A clinical reasoning curriculum for medical students: an interim analysis

Objectives Diagnostic error is a critical patient safety issue that can be addressed in part through teaching clinical reasoning. Medical schools with clinical reasoning curricula tend to emphasize general reasoning concepts (e.g., differential diagnosis generation). Few published curricula go beyond teaching the steps in the diagnostic process to address how students should structure their knowledge to optimize diagnostic performance in future clinical encounters or to discuss elements outside of individual cognition that are essential to diagnosis. Methods In 2016, the University of California, San Francisco School of Medicine launched a clinical reasoning curriculum that simultaneously emphasizes reasoning concepts and intentional knowledge construction; the roles of patients, families, interprofessional colleagues; and communication in diagnosis. The curriculum features a longitudinal thread beginning in first year, with an immersive three week diagnostic reasoning (DR) course in the second year. Students evaluated the DR course. Additionally, we conducted an audit of the multiyear clinical reasoning curriculum using the Society to Improve Diagnosis in Medicine-Macy Foundation interprofessional diagnostic education competencies. Results Students rated DR highly (range 4.13–4.18/5 between 2018 and 2020) and reported high self-efficacy with applying clinical reasoning concepts and communicating reasoning to supervisors. A course audit demonstrated a disproportionate emphasis on individual (cognitive) competencies with inadequate attention to systems and team factors in diagnosis. Conclusions Our clinical reasoning curriculum led to high student self-efficacy. However, we stressed cognitive aspects of reasoning with limited instruction on teams and systems. Diagnosis education should expand beyond the cognitive- and physician-centric focus of most published reasoning courses.

Affective influences on clinical reasoning and diagnosis: insights from social psychology and new research opportunities

Psychological research consistently demonstrates that affect can play an important role in decision-making across a broad range of contexts. Despite this, the role of affect in clinical reasoning and medical decision-making has received relatively little attention. Integrating the affect, social cognition, and patient safety literatures can provide new insights that promise to advance our understanding of clinical reasoning and lay the foundation for novel interventions to reduce diagnostic errors and improve patient safety. In this paper, we briefly review the ways in which psychologists differentiate various types of affect. We then consider existing research examining the influence of both positive and negative affect on clinical reasoning and diagnosis. Finally, we introduce an empirically supported theoretical framework from social psychology that explains the cognitive processes by which these effects emerge and demonstrates that cognitive interventions can alter these processes. Such interventions, if adapted to a medical context, hold great promise for reducing errors that emerge from faulty thinking when healthcare providers experience different affective responses.

Updated picture of SARS-CoV-2 variants and mutations

The worldwide burden of coronavirus disease 2019 (COVID-19) is still unremittingly prosecuting, with nearly 300 million infections and over 5.3 million deaths recorded so far since the origin of the SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) pandemic at the end of the year 2019. The fight against this new highly virulent beta coronavirus appears one of the most strenuous and long challenges that humanity has ever faced, since a definitive treatment has not been identified so far. The adoption of potentially useful physical preventive measures such as lockdowns, social distancing and face masking seems only partially effective for mitigating viral spread, though efficacy and continuation of such measures on the long term is questionable, due to many social and economic reasons. Many COVID-19 vaccines have been developed and are now widely used, though their effectiveness is challenged by several aspects such as low uptake and limited efficacy in some specific populations, as well as by continuous emergence of new mutations in the SARS-CoV-2 genome, accompanying the origin and spread of new variants, which in turn may contribute to further decrease the effectiveness of current vaccines and treatments. This article is hence aimed to provide an updated picture of SARS-CoV-2 variants and mutations that have emerged from November 2019 to present time (i.e., early December 2021).

Diagnostic statements: a linguistic analysis of how clinicians communicate diagnosis

Objectives To investigate from a linguistic perspective how clinicians deliver diagnosis to patients, and how these statements relate to diagnostic accuracy. Methods To identify temporal and discursive features in diagnostic statements, we analysed 16 video-recorded interactions collected during a practice high-stakes exam for internationally trained clinicians (25% female, n=4) to gain accreditation to practice in Australia. We recorded time spent on history-taking, examination, diagnosis and management. We extracted and deductively analysed types of diagnostic statements informed by literature. Results Half of the participants arrived at the correct diagnosis, while the other half misdiagnosed the patient. On average, clinicians who made a diagnostic error took 30 s less in history-taking and 30 s more in providing diagnosis than clinicians with correct diagnosis. The majority of diagnostic statements were evidentialised (describing specific observations (n=24) or alluding to diagnostic processes (n=7)), personal knowledge or judgement (n=8), generalisations (n=6) and assertions (n=4). Clinicians who misdiagnosed provided more specific observations (n=14) than those who diagnosed correctly (n=9). Conclusions Interactions where there is a diagnostic error, had shorter history-taking periods, longer diagnostic statements and featured more evidence. Time spent on history-taking and diagnosis, and use of evidentialised diagnostic statements may be indicators for diagnostic accuracy.

