ContExtended Questions (CEQ) to Teach and Assess Clinical Reasoning: A New Variant of F-Type Testlets

This study introduces ContExtended Questions (CEQ), which is a tool both to teach and assess clinical reasoning particularly in the preclinical years, and the web-based program to implement. CEQ consists of text-based case-based multiple-choice questions that provide patient data in a fixed and predetermined sequence. It enables the examinees to develop and reshape their illness scripts by using feedback after every question. Feedback operates to transform the examinee’s failure into a “productive failure”. The preliminary results of the randomized controlled experiment of teaching clinical reasoning to preclinical students through CEQ is quite satisfactory. In the medical education literature, this would be the first time that students, who have no or very limited clinical experience, developed their illness scripts just by taking formative multiple-choice tests. The approach would be named “test-only learning”. The complete results of the experiment and then more experiments in other contexts and domains are necessary to establish a more powerful assessment tool and software. Furthermore, by changing the content of the questions, it is possible to use CEQ in every period of medical education and health professions education.

What does research on clinical reasoning have to say to clinical teachers?

Clinical reasoning is a crucial determinant of physicians’ performance. It is key to arrive at a correct diagnosis, which substantially increases the chance of appropriate therapeutic decisions. Clinical teachers face the daily challenge of helping their students to develop clinical reasoning. To select appropriate teaching strategies, it may be useful to become acquainted with the results of the research on clinical reasoning that has been conducted over the last decades. This article synthesizes the findings of this research that help in particular to understand the cognitive processes involved in clinical reasoning, the trajectory that leads the student from novice to expert, and instructional approaches that have been shown to be useful to facilitating this trajectory. The focus of the article is the diagnostic process, because it is about it that most research has been conducted. This research indicates that there is not a particular reasoning strategy that is specific to expert physicians and could be taught to students. It is the availability of a large knowledge base organized in memory in illness scripts of different formats that explains the expert’s better performance. The more, the richer, and the more well-structured are the illness scripts a physician has stored in memory, the more he/she would be able to make accurate diagnoses. These scripts are formed gradually over the years of education. To help develop them, students should be exposed to a wide variety of clinical problems, with which they must interact actively. Instructional approaches that require students to systematically reflect on problems, analyzing differences and similarities between them, explaining underlying mechanisms, comparing and contrasting alternative diagnoses, have proved useful to help refine disease scripts. These approaches are valuable tools for teachers concerned with the development of their students clinical reasoning.

1946. An Exploratory Study of the Therapeutic Reasoning Underlying Antimicrobial Selection

Background Clinical reasoning research has helped illuminate how clinicians make diagnoses but offers less insight into management decisions. The need to understand therapeutic choices is particularly salient within infectious diseases (ID), where antimicrobial prescribing has broad implications given increasing rates of resistance. Researchers have examined general factors underlying antibiotic prescribing. Our study advances this work by exploring the factors and processes underlying physician choice of specific antimicrobials. Methods We conducted individual interviews with a purposeful sample of Hospitalists and ID attendings. Our semi-structured interview explored the reasoning underlying antimicrobial choice through clinical vignettes. We identified steps and factors after 12 interviews then conducted 4 more to confirm and refine our findings. We generated a codebook through an iterative, inductive process and used Dedoose to code the interviews and facilitate analysis. Results We identified three antibiotic reasoning steps (Naming the Syndrome, Delineating Pathogens, Antimicrobial Selection) and four factors involved in the reasoning process (Host Features, Case Features, Provider and Healthcare System Factors, Treatment Principles) (Table 1). Participants considered host and case features when determining likely pathogens and antimicrobial options; the other two factors influenced only antimicrobial selection. From these data, we developed an antimicrobial reasoning framework (Figure 1). We also determined that participants seemed to have a “script” with specific content for each antimicrobial they considered, functioning much like the illness scripts common to diagnostic reasoning (Table 2). Conclusion Our antimicrobial reasoning framework details the cognitive processes underlying antimicrobial choice. Our results build on general therapeutic reasoning frameworks while elaborating factors specific to ID. We also provide evidence of the existence of “therapy scripts” that mirror diagnostic reasoning’s “illness scripts.” Our framework has implications for medical education and antimicrobial stewardship. Disclosures All Authors: No reported Disclosures.

