The Causes of Errors in Clinical Reasoning: Cognitive Biases, Knowledge Deficits, and Dual Process Thinking

Using case vignettes to study the presence of outcome, hindsight, and implicit bias in acute unplanned medical care: a cross-sectional study

BACKGROUND AND IMPORTANCE

Various biases can impact decision-making and judgment of case quality in the Emergency Department (ED). Outcome and hindsight bias can lead to wrong retrospective judgment of care quality, and implicit bias can result in unjust treatment differences in the ED based on irrelevant patient characteristics.

OBJECTIVES

First, to evaluate the extent to which knowledge of an outcome influences physicians' quality of care assessment. Secondly, to examine whether patients with functional disorders receive different treatment compared to patients with a somatic past medical history.

DESIGN

A web-based cross-sectional study in which physicians received case vignettes with a case description and care provided. Physicians were informed about vignette outcomes in a randomized way (no, good, or bad outcome). Physicians rated quality of care for four case vignettes with different outcomes. Subsequently, they received two more case vignettes. Physicians were informed about the past medical history of the patient in a randomized way (somatic or functional). Physicians made treatment and diagnostic decisions for both cases.

SETTING AND PARTICIPANTS

One hundred ninety-one Dutch emergency physicians (EPs) and general practitioners (GPs) participated.

OUTCOME MEASURES AND ANALYSIS

Quality of care was rated on a Likert scale (0-5) and dichotomized as adequate (yes/no). Physicians estimated the likelihood of patients experiencing a bad outcome for hindsight bias. For the second objective, physicians decided on prescribing analgesics and additional diagnostic tests.

MAIN RESULTS

Large differences existed in rated quality of care for three out of four vignettes based on different case outcomes. For example, physicians rated the quality of care as adequate in 44% (95% CI 33-57%) for an abdominal pain case with a bad outcome, compared to 88% (95% CI 78-94%) for a good outcome, and 84% (95% CI 73-91%) for no outcome ( P  < 0.01). The estimated likelihood of a bad outcome was higher if physicians received a vignette with a bad patient outcome. Fewer diagnostic tests were performed and fewer opioids were prescribed for patients with a functional disorder.

CONCLUSION

Outcome, hindsight, and implicit bias significantly influence decision-making and care quality assessment by Dutch EPs and GPs.

'Walking together': How relationships shape physicians' clinical reasoning

INTRODUCTION

The clinical reasoning literature has increasingly considered context as an important influence on physicians' thinking. Physicians' relationships with patients, and their ongoing efforts to maintain these relationships, are important influences on how clinical reasoning is contextualised. The authors sought to understand how physicians' relationships with patients shaped their clinical reasoning.

METHODS

Drawing from constructivist grounded theory, the authors conducted semi-structured interviews with primary care physicians. Participants were asked to reflect on recent challenging clinical experiences, and probing questions were used to explore how participants attended to or leveraged relationships in conjunction with their clinical reasoning. Using constant comparison, three investigators coded transcripts, organising the data into codes and conceptual categories. The research team drew from these codes and categories to develop theory about the phenomenon of interest.

RESULTS

The authors interviewed 15 primary care physicians with a range of experience in practice and identified patient agency as a central influence on participants' clinical reasoning. Participants drew from and managed relationships with patients while attending to patients' agency in three ways. First, participants described how contextualised illness constructions enabled them to individualise their approaches to diagnosis and management. Second, participants managed tensions between enacting their typical approaches to clinical problems and adapting their approaches to foster ongoing relationships with patients. Finally, participants attended to relationships with patients' caregivers, seeing these individuals' contributions as important influences on how their clinical reasoning could be enacted within patients' unique social contexts.

CONCLUSION

Clinical reasoning is influenced in important ways by physicians' efforts to both draw from, and maintain, their relationships with patients and patients' caregivers. Such efforts create tensions between their professional standards of care and their orientations toward patient-centredness. These influences of relationships on physicians' clinical reasoning have important implications for training and clinical practice.

Diagnostic errors during perceptual learning in dermatology: a prospective cohort study of Finnish undergraduate students

BACKGROUND

Perceptual learning modules (PLMs) have been shown to significantly improve learning outcomes in teaching dermatology.

OBJECTIVES

To investigate the quantity and quality of diagnostic errors made during undergraduate PLMs and their potential implications.

METHODS

The study data were acquired from 8 successive dermatology courses (2021-23) from 142 undergraduate medical students. Digital PLMs were held before, during and after the courses. We investigated the number and distribution of diagnostic errors, differences between specific skin conditions and classified the errors based on type.

RESULTS

Diagnostic errors were not randomly distributed. Some skin conditions were almost always correctly identified, whereas a significant number of errors were made for other diagnoses. Errors were classified into one of three groups: mostly systematic errors of relevant differential diagnoses ('similarity' errors); partly systematic errors ('mixed' errors); and 'random' errors. While a significant learning effect during the repeated measures was found in accuracy (P < 0.001, η²P = 0.64), confidence (P < 0.001, η²P = 0.60) and fluency (P < 0.001, η²P = 0.16), the three categories differed in all outcome measures (all P < 0.001, all η²P > 0.47). Visual learning was more difficult for diagnoses in the similarity category (all P < 0.001, all η²P > 0.12) than for those in the mixed and random categories.

CONCLUSIONS

Error analysis of PLMs provided relevant information about learning efficacy and progression, and systematic errors in tasks and more difficult-to-learn conditions. This information could be used in the development of adaptive, individual error-based PLMs to improve learning outcomes, both in dermatology and medical education in general.

Effects of interacting with a large language model compared with a human coach on the clinical diagnostic process and outcomes among fourth-year medical students: study protocol for a prospective, randomised experiment using patient vignettes

INTRODUCTION

Versatile large language models (LLMs) have the potential to augment diagnostic decision-making by assisting diagnosticians, thanks to their ability to engage in open-ended, natural conversations and their comprehensive knowledge access. Yet the novelty of LLMs in diagnostic decision-making introduces uncertainties regarding their impact. Clinicians unfamiliar with the use of LLMs in their professional context may rely on general attitudes towards LLMs more broadly, potentially hindering thoughtful use and critical evaluation of their input, leading to either over-reliance and lack of critical thinking or an unwillingness to use LLMs as diagnostic aids. To address these concerns, this study examines the influence on the diagnostic process and outcomes of interacting with an LLM compared with a human coach, and of prior training vs no training for interacting with either of these 'coaches'. Our findings aim to illuminate the potential benefits and risks of employing artificial intelligence (AI) in diagnostic decision-making.

METHODS AND ANALYSIS

We are conducting a prospective, randomised experiment with N=158 fourth-year medical students from Charité Medical School, Berlin, Germany. Participants are asked to diagnose patient vignettes after being assigned to either a human coach or ChatGPT and after either training or no training (both between-subject factors). We are specifically collecting data on the effects of using either of these 'coaches' and of additional training on information search, number of hypotheses entertained, diagnostic accuracy and confidence. Statistical methods will include linear mixed effects models. Exploratory analyses of the interaction patterns and attitudes towards AI will also generate more generalisable knowledge about the role of AI in medicine.

ETHICS AND DISSEMINATION

The Bern Cantonal Ethics Committee considered the study exempt from full ethical review (BASEC No: Req-2023-01396). All methods will be conducted in accordance with relevant guidelines and regulations. Participation is voluntary and informed consent will be obtained. Results will be published in peer-reviewed scientific medical journals. Authorship will be determined according to the International Committee of Medical Journal Editors guidelines.

Use of diagnostic tests in elderly patients consulting the emergency department. Analysis of the emergency department and elder needs cohort (EDEN-8)

OBJECTIVE

Analyse the association between the use of diagnostic tests and the characteristics of older patients 65 years of age or more who consult the emergency department (ED).

METHODS

We performed an analysis of the EDEN cohort that includes patients who consulted 52 Spanish EDs. The association of age, sex, and ageing characteristics with the use of diagnostic tests (blood tests, electrocardiogram (ECG), microbiological cultures, X-ray, computed tomography, ultrasound, invasive techniques) was studied. The association was analysed by calculating the adjusted odds ratios (aOR) and their 95 % confidence intervals (CI) using a logistic regression model.

