons.

RESULTS

There were 95 closed malpractice claims involving neurosurgeons during the study period. Of these claims, 36 (37.9%, 95% confidence interval [CI] 28.7%-47.9%) were DERCs. Patient death was the most common outcome associated with DERCs. Wrong, delayed, and missed diagnosis occurred in 25 (69.4%, 95% CI 53.1%-82.0%), 4 (11.1%, 95% CI 4.4%-25.3%), and 7 (19.4%, 95% CI 9.8%-35.0%) cases, respectively. The most common presenting medical condition in DERCs was stroke. Subarachnoid hemorrhage, accounting for 85.7% of stroke cases, led to 27.8% of the total indemnity paid in DERCs.

CONCLUSIONS

DERCs are associated with higher numbers of accepted claims and worse outcomes. Identifying diagnostic errors is important in neurosurgery, and countermeasures are required to reduce the burden on neurosurgeons and improve quality. This is the first study to focus on diagnostic errors in malpractice claims arising from neurosurgery.