Diagnostic reasoning in cardiovascular medicine

The role of cardiac ultrasound virtual simulation technology in the construction of clinical diagnostic reasoning of structural heart diseases

BACKGROUND

Clinical reasoning education is a very systematic and highly logical medical learning process, but the existing teaching models and methods often divide this process into several stages for separate training using a virtual reality (VR)simulator can simulate and reconstruct the cardiac anatomical structure, ultrasonic section operation, and color doppler ultrasound parameter measurement, then integrate it into a single disease or case. In this case, the students' operation skills,decision-making and communication skills were trained by cardiac physical examination, inquiry and interpretation of laboratory examination results. This study aims to investigate whether the application of virtual simulation technology in cardiac ultrasound learning can improve students' thinking ability in the diagnosis and treatment of structural heart diseases.

METHOD

This study involved fifty-nine undergraduate students studying clinical medicine in the fifth semester at Jinan University. We employed a simple randomization method for random grouping. Random numbers were generated in Excel based on the students' student IDs. Then the students were sorted and divided into the experimental group, which used virtual simulation teaching based on ultrasound, and the control group, which used traditional teaching method. Following the completion of theory teaching, operation demonstration, clinical skills practice and VR practice, students underwent an offline image assessment and online systematic test, which included cardiac ultrasound operation assessment and virtual simulation case assessment to evaluate their proficiency in clinical skills and analytical ability in clinical reasoning. Furthermore, the VR group was given a separate questionnaire to provide their feedback on the cardiac ultrasound virtual simulation education.

RESULTS

There were no statistically significant differences between the two groups in the scores for offline image interpretation and patient inquiry in the virtual simulation case analysis (P > 0.05). The scores for physical examination in virtual simulation case analysis (P < 0.05), virtual simulation ultrasound manipulation(P < 0.05) and diagnosis in virtual simulation case analysis(P < 0.05) were higher in the VR group than in the control group, and the difference was statistically significant. The total score for all evaluation of teaching quality in the VR group was higher than in the control group (P < 0.05). Furthermore, the majorityof students in the VR group displayed satisfaction with course experience, learning effect, teaching evaluation, and overall evaluation.

CONCLUSION

This research demonstrates that cardiac ultrasound virtual simulation technology could improve students' thinking ability in diagnosing and treating of structural heart diseases. The virtual simulation technology not only could be used for technology imitation but also could leverage its characteristics to demonstrate the process of a certain disease from anatomy to pathophysiology and clinical signs from shallow to deep.

Clinical Decision Support Requirements for Ventricular Tachycardia Diagnosis Within the Frameworks of Knowledge and Practice: Survey Study

BACKGROUND

Ventricular tachycardia (VT) diagnosis is challenging due to the similarity between VT and some forms of supraventricular tachycardia, complexity of clinical manifestations, heterogeneity of underlying diseases, and potential for life-threatening hemodynamic instability. Clinical decision support systems (CDSSs) have emerged as promising tools to augment the diagnostic capabilities of cardiologists. However, a requirements analysis is acknowledged to be vital for the success of a CDSS, especially for complex clinical tasks such as VT diagnosis.

OBJECTIVE

The aims of this study were to analyze the requirements for a VT diagnosis CDSS within the frameworks of knowledge and practice and to determine the clinical decision support (CDS) needs.

METHODS

Our multidisciplinary team first conducted semistructured interviews with seven cardiologists related to the clinical challenges of VT and expected decision support. A questionnaire was designed by the multidisciplinary team based on the results of interviews. The questionnaire was divided into four sections: demographic information, knowledge assessment, practice assessment, and CDS needs. The practice section consisted of two simulated cases for a total score of 10 marks. Online questionnaires were disseminated to registered cardiologists across China from December 2022 to February 2023. The scores for the practice section were summarized as continuous variables, using the mean, median, and range. The knowledge and CDS needs sections were assessed using a 4-point Likert scale without a neutral option. Kruskal-Wallis tests were performed to investigate the relationship between scores and practice years or specialty.

RESULTS

Of the 687 cardiologists who completed the questionnaire, 567 responses were eligible for further analysis. The results of the knowledge assessment showed that 383 cardiologists (68%) lacked knowledge in diagnostic evaluation. The overall average score of the practice assessment was 6.11 (SD 0.55); the etiological diagnosis section had the highest overall scores (mean 6.74, SD 1.75), whereas the diagnostic evaluation section had the lowest scores (mean 5.78, SD 1.19). A majority of cardiologists (344/567, 60.7%) reported the need for a CDSS. There was a significant difference in practice competency scores between general cardiologists and arrhythmia specialists (P=.02).

CONCLUSIONS

There was a notable deficiency in the knowledge and practice of VT among Chinese cardiologists. Specific knowledge and practice support requirements were identified, which provide a foundation for further development and optimization of a CDSS. Moreover, it is important to consider clinicians' specialization levels and years of practice for effective and personalized support.

Reflection on medical errors: A thematic analysis

BACKGROUND

As there is a need to prepare doctors to minimize errors, we wanted to determine how doctors go about reflecting upon their medical errors.

METHODS

We conducted a thematic analysis of the published reflection reports of 12 Dutch doctors about the errors they had made. Three questions guided our analysis: What triggers doctors to become aware of their errors? What topics do they reflect upon to explain what happened? What lessons do doctors learn after reflecting on their error?