RESULTS

A total of 25,557 patients were analysed. There was an increase in the use of diagnostic tests based on age, with an aOR for blood test of 1.805 (95 %CI 1.671 - 1.950), ECG 1.793 (95 %CI 1.664 - 1.932) and X-ray 1.707 (95 %CI 1.583 - 1.840) in the group of 85 years or more. The use of diagnostic tests is lower in the female population. Most ageing characteristics (cognitive impairment, previous falls, polypharmacy, dependence, and comorbidity) were independently associated with increased use of diagnostic tests.

CONCLUSIONS

Age, and the characteristics of ageing itself are generally associated with a greater use of diagnostic tests in the ED.

Identifying, Understanding, and Minimizing Unconscious Cognitive Biases in Perioperative Crisis Management: A Narrative Review

Rapid clinical decision-making behavior is often based on pattern recognition and other mental shortcuts. Although such behavior is often faster than deliberative thinking, it can also lead to errors due to unconscious cognitive biases (UCBs). UCBs may contribute to inaccurate diagnoses, hamper interpersonal communication, trigger inappropriate clinical interventions, or result in management delays. The authors review the literature on UCBs and discuss their potential impact on perioperative crisis management. Using the Scale for the Assessment of Narrative Review Articles (SANRA), publications with the most relevance to UCBs in perioperative crisis management were selected for inclusion. Of the 19 UCBs that have been most investigated in the medical literature, the authors identified 9 that were judged to be clinically relevant or most frequently occurring during perioperative crisis management. Formal didactic training on concepts of deliberative thinking has had limited success in reducing the presence of UCBs during clinical decision-making. The evolution of clinical decision support tools (CDSTs) has demonstrated efficacy in improving deliberative clinical decision-making, possibly by reducing the intrusion of maladaptive UCBs and forcing reflective thinking. Anesthesiology remains a leader in perioperative crisis simulation and CDST implementation, but spearheading innovations to reduce the adverse impact of UCBs will further improve diagnostic precision and patient safety during perioperative crisis management.

Ten misconceptions regarding decision-making in critical care

Diagnostic errors are prevalent in critical care practice and are associated with patient harm and costs for providers and the healthcare system. Patient complexity, illness severity, and the urgency in initiating proper treatment all contribute to decision-making errors. Clinician-related factors such as fatigue, cognitive overload, and inexperience further interfere with effective decision-making. Cognitive science has provided insight into the clinical decision-making process that can be used to reduce error. This evidence-based review discusses ten common misconceptions regarding critical care decision-making. By understanding how practitioners make clinical decisions and examining how errors occur, strategies may be developed and implemented to decrease errors in Decision-making and improve patient outcomes.

Beyond thinking fast and slow: Implications of a transtheoretical model of clinical reasoning and error on teaching, assessment, and research

From dual process to a family of theories known collectively as situativity, both micro and macro theories of cognition inform our current understanding of clinical reasoning (CR) and error. CR is a complex process that occurs in a complex environment, and a nuanced, expansive, integrated model of these theories is necessary to fully understand how CR is performed in the present day and in the future. In this perspective, we present these individual theories along with figures and descriptive cases for purposes of comparison before exploring the implications of a transtheoretical model of these theories for teaching, assessment, and research in CR and error.

Dual process models of clinical reasoning: The central role of knowledge in diagnostic expertise

RATIONALE

Research on diagnostic reasoning has been conducted for fifty years or more. There is growing consensus that there are two distinct processes involved in human diagnostic reasoning: System 1, a rapid retrieval of possible diagnostic hypotheses, largely automatic and based to a large part on experiential knowledge, and System 2, a slower, analytical, conscious application of formal knowledge to arrive at a diagnostic conclusion. However, within this broad framework, controversy and disagreement abound. In particular, many authors have suggested that the root cause of diagnostic errors is cognitive biases originating in System 1 and propose that educating learners about the types of cognitive biases and their impact on diagnosis would have a major influence on error reduction.

AIMS AND OBJECTIVES

In the present paper, we take issue with these claims.

METHOD

We reviewed the literature to examine the extent to which this theoretical model is supported by the evidence.

RESULTS

We show that evidence derived from fundamental research in human cognition and studies in clinical medicine challenges the basic assumptions of this theory-that errors arise in System 1 processing as a consequence of cognitive biases, and are corrected by slow, deliberative analytical processing. We claim that, to the contrary, errors derive from both System 1 and System 2 reasoning, that they arise from lack of access to the appropriate knowledge, not from errors of processing, and that the two processes are not essential to the process of diagnostic reasoning.

CONCLUSIONS

The two processing modes are better understood as a consequence of the nature of the knowledge retrieved, not as independent processes.

The inseparability of context and clinical reasoning

Early descriptions of clinical reasoning have described a dual process model that relies on analytical or nonanalytical approaches to develop a working diagnosis. In this classic research, clinical reasoning is portrayed as an individual-driven cognitive process based on gathering information from the patient encounter, forming mental representations that rely on previous experience and engaging developed patterns to drive working diagnoses and management plans. Indeed, approaches to patient safety, as well as teaching and assessing clinical reasoning focus on the individual clinician, often ignoring the complexity of the system surrounding the diagnostic process. More recent theories and evidence portray clinical reasoning as a dynamic collection of processes that takes place among and between persons across clinical settings. Yet, clinical reasoning, taken as both an individual and a system process, is insufficiently supported by theories of cognition based on individual clinicals and lacks the specificity needed to describe the phenomenology of clinical reasoning. In this review, we reinforce that the modern healthcare ecosystem - with its people, processes and technology - is the context in which health care encounters and clinical reasoning take place.

Characteristics differentiating problem representation synthesis between novices and experts

BACKGROUND

Formulating a thoughtful problem representation (PR) is fundamental to sound clinical reasoning and an essential component of medical education. Aside from basic structural recommendations, little consensus exists on what characterizes high-quality PRs.

OBJECTIVES

To elucidate characteristics that distinguish PRs created by experts and novices.

METHODS

Early internal medicine residents (novices) and inpatient teaching faculty (experts) from two academic medical centers were given two written clinical vignettes and were instructed to write a PR and three-item differential diagnosis for each. Deductive content analysis described the characteristics comprising PRs. An initial codebook of characteristics was refined iteratively. The primary outcome was differences in characteristic frequencies between groups. The secondary outcome was characteristics correlating with diagnostic accuracy. Mixed-effects regression with random effects modeling compared case-level outcomes by group.

RESULTS

Overall, 167 PRs were analyzed from 30 novices and 54 experts. Experts included 0.8 fewer comorbidities (p < .01) and 0.6 more examination findings (p = .01) than novices on average. Experts were less likely to include irrelevant comorbidities (odds ratio [OR] = 0.4, 95% confidence interval [CI] = 0.2-0.8) or a diagnosis (OR = 0.3, 95% CI = 0.1-0.8) compared with novices. Experts encapsulated clinical data into higher-order terms (e.g., sepsis) than novices (p < .01) while including similar numbers of semantic qualifiers (SQs). Regardless of expertise level, PRs following a three-part structure (e.g., demographics, temporal course, and clinical syndrome) and including temporal SQs were associated with diagnostic accuracy (p < .01).

CONCLUSIONS

Compared with novices, expert PRs include less irrelevant data and synthesize information into higher-order concepts. Future studies should determine whether targeted educational interventions for PRs improve diagnostic accuracy.

The influence of context on diagnostic reasoning: A narrative synthesis of experimental findings

AIMS AND OBJECTIVES

Contextual information which is implicitly available to physicians during clinical encounters has been shown to influence diagnostic reasoning. To better understand the psychological mechanisms underlying the influence of context on diagnostic accuracy, we conducted a review of experimental research on this topic.

METHOD

We searched Web of Science, PubMed, and Scopus for relevant articles and looked for additional records by reading the references and approaching experts. We limited the review to true experiments involving physicians in which the outcome variable was the accuracy of the diagnosis.

RESULTS

The 43 studies reviewed examined two categories of contextual variables: (a) case-intrinsic contextual information and (b) case-extrinsic contextual information. Case-intrinsic information includes implicit misleading diagnostic suggestions in the disease history of the patient, or emotional volatility of the patient. Case-extrinsic or situational information includes a similar (but different) case seen previously, perceived case difficulty, or external digital diagnostic support. Time pressure and interruptions are other extrinsic influences that may affect the accuracy of a diagnosis but have produced conflicting findings.