Evaluation of feedback modalities and preferences regarding feedback on decision-making in a pediatric emergency department

Objectives To compare pediatric emergency clinicians’ attitudes toward three feedback modalities and assess clinicians’ case-based feedback preferences. Methods Electronic survey sent to pediatric emergency medicine (PEM) physicians and fellows; general pediatricians; and advanced practice providers (APPs) with nine questions exploring effectiveness and emotional impact of three feedback modalities: case-based feedback, bounce-back notifications, and biannual performance reports. Additional questions used a four-point ordinal agreement response scale and assessed clinicians’ attitudes toward case review notification, case-based feedback preferences, and emotional support. Survey responses were compared by feedback modality using Pearson’s chi-squared. Results Of 165 eligible providers, 93 (56%) responded. Respondents agreed that case-based feedback was timely (81%), actionable (75%), prompted reflection on decision-making (92%), prompted research on current clinical practice (53%), and encouraged practice change (58%). Pediatric Emergency Care Applied Research Network (PECARN) performance reports scored the lowest on all metrics except positive feedback. No more than 40% of providers indicated that any feedback modality provided emotional support. Regarding case-based feedback, 88% of respondents desired email notification before case review and 88% desired feedback after case review. Clinicians prefer receiving feedback from someone with similar or more experience/training. Clinicians receiving feedback desire succinctness, supporting evidence, consistency, and sensitive delivery. Conclusions Case-based feedback scored highest of the three modalities and is perceived to be the most likely to improve decision-making and promote practice change. Most providers did not perceive emotional support from any feedback modality. Emotional safety warrants purposeful attention in feedback delivery. Critical components of case-based feedback include succinctness, supporting evidence, consistency, and sensitive delivery.

“Sick or not sick?” A mixed methods study evaluating the rapid determination of illness severity in a pediatric emergency department

Objectives Experienced physicians must rapidly identify ill pediatric patients. We evaluated the ability of an illness rating score (IRS) to predict admission to a pediatric hospital and explored the underlying clinical reasoning of the gestalt assessment of illness. Methods We used mixed-methods to study pediatric emergency medicine physicians at an academic children’s hospital emergency department (ED). Physicians rated patients’ illness severity with the IRS, anchored by 0 (totally well) and 10 (critically ill), and shared their rationale with concurrent think-aloud responses. The association between IRS and need for hospitalization, respiratory support, parenteral antibiotics, and resuscitative intravenous (IV) fluids were analyzed with mixed effects linear regression. Area under the curve (AUC) receiver operator characteristic (ROC) curve and test characteristics at different cut-points were calculated for IRS as a predictor of admission. Think-aloud responses were qualitatively analyzed via inductive process. Results A total of 141 IRS were analyzed (mean 3.56, SD 2.30, range 0–9). Mean IRS were significantly higher for patients requiring admission (4.32 vs. 3.13, p<0.001), respiratory support (6.15 vs. 3.98, p = 0.033), IV fluids (4.53 vs. 3.14, p < 0.001), and parenteral antibiotics (4.68 vs. 3.32, p = 0.009). AUC for IRS as a predictor of admission was 0.635 (95% CI: 0.534–0.737). Analysis of 95 think-aloud responses yielded eight categories that describe the underlying clinical reasoning. Conclusions Rapid assessments as captured by the IRS differentiated pediatric patients who required admission and medical interventions. Think-aloud responses for the rationale for rapid assessments may form the basis for teaching the skill of identifying ill pediatric patients.

A call to action: next steps to advance diagnosis education in the health professions

Objectives Improving diagnosis-related education in the health professions has great potential to improve the quality and safety of diagnosis in practice. Twelve key diagnostic competencies have been delineated through a previous initiative. The objective of this project was to identify the next steps necessary for these to be incorporated broadly in education and training across the health professions. Methods We focused on medicine, nursing, and pharmacy as examples. A literature review was conducted to survey the state of diagnosis education in these fields, and a consensus group was convened to specify next steps, using formal approaches to rank suggestions. Results The literature review confirmed initial but insufficient progress towards addressing diagnosis-related education. By consensus, we identified the next steps necessary to advance diagnosis education, and five required elements relevant to every profession: 1) Developing a shared, common language for diagnosis, 2) developing the necessary content, 3) developing assessment tools, 4) promoting faculty development, and 5) spreading awareness of the need to improve education in regard to diagnosis. Conclusions The primary stakeholders, representing education, certification, accreditation, and licensure, in each profession must now take action in their own areas to encourage, promote, and enable improved diagnosis, and move these recommendations forward.