RESULTS

We found that the triggers which made doctors aware of their errors were mostly death and/or a complication. This suggests that the trigger to recognize that something might be wrong came too late. The 12 doctors cited 20 topics' themes that explained the error and 16 lessons-learnt themes. The majority of the topics and lessons learnt were related more to the doctors' inner worlds (personal features) than to the outer world (environment).

CONCLUSION

To minimize errors, doctors should be trained to become earlier and in time aware of distracting and misleading features that might interfere with their clinical reasoning. This training should focus on reflection in action and on discovering more about doctors' personal inner world to identify vulnerabilities.

Integration of respiratory physiology and clinical reasoning in the early years of a medical curriculum: engaging with students in a large classroom setting

Medical graduates are expected to apply scientific principles and explain the processes underlying common and important diseases. Evidence shows that integrated medical curricula, which deliver biomedical science within the context of clinical cases, facilitate student learning in preparation for practice. However, research has also shown that the student's perception of their knowledge can be lower in integrated compared to traditional courses. Thus the development of teaching methods to support both integrated learning and build student confidence in clinical reasoning is a priority. In this study, we describe the use of an audience response system to support active learning in large classes. Sessions, delivered by medical faculty from both academic and clinical backgrounds, were designed to build on the knowledge of the respiratory system in both health and disease through the interpretation of clinical cases. Results showed that student engagement was high throughout the session and students strongly agreed that the application of knowledge to real-life cases was a better way to understand clinical reasoning. Qualitative free text comments revealed that students liked the link between theory and practice and the active, integrated method of learning. In summary, this study describes a relatively simple but highly effective way of delivering integrated medical science teaching, in this case respiratory medicine, to improve student confidence in clinical reasoning. This educational approach was applied within the early years of the curriculum in preparation for teaching within a hospital setting, but the format could be applied across many different settings.NEW & NOTEWORTHY The development of teaching methods that support integrated learning and build student confidence is a priority. An audience response system was used to engage early year medical students in large classes in preparation for teaching within a hospital setting. Results showed high levels of student engagement and a greater appreciation for the link between theory and practice. This study describes a simple, active, and integrated method of learning that improves student confidence in clinical reasoning.

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.

Modeling Diagnostic Expertise in Cases of Irreducible Uncertainty: The Decision-Aligned Response Model

PURPOSE

Assessing expertise using psychometric models usually yields a measure of ability that is difficult to generalize to the complexity of diagnoses in clinical practice. However, using an item response modeling framework, it is possible to create a decision-aligned response model that captures a clinician's decision-making behavior on a continuous scale that fully represents competing diagnostic possibilities. In this proof-of-concept study, the authors demonstrate the necessary statistical conceptualization of this model using a specific electrocardiogram (ECG) example.

METHOD

The authors collected a range of ECGs with elevated ST segments due to either ST-elevation myocardial infarction (STEMI) or pericarditis. Based on pilot data, 20 ECGs were chosen to represent a continuum from "definitely STEMI" to "definitely pericarditis," including intermediate cases in which the diagnosis was intentionally unclear. Emergency medicine and cardiology physicians rated these ECGs on a 5-point scale ("definitely STEMI" to "definitely pericarditis"). The authors analyzed these ratings using a graded response model showing the degree to which each participant could separate the ECGs along the diagnostic continuum. The authors compared these metrics with the discharge diagnoses noted on chart review.

RESULTS

Thirty-seven participants rated the ECGs. As desired, the ECGs represented a range of phenotypes, including cases where participants were uncertain in their diagnosis. The response model showed that participants varied both in their propensity to diagnose one condition over another and in where they placed the thresholds between the 5 diagnostic categories. The most capable participants were able to meaningfully use all categories, with precise thresholds between categories.

CONCLUSIONS

The authors present a decision-aligned response model that demonstrates the confusability of a particular ECG and the skill with which a clinician can distinguish 2 diagnoses along a continuum of confusability. These results have broad implications for testing and for learning to manage uncertainty in diagnosis.

On the definition of dermatological disease. Part 2: approaches for defining dermatological diseases

In Part 1 of this two-part review, conceptual frameworks for defining skin diseases were articulated. In this review, the main approaches that can be used to develop diagnostic criteria for skin disease are summarized, using atopic dermatitis (AD) as an example. Different frameworks for defining skin disease for research purposes are articulated, including statistical, prognostic, operational, clinical and epidemiological approaches. All share the common aim of attempting to develop criteria that enable meaningful comparisons between groups of people. The desirable attributes of a good definition are described: diagnostic criteria should measure what they are meant to measure; the results should be the same for different assessors; the criteria should be coherent with what is known about that disease; they should reflect some degree of morbidity and not pick up subclinical disease; they should be easy to administer; and they should be applicable to a range of people of different ages, sexes/genders and ethnicities. Consensus-based criteria are contrasted with epidemiological derivation methods that assess the performance of diagnostic criteria in relation to a reference standard. The sensitivity and specificity of a disease definition is explained, along with how the trade-off between these two properties can vary, depending on the purpose of the study and the study setting. The review closes with some reflections on when it is appropriate to consider splitting a disease into more than one category and how diagnostic criteria can be interpreted in the clinical setting.