CONCLUSION

We propose two tentative hypotheses explaining the role of context in diagnostic accuracy. According to the negative-affect hypothesis, diagnostic errors emerge when the physician's attention shifts from the relevant clinical findings to the (irrelevant) source of negative affect (for instance patient aggression) raised in a clinical encounter. The early-diagnosis-primacy hypothesis attributes errors to the extraordinary influence of the initial hypothesis that comes to the physician's mind on the subsequent collecting and interpretation of case information. Future research should test these mechanisms explicitly. Possible alternative mechanisms such as premature closure or increased production of (irrelevant) rival diagnoses in response to context deserve further scrutiny. Implications for medical education and practice are discussed.

The Effects of Displaying the Time Targets of the Manchester Triage System to Emergency Department Personnel: Prospective Crossover Study

BACKGROUND

The use of triage systems such as the Manchester Triage System (MTS) is a standard procedure to determine the sequence of treatment in emergency departments (EDs). When using the MTS, time targets for treatment are determined. These are commonly displayed in the ED information system (EDIS) to ED staff. Using measurements as targets has been associated with a decline in meeting those targets.

OBJECTIVE

This study investigated the impact of displaying time targets for treatment to physicians on processing times in the ED.

METHODS

We analyzed the effects of displaying time targets to ED staff on waiting times in a prospective crossover study, during the introduction of a new EDIS in a large regional hospital in Germany. The old information system version used a module that showed the time target determined by the MTS, while the new system version used a priority list instead. Evaluation was based on 35,167 routinely collected electronic health records from the preintervention period and 10,655 records from the postintervention period. Electronic health records were extracted from the EDIS, and data were analyzed using descriptive statistics and generalized additive models. We evaluated the effects of the intervention on waiting times and the odds of achieving timely treatment according to the time targets set by the MTS.

RESULTS

The average ED length of stay and waiting times increased when the EDIS that did not display time targets was used (average time from admission to treatment: preintervention phase=median 15, IQR 6-39 min; postintervention phase=median 11, IQR 5-23 min). However, severe cases with high acuity (as indicated by the triage score) benefited from lower waiting times (0.15 times as high as in the preintervention period for MTS1, only 0.49 as high for MTS2). Furthermore, these patients were less likely to receive delayed treatment, and we observed reduced odds of late treatment when crowding occurred.

CONCLUSIONS

Our results suggest that it is beneficial to use a priority list instead of displaying time targets to ED personnel. These time targets may lead to false incentives. Our work highlights that working better is not the same as working faster.

Lessons in clinical reasoning - pitfalls, myths, and pearls: shoulder pain as the first and only manifestation of lung cancer

OBJECTIVES

Lung cancer is the leading cause of cancer-related death and poses significant challenges in diagnosis and management. Although muscle metastases are exceedingly rare and typically not the initial clinical manifestation of neoplastic processes, their recognition is crucial for optimal patient care.

CASE PRESENTATION

We present a case report in which we identify the unique scenario of a 60-year-old man with shoulder pain and a deltoid muscle mass, initially suggestive of an undifferentiated pleomorphic sarcoma. However, further investigations, including radiological findings and muscle biopsy, revealed an unexpected primary lung adenocarcinoma. We performed a systematic literature search to identify the incidence of SMM and reflect on how to improve and build on better diagnosis for entities as atypical as this. This atypical presentation highlights the importance of recognizing and addressing cognitive biases in clinical decision-making, as acknowledging the possibility of uncommon presentations is vital. By embracing a comprehensive approach that combines imaging studies with histopathological confirmation, healthcare providers can ensure accurate prognoses and appropriate management strategies, ultimately improving patient outcomes.

CONCLUSIONS

This case serves as a reminder of the need to remain vigilant, open-minded, and aware of cognitive biases when confronted with uncommon clinical presentations, emphasizing the significance of early recognition and prompt evaluation in achieving optimal patient care.

Application of Cardiovascular Physiology to the Critically Ill Patient

OBJECTIVES

To use the ventricular pressure-volume relationship and time-varying elastance model to provide a foundation for understanding cardiovascular physiology and pathophysiology, interpreting advanced hemodynamic monitoring, and for illustrating the physiologic basis and hemodynamic effects of therapeutic interventions. We will build on this foundation by using a cardiovascular simulator to illustrate the application of these principles in the care of patients with severe sepsis, cardiogenic shock, and acute mechanical circulatory support.

DATA SOURCES

Publications relevant to the discussion of the time-varying elastance model, cardiogenic shock, and sepsis were retrieved from MEDLINE. Supporting evidence was also retrieved from MEDLINE when indicated.

STUDY SELECTION, DATA EXTRACTION, AND SYNTHESIS

Data from relevant publications were reviewed and applied as indicated.

CONCLUSIONS

The ventricular pressure-volume relationship and time-varying elastance model provide a foundation for understanding cardiovascular physiology and pathophysiology. We have built on this foundation by using a cardiovascular simulator to illustrate the application of these important principles and have demonstrated how complex pathophysiologic abnormalities alter clinical parameters used by the clinician at the bedside.

Emergency department use of an electronic differential diagnosis generator in the evaluation of critically ill patients

BACKGROUND

Accurate diagnosis is an essential component of managing critically ill emergency department (ED) patients. Electronic diagnosis generators (EDGs) are software tools which assist clinicians in their diagnosis generation; however, they have not been evaluated for use for critical ED patients. We aimed to evaluate the use of an EDG for this population to determine its impact on diagnosis generation and diagnostic testing.

METHODS

We performed an observational study on usage of an EDG in the high-acuity area of a tertiary care ED. The EDG was used by residents evaluating each patient in the area. The resident used the EDG when the case was felt to have diagnostic uncertainty and completed a data collection tool. Data were summarized by frequencies. Chi-squared or Fisher's exact tests were used to assess the association of added value of the EDG for diagnosis generation and diagnostic testing.

RESULTS

Over the 8-month study period, the EDG was utilized to evaluate 98 critical ED patients, of whom 60% were female, 7% were pediatric, and 46% were elderly. It was used most commonly for gastroenterological, infectious disease/immunologic, metabolic/renal, and neuropsychiatric presentations, and was least used for trauma presentations. Use of the EDG led to a diagnosis not initially considered in 47% of cases and led to additional diagnostic testing in 4% of cases.

CONCLUSION

EDGs have some potential to improve diagnosis in critical EM patients by expanding the differential diagnosis and, to a lesser extent, altering diagnostic testing.

The Art of Communicating Risk and Benefit to Promote Shared Decision-Making, Informed by Behavioral Economic Principles

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Where experience makes a difference: teachers' judgment accuracy and diagnostic reasoning regarding student learning characteristics

The concept of teacher professional vision suggests that experienced teachers, compared to novice teachers, might be better at making accurate judgments of students' learning characteristics, which can be explained by their advanced reasoning in diagnostic situations. This study examines experienced and novice teachers' diagnoses of different student characteristic profiles: three inconsistent profiles (overestimating, uninterested, and underestimating) and two consistent profiles (strong and struggling). We examined both experienced (n = 19 in-service mathematics teachers) and novice teachers (n = 24 pre-service mathematics teachers) to determine the extent of differences in their judgment accuracy and their diagnostic reasoning about observable cues when diagnosing student profiles while watching a lesson video. ANOVA results indicate that experienced teachers generally achieved a higher judgment accuracy in diagnosing student profiles compared to novice teachers. Moreover, epistemic network analysis of observable cues in experienced and novice teachers' diagnostic reasoning showed that, compared to novice teachers, experienced teachers make more relations between a broader spectrum of both surface cues (e.g., a student's hand-raising behavior) and deep cues (e.g., a student being interested in the subject). Experienced teachers thereby construct more comprehensive and robust reasoning compared to novice teachers. The findings highlight how professional experience shapes teachers' professional skills, such as diagnosing, and suggest strategies for enhancing teacher training.

Collaborative clinical reasoning: a scoping review

Background

Collaborative clinical reasoning (CCR) among healthcare professionals is crucial for maximizing clinical outcomes and patient safety. This scoping review explores CCR to address the gap in understanding its definition, structure, and implications.

Methods

A scoping review was undertaken to examine CCR related studies in healthcare. Medline, PsychInfo, SciVerse Scopus, and Web of Science were searched. Inclusion criteria included full-text articles published between 2011 to 2020. Search terms included cooperative, collaborative, shared, team, collective, reasoning, problem solving, decision making, combined with clinical or medicine or medical, but excluded shared decision making.