Lessons in clinical reasoning ‒ pitfalls, myths and pearls: a case of recurrent pancreatitis

Objectives Cognitive biases can result in clinical reasoning failures that can lead to diagnostic errors. Autobrewery syndrome is a rare, but likely underdiagnosed, condition in which gut flora ferment glucose, producing ethanol. It most frequently presents with unexplained episodes of inebriation, though more case studies are necessary to better characterize the syndrome. Case presentation This is a case of a 41-year old male with a past medical history notable only for frequent sinus infections, who presented with recurrent episodes of acute pancreatitis. In the week prior to his first episode of pancreatitis, he consumed four beers, an increase from his baseline of 1–2 drinks per month. At home, he had several episodes of confusion, which he attributed to fatigue. He underwent laparoscopic cholecystectomy and testing for genetic and autoimmune causes of pancreatitis, which were non-revealing. He was hospitalized 10 more times during that 9-month period for acute pancreatitis with elevated transaminases. During these admissions, he had elevated triglycerides requiring an insulin drip and elevated alcohol level despite abstaining from alcohol for the prior eight months. His alcohol level increased after consumption of complex carbohydrates, confirming the diagnosis of autobrewery syndrome. Conclusions Through integrated commentary on the diagnostic reasoning process, this case underscores how overconfidence can lead to premature closure and anchoring resulting in diagnostic error. Using a metacognitive overview, case discussants describe the importance of structured reflection and a standardized approach to early hypothesis generation to navigate these cognitive biases.

Learning to diagnose X-rays: a neuroscientific study of practice-related activation changes in the prefrontal cortex

Objectives Medical expertise manifests itself by the ability of a physician to rapidly diagnose patients. How this expertise develops from a neural-activation perspective is not well understood. The objective of the present study was to investigate practice-related activation changes in the prefrontal cortex (PFC) as medical students learn to diagnose chest X-rays. Methods The experimental paradigm consisted of a learning and a test phase. During the learning phase, 26 medical students were trained to diagnose four out of eight chest X-rays. These four cases were presented repeatedly and corrective feedback was provided. During the test phase, all eight cases were presented together with near- and far-transfer cases to examine whether participants’ diagnostic learning went beyond simple rote recognition of the trained X-rays. During both phases, participants’ PFC was scanned using functional near-infrared spectroscopy. Response time and diagnostic accuracy were recorded as behavioural indicators. One-way repeated measures ANOVA were conducted to analyse the data. Results Results revealed that participants’ diagnostic accuracy significantly increased during the learning phase (F=6.72, p<0.01), whereas their response time significantly decreased (F=16.69, p<0.001). Learning to diagnose chest X-rays was associated with a significant decrease in PFC activity (F=33.21, p<0.001) in the left dorsolateral prefrontal cortex, the orbitofrontal area, the frontopolar area and the frontal eye field. Further, the results of the test phase indicated that participants’ diagnostic accuracy was significantly higher for the four trained cases, second highest for the near-transfer, third highest for the far-transfer cases and lowest for the untrained cases (F=167.20, p<0.001) and response time was lowest for the trained cases, second lowest for the near-transfer, third lowest for the far-transfer cases and highest for the untrained cases (F=9.72, p<0.001). In addition, PFC activity was lowest for the trained and near-transfer cases, followed by the far-transfer cases and highest for the untrained cases (F=282.38, p<0.001). Conclusions The results suggest that learning to diagnose X-rays is associated with a significant decrease in PFC activity. In terms of dual-process theory, these findings support the notion that students initially rely more on slow analytical system-2 reasoning. As expertise develops, system-2 reasoning transitions into faster and automatic system-1 reasoning.

Emergency medicine physicians’ perspectives on diagnostic accuracy in neurology: a qualitative study

Objectives We sought to understand the knowledge, attitudes, and beliefs of emergency medicine (EM) physicians towards non-specific neurological conditions and the use of clinical decision support (CDS) to improve diagnostic accuracy. Methods We conducted semi-structured interviews of EM physicians at four emergency departments (EDs) affiliated with a single US healthcare system. Interviews were conducted until thematic saturation was achieved. Conventional content analysis was used to identify themes related to EM physicians’ perspectives on acute diagnostic neurology; directed content analysis was used to explore views regarding CDS. Each interview transcript was independently coded by two researchers using an iteratively refined codebook with consensus-based resolution of coding differences. Results We identified two domains regarding diagnostic safety: (1) challenges unique to neurological complaints and (2) challenges in EM more broadly. Themes relevant to neurology included: (1) knowledge gaps and uncertainty, (2) skepticism about neurology, (3) comfort with basic as opposed to detailed neurological examination, and (4) comfort with non-neurological diseases. Themes relevant to diagnostic decision making in the ED included: (1) cognitive biases, (2) ED system/environmental issues, (3) patient barriers, (4) comfort with diagnostic uncertainty, and (5) concerns regarding diagnostic error identification and measurement. Most participating EM physicians were enthusiastic about the potential for well-designed CDS to improve diagnostic accuracy for non-specific neurological complaints. Conclusions Physicians identified diagnostic challenges unique to neurological diseases as well as issues related more generally to diagnostic accuracy in EM. These physician-reported issues should be accounted for when designing interventions to improve ED diagnostic accuracy.