Results

A total of 24 articles were identified in the review. The review reveals a growing interest in CCR, with 14 articles emphasizing the decision-making process, five using Multidisciplinary Team-Metric for the Observation of Decision Making (MDTs-MODe), three exploring CCR theory, and two focusing on the problem-solving process. Communication, trust, and team dynamics emerge as key influencers in healthcare decision-making. Notably, only two articles provide specific CCR definitions.

Conclusions

While decision-making processes dominate CCR studies, a notable gap exists in defining and structuring CCR. Explicit theoretical frameworks, such as those proposed by Blondon et al. and Kiesewetter et al., are crucial for advancing research and understanding CCR dynamics within collaborative teams. This scoping review provides a comprehensive overview of CCR research, revealing a growing interest and diversity in the field. The review emphasizes the need for explicit theoretical frameworks, citing Blondon et al. and Kiesewetter et al. The broader landscape of interprofessional collaboration and clinical reasoning requires exploration.

Overconfidence, Time-on-Task, and Medical Errors: Is There a Relationship?

Background

Literature suggest that physicians' high level of confidence has a negative impact on medical decisions, and this may lead to medical errors. Experimental research is lacking; however, this study investigated the effects of high confidence on diagnostic accuracy.

Methods

Forty internal medicine residents from different hospitals in Saudi Arabia were divided randomly into two groups: A high-confidence group as an experimental and a low-confidence group acting as a control. Both groups solved each of eight written complex clinical vignettes. Before diagnosing these cases, the high-confidence group was led to believe that the task was easy, while the low-confidence group was presented with information from which it could deduce that the diagnostic task was difficult. Level of confidence, response time, and diagnostic accuracy were recorded.

Results

The participants in the high-confidence group had a significantly higher confidence level than those in the control group: 0.75 compared to 0.61 (maximum 1.00). However, neither time on task nor diagnostic accuracy significantly differed between the two groups.

Conclusion

In the literature, high confidence as one of common cognitive biases has a strong association with medical error. Even though the high-confidence group spent somewhat less time on the cases, suggesting potential premature decision-making, we failed to find differences in diagnostic accuracy. It is suggested that overconfidence should be studied as a personality trait rather than as a malleable characteristic.

Role of knowledge and reasoning processes as predictors of resident physicians' susceptibility to anchoring bias in diagnostic reasoning: a randomised controlled experiment

BACKGROUND

Diagnostic errors have been attributed to reasoning flaws caused by cognitive biases. While experiments have shown bias to cause errors, physicians of similar expertise differed in susceptibility to bias. Resisting bias is often said to depend on engaging analytical reasoning, disregarding the influence of knowledge. We examined the role of knowledge and reasoning mode, indicated by diagnosis time and confidence, as predictors of susceptibility to anchoring bias. Anchoring bias occurs when physicians stick to an incorrect diagnosis triggered by early salient distracting features (SDF) despite subsequent conflicting information.

METHODS

Sixty-eight internal medicine residents from two Dutch university hospitals participated in a two-phase experiment. Phase 1: assessment of knowledge of discriminating features (ie, clinical findings that discriminate between lookalike diseases) for six diseases. Phase 2 (1 week later): diagnosis of six cases of these diseases. Each case had two versions differing exclusively in the presence/absence of SDF. Each participant diagnosed three cases with SDF (SDF+) and three without (SDF-). Participants were randomly allocated to case versions. Based on phase 1 assessment, participants were split into higher knowledge or lower knowledge groups.

MAIN OUTCOME MEASUREMENTS

frequency of diagnoses associated with SDF; time to diagnose; and confidence in diagnosis.

RESULTS

While both knowledge groups performed similarly on SDF- cases, higher knowledge physicians succumbed to anchoring bias less frequently than their lower knowledge counterparts on SDF+ cases (p=0.02). Overall, physicians spent more time (p<0.001) and had lower confidence (p=0.02) on SDF+ than SDF- cases (p<0.001). However, when diagnosing SDF+ cases, the groups did not differ in time (p=0.88) nor in confidence (p=0.96).

CONCLUSIONS

Physicians apparently adopted a more analytical reasoning approach when presented with distracting features, indicated by increased time and lower confidence, trying to combat bias. Yet, extended deliberation alone did not explain the observed performance differences between knowledge groups. Success in mitigating anchoring bias was primarily predicted by knowledge of discriminating features of diagnoses.

Evaluating the clinical utility of artificial intelligence assistance and its explanation on the glioma grading task

Clinical evaluation evidence and model explainability are key gatekeepers to ensure the safe, accountable, and effective use of artificial intelligence (AI) in clinical settings. We conducted a clinical user-centered evaluation with 35 neurosurgeons to assess the utility of AI assistance and its explanation on the glioma grading task. Each participant read 25 brain MRI scans of patients with gliomas, and gave their judgment on the glioma grading without and with the assistance of AI prediction and explanation. The AI model was trained on the BraTS dataset with 88.0% accuracy. The AI explanation was generated using the explainable AI algorithm of SmoothGrad, which was selected from 16 algorithms based on the criterion of being truthful to the AI decision process. Results showed that compared to the average accuracy of 82.5±8.7% when physicians performed the task alone, physicians' task performance increased to 87.7±7.3% with statistical significance (p-value = 0.002) when assisted by AI prediction, and remained at almost the same level of 88.5±7.0% (p-value = 0.35) with the additional assistance of AI explanation. Based on quantitative and qualitative results, the observed improvement in physicians' task performance assisted by AI prediction was mainly because physicians' decision patterns converged to be similar to AI, as physicians only switched their decisions when disagreeing with AI. The insignificant change in physicians' performance with the additional assistance of AI explanation was because the AI explanations did not provide explicit reasons, contexts, or descriptions of clinical features to help doctors discern potentially incorrect AI predictions. The evaluation showed the clinical utility of AI to assist physicians on the glioma grading task, and identified the limitations and clinical usage gaps of existing explainable AI techniques for future improvement.

Interdisciplinary fetal-neonatal neurology training applies neural exposome perspectives to neurology principles and practice

An interdisciplinary fetal-neonatal neurology (FNN) program over the first 1,000 days teaches perspectives of the neural exposome that are applicable across the life span. This curriculum strengthens neonatal neurocritical care, pediatric, and adult neurology training objectives. Teaching at maternal-pediatric hospital centers optimally merges reproductive, pregnancy, and pediatric approaches to healthcare. Phenotype-genotype expressions of health or disease pathways represent a dynamic neural exposome over developmental time. The science of uncertainty applied to FNN training re-enforces the importance of shared clinical decisions that minimize bias and reduce cognitive errors. Trainees select mentoring committee participants that will maximize their learning experiences. Standardized questions and oral presentations monitor educational progress. Master or doctoral defense preparation and competitive research funding can be goals for specific individuals. FNN principles applied to practice offer an understanding of gene-environment interactions that recognizes the effects of reproductive health on the maternal-placental-fetal triad, neonate, child, and adult. Pre-conception and prenatal adversities potentially diminish life-course brain health. Endogenous and exogenous toxic stressor interplay (TSI) alters the neural exposome through maladaptive developmental neuroplasticity. Developmental disorders and epilepsy are primarily expressed during the first 1,000 days. Communicable and noncommunicable illnesses continue to interact with the neural exposome to express diverse neurologic disorders across the lifespan, particularly during the critical/sensitive time periods of adolescence and reproductive senescence. Anomalous or destructive fetal neuropathologic lesions change clinical expressions across this developmental-aging continuum. An integrated understanding of reproductive, pregnancy, placental, neonatal, childhood, and adult exposome effects offers a life-course perspective of the neural exposome. Exosome research promises improved disease monitoring and drug delivery starting during pregnancy. Developmental origins of health and disease principles applied to FNN practice anticipate neurologic diagnoses with interventions that can benefit successive generations. Addressing health care disparities in the Global South and high-income country medical deserts require constructive dialogue among stakeholders to achieve medical equity. Population health policies require a brain capital strategy that reduces the global burden of neurologic diseases by applying FNN principles and practice. This integrative neurologic care approach will prolong survival with an improved quality of life for persons across the lifespan confronted with neurological disorders.

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.

How Does the Sequence of the American Board of Surgery Examinations Impact Pass/Fail Outcomes?

OBJECTIVE

Historically, the American Board of Surgery required surgeons to pass the qualifying examination (QE) before taking the certifying examination (CE). However, in the 2020-2021 academic year, with mitigating circumstances related to COVID-19, the ABS removed this sequencing requirement to facilitate the certification process for those candidates who were negatively impacted by a QE delivery failure. This decoupling of the traditional order of exam delivery has provided a natural comparator to the traditional route and an analysis of the impact of examination sequencing on candidate performance.

METHODS

All candidates who applied for the canceled July 2020 QE were allowed to take the CE before passing the QE. The sample was then reduced to include only first-time candidates to ensure comparable groups for performance outcomes. Logistic regression was used to analyze the relationship between the order of taking the QE and the CE, controlling for other examination performance, international medical graduate status, and gender.

RESULTS

Only first-time candidates who took both examinations were compared (n=947). Examination sequence was not a significant predictor of QE pass/fail outcomes, OR=0.54; 95% CI, 0.19-1.61, P =0.26. However, examination sequence was a significant predictor of CE pass/fail outcomes, OR=2.54; 95% CI, 1.46-4.68, P =0.002.

CONCLUSIONS

This important study suggests that preparation for the QE increases the probability of passing the CE and provides evidence that knowledge may be foundational for clinical judgment. The ABS will consider these findings for examination sequencing moving forward.

An Update Summary on the Learning Sciences Within an Ophthalmic Context

Clinical reasoning, specifically diagnostic decision-making, has been a subject of fragmented literature since the 1970s, marked by diverse theories and conflicting perspectives. This article reviews the latest evidence in medical education, drawing from scientific literature, to offer ophthalmologists insights into optimal strategies for personal learning and the education of others. It explores the historical development of clinical reasoning theories, emphasising the challenges in understanding how doctors formulate diagnoses. The importance of clinical reasoning is underscored by its role in making accurate diagnoses and preventing diagnostic errors. The article delves into the dual process theory, distinguishing between type 1 and type 2 thinking and their implications for clinical decision-making. Cognitive load theory is introduced as a crucial aspect, highlighting the limited capacity of working memory and its impact on the diagnostic process. The zone of proximal development (ZPD) is explored as a framework for optimal learning environments, emphasising the importance of scaffolding and deliberate practice in skill development. The article discusses semantic competence, mental representation, and the interplay of different memory stores-semantic, episodic, and procedural-in enhancing diagnostic proficiency. Self-regulated learning (SRL) is introduced as a student-centric approach, emphasising goal setting, metacognition, and continuous improvement. Practical advice is provided for minimising cognitive errors in clinical reasoning, applying dual process theory, and considering cognitive load theory in teaching. The relevance of deliberate practice in ophthalmology, especially in a rapidly evolving field, is emphasised for continuous learning and staying updated with advancements. The article concludes by highlighting the importance of clinical supervisors in recognising and supporting trainees' self-regulated learning and understanding the principles of various teaching and learning theories. Ultimately, a profound comprehension of the science behind clinical reasoning is deemed fundamental for ophthalmologists to deliver high-quality, evidence-based care and foster critical thinking skills in the dynamic landscape of ophthalmology.

Medical competence as a multilayered construct

BACKGROUND

The conceptualisation of medical competence is central to its use in competency-based medical education. Calls for 'fixed standards' with 'flexible pathways', recommended in recent reports, require competence to be well defined. Making competence explicit and measurable has, however, been difficult, in part due to a tension between the need for standardisation and the acknowledgment that medical professionals must also be valued as unique individuals. To address these conflicting demands, a multilayered conceptualisation of competence is proposed, with implications for the definition of standards and approaches to assessment.

THE MODEL

Three layers are elaborated. This first is a core layer of canonical knowledge and skill, 'that, which every professional should possess', independent of the context of practice. The second layer is context-dependent knowledge, skill, and attitude, visible through practice in health care. The third layer of personalised competence includes personal skills, interests, habits and convictions, integrated with one's personality. This layer, discussed with reference to Vygotsky's concept of Perezhivanie, cognitive load theory, self-determination theory and Maslow's 'self-actualisation', may be regarded as the art of medicine. We propose that fully matured professional competence requires all three layers, but that the assessment of each layer is different.

IMPLICATIONS

The assessment of canonical knowledge and skills (Layer 1) can be approached with classical psychometric conditions, that is, similar tests, circumstances and criteria for all. Context-dependent medical competence (Layer 2) must be assessed differently, because conditions of assessment across candidates cannot be standardised. Here, multiple sources of information must be merged and intersubjective expert agreement should ground decisions about progression and level of clinical autonomy of trainees. Competence as the art of medicine (Layer 3) cannot be standardised and should not be assessed with the purpose of permission to practice. The pursuit of personal excellence in this level, however, can be recognised and rewarded.

Medico-legal risk of infectious disease physicians in Canada: A retrospective review

Objective

There is little known about the medico-legal risk for infectious disease specialists in Canada. The objective of this study was to identify the causes of these medico-legal risks with the goal of improving patient safety and outcomes.

Methods

A 10-year retrospective analysis of Canadian Medical Protective Association (CMPA) closed medico-legal cases from 2012 to 2021 was performed. Peer expert criticism was used to identify factors that contributed to the medico-legal cases at the provider, team, or system level, and were contrasted with the patient complaint.

Results

During the study period there were 571 infectious disease physician members of the CMPA. There were 96 patient medico-legal cases: 45 College complaints, 40 civil legal matters, and 11 hospital complaints. Ten cases were associated with severe patient harm or death. Patients were most likely to complain about perceived deficient assessments (54%), diagnostic errors (53%), inadequate monitoring or follow-up (20%), and unprofessional manner (20%). In contrast, peer experts were most critical of the areas of diagnostic assessment (20%), deficient assessment (10%), failure to perform test/intervention (8%), and failure to refer (6%).

Conclusion

While infectious disease physicians tend to have lower medico-legal risks compared to other health care providers, these risks still do exist. This descriptive study provides insights into the types of cases, presenting conditions, and patient allegations associated with their practice.

No knowledge gap in human physiology after remote teaching for second year medical students throughout the Covid-19 pandemic

The COVID-19 pandemic had a disruptive effect on higher education. A critical question is whether these changes affected students' learning outcomes. Knowledge gaps have consequences for future learning and may-in health professionals' education-also pose a threat to patient safety. Current research has shortcomings and does not allow for clear-cut interpretation. Our context is instruction in human physiology in an undergraduate medical program from high stakes end of term examinations. The sequence of imposed measures to slow the COVID-19 pandemic created a natural experiment, allowing for comparisons in performance during in-person versus remote instruction.In a two-factorial design, mode of instruction (in-person vs. remote) and mode of assessment (in-person vs. remote) were analyzed using both basic (non-parametric statistics, T-tests) and advanced statistical methods (linear mixed-effects model; resampling techniques). Test results from a total of N = 1095 s-year medical students were included in the study.We did not find empirical evidence of knowledge gaps; rather, students received comparable or higher scores during remote teaching. We interpret these findings as empirical evidence that both students and teachers adapted to pandemic disruption in a way that did not lead to knowledge gaps.We conclude that highly motivated students had no reduction in academic achievement. Moreover, we have developed an accessible digital exam system for secure, fair, and effective assessments which is sufficiently defensible for making pass/fail decisions.

Using an experiential learning model to teach clinical reasoning theory and cognitive bias: an evaluation of a first-year medical student curriculum

BACKGROUND

Most medical students entering clerkships have limited understanding of clinical reasoning concepts. The value of teaching theories of clinical reasoning and cognitive biases to first-year medical students is unknown. This study aimed to evaluate the value of explicitly teaching clinical reasoning theory and cognitive bias to first-year medical students.

METHODS

Using Kolb's experiential learning model, we introduced dual process theory, script theory, and cognitive biases in teaching clinical reasoning to first-year medical students at an academic medical center in New York City between January and June 2020. Due to the COVID-19 pandemic, instruction was transitioned to a distance learning format in March 2020. The curriculum included a series of written clinical reasoning examinations with facilitated small group discussions. Written self-assessments prompted each student to reflect on the experience, draw conclusions about their clinical reasoning, and plan for future encounters involving clinical reasoning. We evaluated the value of the curriculum using mixed-methods to analyze faculty assessments, student self-assessment questionnaires, and an end-of-curriculum anonymous questionnaire eliciting student feedback.

RESULTS

Among 318 total examinations of 106 students, 254 (80%) had a complete problem representation, while 199 (63%) of problem representations were considered concise. The most common cognitive biases described by students in their clinical reasoning were anchoring bias, availability bias, and premature closure. Four major themes emerged as valuable outcomes of the CREs as identified by students: (1) synthesis of medical knowledge; (2) enhanced ability to generate differential diagnoses; (3) development of self-efficacy related to clinical reasoning; (4) raised awareness of personal cognitive biases.

CONCLUSIONS

We found that explicitly teaching clinical reasoning theory and cognitive biases using an experiential learning model provides first-year medical students with valuable opportunities for developing knowledge, skills, and self-efficacy related to clinical reasoning.

Can degrading information about patient symptoms in vignettes alter clinical reasoning in paramedics and paramedic students? An experimental application of fuzzy trace theory

BACKGROUND

Research has shown paramedics form rapid intuitive impressions on first, meeting a patient and these impressions subsequently affected their clinical reasoning. We report an experiment where theory-based interventions are developed with the goal of reducing reliance on intuitive reasoning by paramedics and paramedic students in simulated patients.

METHOD

Australian paramedics (n = 213; 49% female) and paramedicine students (n = 83; 55% female) attending paramedic conferences completed a 2 × 2 fully between participants experiment. They saw a written clinical vignette designed to be representative of Acute Coronary Syndrome (ACS) in which key clinical information was precise or degraded (stimulus), they then either chose the single most likely diagnosis from a list, or ranked competing diagnoses (response). Outcome variables were diagnostic rate and response time.

RESULTS

There were no differences in the proportion of participants choosing ACS across the four stimulus-response conditions (0.75 [0.65, 0.84] vs 0.79 [0.68, 0.87] vs, 0.78 [0.65, 0.87] vs 0.72 [0.59, 0.82], p = 0.42) CONCLUSION: This is the first study attempting to experimentally examine clinical reasoning in paramedics using a theory-based intervention. Neither of the interventions tested succeeded in altering measures of clinical reasoning. Similar to previous research on physicians, paramedic reasoning appears robust to manipulation.

Inter- and intraindividual variability in virtual single-tooth implant positioning

OBJECTIVES

The purpose of this prospective study was to determine the inter- and intraindividual variability in virtual single-tooth implant positioning based on the level of expertise, specialty, total time spent, and the use of a prosthetic tooth setup.

MATERIALS AND METHODS

Virtual implant planning was performed on matched pre- and post-extraction intraoral scans (IOS), and cone-beam computed tomography scans of 15 patients. Twelve individual examiners, involving six novices and experts from oral surgery and prosthodontics positioned the implants, first based on anatomical landmarks utilizing only the post-extraction, and second with the use of the pre-extraction IOS as a setup. The time for implant positioning was recorded. After 1 month, all virtual plannings were performed again. The individual implant positions were superimposed to obtain 3D deviations using a software algorithm.

RESULTS

An interindividual variability with mean angular, crestal, and apical positional deviations of 3.8 ± 1.94°, 1.11 ± 0.55, and 1.54 ± 0.66 mm, respectively, was found. When assessing intraindividual variability, deviations of 3.28 ± 1.99°, 0.78 ± 0.46, and 1.12 ± 0.61 mm, respectively, were observed. Implants planned by experts exhibited statistically lower deviations compared to those planned by novices. Longer planning times resulted in lower deviations in the experts' group but not in the novices. Oral surgeons demonstrated lower crestal, but not angular and apical deviations than prosthodontists. The use of a setup only led to minor adjustments.

CONCLUSIONS

Substantial inter- and intraindividual variability exists during implant positioning utilizing specialized software planning. The level of expertise and the time invested influenced the deviations of the implant position during the planning sequence.

Is language an issue? Accuracy of the German computerized diagnostic decision support system ISABEL and cross-validation with the English counterpart

OBJECTIVES

Existing computerized diagnostic decision support tools (CDDS) accurately return possible differential diagnoses (DDx) based on the clinical information provided. The German versions of the CDDS tools for clinicians (Isabel Pro) and patients (Isabel Symptom Checker) from ISABEL Healthcare have not been validated yet.

METHODS

We entered clinical features of 50 patient vignettes taken from an emergency medical text book and 50 real cases with a confirmed diagnosis derived from the electronic health record (EHR) of a large academic Swiss emergency room into the German versions of Isabel Pro and Isabel Symptom Checker. We analysed the proportion of DDx lists that included the correct diagnosis.

RESULTS

Isabel Pro and Symptom Checker provided the correct diagnosis in 82 and 71 % of the cases, respectively. Overall, the correct diagnosis was ranked in 71 , 61 and 37 % of the cases within the top 20, 10 and 3 of the provided DDx when using Isabel Pro. In general, accuracy was higher with vignettes than ED cases, i.e. listed the correct diagnosis more often (non-significant) and ranked the diagnosis significantly more often within the top 20, 10 and 3. On average, 38 ± 4.5 DDx were provided by Isabel Pro and Symptom Checker.

CONCLUSIONS

The German versions of Isabel achieved a somewhat lower accuracy compared to previous studies of the English version. The accuracy decreases substantially when the position in the suggested DDx list is taken into account. Whether Isabel Pro is accurate enough to improve diagnostic quality in clinical ED routine needs further investigation.

The challenge of clinical reasoning in chronic multimorbidity: time and interactions in the Health Issues Network model

The increasing prevalence of multimorbidity requires new theoretical models and educational approaches to develop physicians' ability to manage multimorbidity patients. The Health Issues Network (HIN) is an educational approach based on a graphical depiction of the evolutions over time of the concurrent health issues of a patient and of their interactions. From a theoretical point of view, the HIN approach is rooted in Prigogine's vision of the "becoming" of the events and in the concept of knowledge organization, intended as the process of storing and structuring of information in a learner's mind. The HIN approach allows to design clinical exercises to foster learners' ability to detect evolutionary paths and interactions among health issues. Recent findings of neuroscience support the expectation that interpreting, completing, and creating diagrams depicting complex clinical cases improves the "sense of time", as a fundamental competence in the management of multimorbidity. The application of the HIN approach is expected to decrease the risk of errors in the management of multimorbidity patients. The approach is still under validation, both for undergraduate students and for the continuous professional development of physicians.

A comprehensive approach to identify challenges for clinical reasoning development in undergraduate dental students and their potential solutions

INTRODUCTION

Clinical reasoning is a core competence in health professions that impacts the ability to solve patients' health problems. Due to its relevance, it is necessary to identify difficulties arising from different sources that affect clinical reasoning development in students. The aim of this study was to explore a comprehensive approach to identify challenges for clinical reasoning development in undergraduate dental students and their potential solutions.

METHODS

Mixed methods were used in four stages: (1) students and clinical teachers focus groups to identify challenges to clinical reasoning development; (2) literature review to explore potential solutions for these challenges; (3) Delphi technique for teacher consensus on pertinence and feasibility of solutions (1-5 scale); and (4) teachers' self-perception of their ability to implement the solutions.

RESULTS

Three categories and seven subcategories of challenges were identified: (I) educational context factors influencing the clinical reasoning process; (II) teacher's role in clinical reasoning development; and (III) student factors influencing the clinical reasoning process. From 134 publications identified, 53 were selected for review, resulting in 10 potential solutions. Through two Delphi rounds, teachers rated the potential solutions very highly in terms of relevance (4.50-4.85) and feasibility (3.50-4.29). Finally, a prioritisation ranking of these solutions was generated using their scores for relevance, feasibility, and teachers' self-perception of their ability to implement them.

CONCLUSIONS

The present comprehensive approach identified challenges for clinical reasoning development in dental students and their potential solutions, perceived as relevant and feasible by teachers, requiring further research and follow-up actions to address them.

Cognitive bias during clinical decision-making and its influence on patient outcomes in the emergency department: A scoping review

BACKGROUND

An integral part of clinical practice is decision-making. Yet there is widespread acceptance that there is evidence of cognitive bias within clinical practice among nurses and physicians. However, how cognitive bias among emergency nurses and physicians' decision-making influences patient outcomes remains unclear.

AIM

The aim of this review was to systematically synthesise research exploring the emergency nurses' and physicians' cognitive bias in decision-making and its influence on patient outcomes.

METHODS

This scoping review was guided by the PRISMA Extension for Scoping Reviews. The databases searched included CINAHL, MEDLINE, Web of Science and PubMed. No date limits were applied. The Patterns, Advances, Gaps, Evidence for practice and Research recommendation (PAGER) framework was used to guide the discussion.

RESULTS

The review included 18 articles, consisting of 10 primary studies (nine quantitative and one qualitative) and eight literature reviews. Of the 18 articles, nine investigated physicians, five articles examined nurses, and four both physicians and nurses with sample sizes ranging from 13 to 3547. Six primary studies were cross-sectional and five used hypothetical scenarios, and one real-world assessment. Three were experimental studies. Twenty-nine cognitive biases were identified with Implicit bias (n = 12) most frequently explored, followed by outcome bias (n = 4). Results were inconclusive regarding the influence of biases on treatment decisions and patient outcomes. Four key themes were identified; (i) cognitive biases among emergency clinicians; (ii) measurement of cognitive bias; (iii) influence of cognitive bias on clinical decision-making; and (iv) association between emergency clinicians' cognitive bias and patient outcomes.

CONCLUSIONS

This review identified that cognitive biases were present among emergency nurses and physicians during clinical decision-making, but it remains unclear how cognitive bias influences patient outcomes. Further research examining emergency clinicians' cognitive bias is required.

RELEVANCE TO CLINICAL PRACTICE

Awareness of emergency clinicians' own cognitive biases may result to the provision of equity in care.

NO PATIENT OR PUBLIC CONTRIBUTION IN THIS REVIEW

We intend to disseminate the results through publication in a peer-reviewed journals and conference presentations.

Temporal uncertainty in disease diagnosis

There is a profound paradox in modern medical knowledge production: The more we know, the more we know that we (still) do not know. Nowhere is this more visible than in diagnostics and early detection of disease. As we identify ever more markers, predictors, precursors, and risk factors of disease ever earlier, we realize that we need knowledge about whether they develop into something experienced by the person and threatening to the person's health. This study investigates how advancements in science and technology alter one type of uncertainty, i.e., temporal uncertainty of disease diagnosis. As diagnosis is related to anamnesis and prognosis it identifies how uncertainties in all these fields are interconnected. In particular, the study finds that uncertainty in disease diagnosis has become more subject to prognostic uncertainty because diagnosis is more connected to technologically detected indicators and less closely connected to manifest and experienced disease. These temporal uncertainties pose basic epistemological and ethical challenges as they can result in overdiagnosis, overtreatment, unnecessary anxiety and fear, useless and even harmful diagnostic odysseys, as well as vast opportunity costs. The point is not to stop our quest for knowledge about disease but to encourage real diagnostic improvements that help more people in ever better manner as early as possible. To do so, we need to pay careful attention to specific types of temporal uncertainty in modern diagnostics.

Management reasoning and patient-clinician interactions: Insights from shared decision-making and simulated outpatient encounters

PURPOSE

To expand understanding of patient-clinician interactions in management reasoning.

METHODS

We reviewed 10 videos of simulated patient-clinician encounters to identify instances of problematic and successful communication, then reviewed the videos again through the lens of two models of shared decision-making (SDM): an 'involvement-focused' model and a 'problem-focused' model. Using constant comparative qualitative analysis we explored the connections between these patient-clinician interactions and management reasoning.

RESULTS

Problems in patient-clinician interactions included failures to: encourage patient autonomy; invite the patient's involvement in decision-making; convey the health impact of the problem; explore and address concerns and questions; explore the context of decision-making (including patient preferences); meet the patient where they are; integrate situational preferences and priorities; offer >1 viable option; work with the patient to solve a problem of mutual concern; explicitly agree to a final care plan; and build the patient-clinician relationship. Clinicians' 'management scripts' varied along a continuum of prioritizing clinician vs patient needs. Patients also have their own cognitive scripts that guide their interactions with clinicians. The involvement-focused and problem-focused SDM models illuminated distinct, complementary issues.

CONCLUSIONS

Management reasoning is a deliberative interaction occurring in the space between individuals. Juxtaposing management reasoning alongside SDM generated numerous insights.

Cognitive biases in internal medicine: a scoping review

BACKGROUND

Medical errors account for up to 440,000 deaths annually, and cognitive errors outpace knowledge deficits as causes of error. Cognitive biases are predispositions to respond in predictable ways, and they don't always result in error. We conducted a scoping review exploring which biases are most prevalent in Internal Medicine (IM), if and how they influence patient outcomes, and what, if any, debiasing strategies are effective.

CONTENT

We searched PubMed, OVID, ERIC, SCOPUS, PsychINFO, and CINAHL. Search terms included variations of "bias", "clinical reasoning", and IM subspecialties. Inclusion criteria were: discussing bias, clinical reasoning, and physician participants.

SUMMARY

Fifteen of 334 identified papers were included. Two papers looked beyond general IM: one each in Infectious Diseases and Critical Care. Nine papers distinguished bias from error, whereas four referenced error in their definition of bias. The most commonly studied outcomes were diagnosis, treatment, and physician impact in 47 % (7), 33 % (5), and 27 % (4) of studies, respectively. Three studies directly assessed patient outcomes. The most commonly cited biases were availability bias (60 %, 9), confirmation bias (40 %, 6), anchoring (40 %, 6), and premature closure (33 %, 5). Proposed contributing features were years of practice, stressors, and practice setting. One study found that years of practice negatively correlated with susceptibility to bias. Ten studies discussed debiasing; all reported weak or equivocal efficacy.

OUTLOOK

We found 41 biases in IM and 22 features that may predispose physicians to bias. We found little evidence directly linking biases to error, which could account for the weak evidence of bias countermeasure efficacy. Future study clearly delineating bias from error and directly assessing clinical outcomes would be insightful.

Implementation of three knowledge-oriented instructional strategies to teach clinical reasoning: Self-explanation, a concept mapping exercise, and deliberate reflection: AMEE Guide No. 150

The teaching of clinical reasoning is essential in medical education. This guide has been written to provide educators with practical advice on the design, development, and implementation of three knowledge-oriented instructional strategies for the teaching of clinical reasoning to medical students: Self-explanation (SE), a Clinical Reasoning Mapping Exercise (CREsME), and Deliberate Reflection (DR). We first synthesize the theoretical tenets that support the use of these strategies, including knowledge organization, and development of illness scripts. We then provide a detailed description of the key components of each strategy, emphasizing the practical applications of each one by sharing specific examples. We also explore the potential for a combined application of these strategies in a longitudinal and developmental approach to teaching clinical reasoning at the undergraduate level. Finally, we discuss enablers and barriers in the implementation and integration of these teaching strategies while taking into consideration curricular needs, context, and resources. We are aware that many strategies exist and are not arguing that SE, CReSME, and DR are the most effective ones or the only ones to be adopted. Nevertheless, we selected these strategies because of overarching theoretical principles, empirical evidence supporting their use, and our own experience with them. We are hoping to provide practical advice on the implementation of these strategies to practicing educators who aim at developing an integrated approach to the teaching of clinical reasoning to medical students at different stages of their development.

Impact of emotional competence on physicians' clinical reasoning: a scoping review protocol

INTRODUCTION

Clinical reasoning (CR) is a key competence for physicians and a major source of damaging medical errors. Many strategies have been explored to improve CR quality, most of them based on knowledge enhancement, cognitive debiasing and the use of analytical reasoning. If increasing knowledge and fostering analytical reasoning have shown some positive results, the impact of debiasing is however mixed. Debiasing and promoting analytical reasoning have also been criticised for their lack of pragmatism. Alternative means of increasing CR quality are therefore still needed. Because emotions are known to influence the quality of reasoning in general, we hypothesised that emotional competence (EC) could improve physicians' CR. EC refers to the ability to identify, understand, express, regulate and use emotions. The influence of EC on CR remains unclear. This article presents a scoping review protocol, the aim of which will be to describe the current state of knowledge concerning the influence of EC on physicians' CR, the type of available literature and finally the different methods used to examine the link between EC and CR.

METHOD AND ANALYSIS

The population of interest is physicians and medical students. EC will be explored according to the model of Mikolajczak et al, describing five major components of EC (identify, understand, express, regulate and use emotions). The concept of CR will include terms related to its processes and outcomes. Context will include real or simulated clinical situations. The search for primary sources and reviews will be conducted in MEDLINE (via Ovid), Scopus and PsycINFO. The grey literature will be searched in the references of included articles and in OpenGrey. Study selection and data extraction will be conducted using the Covidence software. Search and inclusion results will be reported using the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for scoping review model (PRISMA-ScR).

ETHICS AND DISSEMINATION

There are no ethical or safety concerns regarding this review.

REGISTRATION DETAILS

OSF Registration DOI: https://doi.org/10.17605/OSF.IO/GM7YD.

Heuristics and biases in medical decision-making under uncertainty: The case of neuropronostication for consciousness disorders

Neuropronostication for consciousness disorders can be very complex and prone to high uncertainty. Despite notable advancements in the development of dedicated scales and physiological markers using innovative paradigms, these technical progressions are often overshadowed by factors intrinsic to the medical environment. Beyond the scarcity of objective data guiding medical decisions, factors like time pressure, fatigue, multitasking, and emotional load can drive clinicians to rely more on heuristic-based clinical reasoning. Such an approach, albeit beneficial under certain circumstances, may lead to systematic error judgments and impair medical decisions, especially in complex and uncertain environments. After a brief review of the main theoretical frameworks, this paper explores the influence of clinicians' cognitive biases on clinical reasoning and decision-making in the challenging context of neuroprognostication for consciousness disorders. The discussion further revolves around developing and implementing various strategies designed to mitigate these biases and their impact, aiming to enhance the quality of care and the patient safety.

Bias analysis in forensic and non-forensic psychiatric assessments

In this research, we provide two important contributions to the psychiatric community. First, we offer the first valid and reliable cognitive test that measures forensic clinicians' ability to detect and avoid diagnostic biases in psychiatric assessments. Second, we also estimate the prevalence of clinical decision bias detection and prevention ability among psychiatrists and psychologists. A total of 1069 clinicians from different specialties (317 psychiatrists and 752 clinical psychologists, of which 286 were forensic clinicians) participated in this research. The Checklist of Biases for Clinicians (BIAS-31) was developed, and its psychometric properties were analyzed. The prevalence of bias detection and prevention was estimated using BIAS-31 scores. The BIAS-31 is valid and reliable for measuring clinicians' ability to avoid and detect clinical biases. Between 41.2% and 55.8% of clinicians try to avoid biased clinical judgments. Likewise, between 48.5% and 57.5% of clinicians were able to correctly detect the biases involved in the diagnostic assessment process. We did not expect to obtain these prevalences. Therefore, we discuss to what extent specific training in the prevention of diagnostic biases is necessary and propose several clinical strategies to prevent a priori the occurrence of biases in the psychiatric assessment.

Impact of diagnostic checklists on the interpretation of normal and abnormal electrocardiograms

OBJECTIVES

Checklists that aim to support clinicians' diagnostic reasoning processes are often recommended to prevent diagnostic errors. Evidence on checklist effectiveness is mixed and seems to depend on checklist type, case difficulty, and participants' expertise. Existing studies primarily use abnormal cases, leaving it unclear how the diagnosis of normal cases is affected by checklist use. We investigated how content-specific and debiasing checklists impacted performance for normal and abnormal cases in electrocardiogram (ECG) diagnosis.

METHODS

In this randomized experiment, 42 first year general practice residents interpreted normal, simple abnormal, and complex abnormal ECGs without a checklist. One week later, they were randomly assigned to diagnose the ECGs again with either a debiasing or content-specific checklist. We measured residents' diagnostic accuracy, confidence, patient management, and time taken to diagnose. Additionally, confidence-accuracy calibration was assessed.

RESULTS

Accuracy, confidence, and patient management were not significantly affected by checklist use. Time to diagnose decreased with a checklist (M=147s (77)) compared to without a checklist (M=189s (80), Z=-3.10, p=0.002). Additionally, residents' calibration improved when using a checklist (phase 1: R2=0.14, phase 2: R2=0.40).

CONCLUSIONS

In both normal and abnormal cases, checklist use improved confidence-accuracy calibration, though accuracy and confidence were not significantly affected. Time to diagnose was reduced. Future research should evaluate this effect in more experienced GPs. Checklists appear promising for reducing overconfidence without negatively impacting normal or simple ECGs. Reducing overconfidence has the potential to improve diagnostic performance in the long term.

Twelve tips for physicians’ mastering expertise in diagnostic excellence

Diagnostic errors, which account for a large proportion of medical errors, are a global medical challenge. The slogan of reducing diagnostic errors has recently shifted to a new strategy of diagnostic excellence, the core of which is the importance of improving the multidisciplinary diagnostic process. Many of the elements and strategies necessary for diagnostic excellence have been presented. In the context of this diagnostic improvement, some reports have been structured to improve the quality of performance of individual physicians as players. Still, surprisingly, only a few reports have focused on specific day-to-day training strategies for the diagnostic thinking process as expertise. This paper focuses on this point and proposes strategies for refining the diagnostic thinking expertise of frontline physicians in the new era, based on the following four elements: knowledge and experience, diagnostic thinking strategies, information management skills, and calibration and reflection.

Effects of a computerised diagnostic decision support tool on diagnostic quality in emergency departments: study protocol of the DDx-BRO multicentre cluster randomised cross-over trial

INTRODUCTION

Computerised diagnostic decision support systems (CDDS) suggesting differential diagnoses to physicians aim to improve clinical reasoning and diagnostic quality. However, controlled clinical trials investigating their effectiveness and safety are absent and the consequences of its use in clinical practice are unknown. We aim to investigate the effect of CDDS use in the emergency department (ED) on diagnostic quality, workflow, resource consumption and patient outcomes.

METHODS AND ANALYSIS

This is a multicentre, outcome assessor and patient-blinded, cluster-randomised, multiperiod crossover superiority trial. A validated differential diagnosis generator will be implemented in four EDs and randomly allocated to a sequence of six alternating intervention and control periods. During intervention periods, the treating ED physician will be asked to consult the CDDS at least once during diagnostic workup. During control periods, physicians will not have access to the CDDS and diagnostic workup will follow usual clinical care. Key inclusion criteria will be patients' presentation to the ED with either fever, abdominal pain, syncope or a non-specific complaint as chief complaint. The primary outcome is a binary diagnostic quality risk score composed of presence of an unscheduled medical care after discharge, change in diagnosis or death during time of follow-up or an unexpected upscale in care within 24 hours after hospital admission. Time of follow-up is 14 days. At least 1184 patients will be included. Secondary outcomes include length of hospital stay, diagnostics and data regarding CDDS usage, physicians' confidence calibration and diagnostic workflow. Statistical analysis will use general linear mixed modelling methods.

ETHICS AND DISSEMINATION

Approved by the cantonal ethics committee of canton Berne (2022-D0002) and Swissmedic, the Swiss national regulatory authority on medical devices. Study results will be disseminated through peer-reviewed journals, open repositories and the network of investigators and the expert and patients advisory board.

TRIAL REGISTRATION NUMBER

NCT05346523.

Stabilizing expectations when shifting from analytical to intuitive reasoning: The role of prediction errors in reasoning

As humans, we rely on intuitive reasoning for most of our decisions. However, when there is a novel or atypical decision to be made, we must rely on a slower and more deliberative thought process-analytical reasoning. As we gain experience with these novel or atypical decisions, our reasoning shifts from analytical to intuitive, which parallels a reduction in the need for cognitive control. Here, we sought to confirm this claim by employing electroencephalographic (EEG) measures of cognitive control as participants performed a simple perceptual decision-making task. Specifically, we had participants categorize "blobs" into families based on their visual attributes so we could examine how their reasoning changed with learning. In a key manipulation, halfway through the experiment we introduced novel blob families to categorize, thus temporarily increasing the need for analytical reasoning (i.e., cognitive control). Congruent with past research, we focused our EEG analyses on frontal theta activity as it has been linked to cognitive control and analytical thinking. As hypothesized, we found a transition from analytical to intuitive decision-making systems with learning as indexed by a decrease in frontal theta power. Further, when the novel blobs were introduced at the midpoint of the experiment, we found that decisions about these stimuli recruited analytical reasoning as indicated by increased theta power in comparison to decisions about well-practiced stimuli. We propose our findings to reflect prediction errors to decision demands-a monitoring process that determines whether our expectations of demands are met. Shifting from analytical to intuitive reasoning thus reflects the stabilization of our expectations of decision demands, which can be violated with unexpected demands when encountering novel stimuli.

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.