Applying Metacognition Through Patient Encounters and Illness Scripts to Create a Conceptual Framework for Basic Science Integration, Storage, and Retrieval

Problem: Medical school curriculum continues to search for methods to develop a conceptual educational framework that promotes the storage, retrieval, transfer, and application of basic science to the human experience. To achieve this goal, we propose a metacognitive approach that integrates basic science with the humanistic and health system aspects of medical education. Intervention: During the week, via problem-based learning and lectures, first-year medical students were taught the basic science underlying a disease. Each Friday, a patient with the disease spoke to the class. Students then wrote illness scripts, which required them to metacognitively reflect not only on disease pathophysiology, complications, and treatments but also on the humanistic and health system issues revealed during the patient encounter. Evaluation of the intervention was conducted by measuring results on course exams and national board exams and analyzing free responses on the illness scripts and student course feedback. The course exams and National Board of Medical Examiners questions were divided into 3 categories: content covered in lecture, problem-based learning, or patient + illness script. Comparisons were made using Student t-test. Free responses were inductively analyzed using grounded theory methodology. Context: This curricular intervention was implemented during the first 13-week basic science course of medical school. The main objective of the course, Scientific Principles of Medicine, is to lay the scientific foundation for subsequent organ system courses. A total of 150 students were enrolled each year. We evaluated this intervention over 2 years, totaling 300 students. Outcome: Students scored significantly higher on illness script content compared to lecture content on the course exams (mean difference = 11.1, P = .006) and national board exams given in December (mean difference = 21.8, P = .0002) and June (mean difference = 12.7, P = .016). Themes extracted from students’ free responses included the following: relevance of basic science, humanistic themes of empathy, resilience, and the doctor-patient relationship, and systems themes of cost, barriers to care, and support systems. Lessons learned: A metacognitive approach to learning through the use of patient encounters and illness script reflections creates stronger conceptual frameworks for students to integrate, store, retain, and retrieve knowledge.

Diagnostic Accuracy: The Wellspring of EBVM Success, and How We Can Improve It

Therapy and prognosis are entailed by the diagnosis: the holistic success of the EBVM approach there­fore firmly and critically rests on diagnostic accuracy.Unfortunately, medical professionals do not appear to be very accurate with diagnoses. In human medi­cine, there is 30-50% discordance reported between doctors’ ante- (presumptive) and post-mortem (defin­itive) diagnoses, with no significant change in the last 100 years (Goldberg et al 2002). This is attenuated by attaching a degree of certainty – ‘very certain’ shows 16% discordance, ‘probable’ 33% and ‘uncertain’ 50% – and some body systems are more difficult (e.g. respiratory) than others (Shojania et al 2002; Sing­ton and Cottrell 2002).Veterinary surgeons do not perform much better, although it is a chronically under-researched area. The single study that exists – from a respected referral institution – shows discordance between ante- and post-mortem diagnoses of ranging from 15% (oncology) to 45% (ECC), with internal medicine (44%), neu­rology (35%), surgery (33%) and cardiology (21%) lying in between (Kent et al 2004). Incorrect diagnoses are therefore common; the potential for subsequent incorrect or harmful therapy and/or prognosis is great; the quality of interventional evidence is immaterial if the wrong disease is being treated.How can we do better? Human EBM shows that technology, big data and further evidence does not guar­antee improvement; these are unlikely realisations for EBVM in the near future in any case. The answer may lie in the fields of psychology and social science. Studies indicate that diagnostic success may rest largely with the individual: expert clinicians consistently perform better. But how?Experts are marked out by the use of ‘illness scripts’, which are mental knowledge networks against which the presenting patient – history, signs, clinical data – are checked and hypotheses entertained or refuted until (with the addition of more clinical data) a diagnosis is reached (Custers 2015). Experts rapidly ap­praise relevant data, embracing and exploring inconsistencies in the clinical picture, largely ignore patho­physiology and make far fewer errors than novices.It appears we would do well to harness and teach these skills – however, current problem-based learning methods fail to do so. To maximise the impact on clinical performance, it seems explicit recognition, teach­ing and integration of illness scripts and pathways to expertise are fundamental steps for EBVM. This would require a ground-shift change in veterinary teaching and professional development, but may well prove to be the greatest positive difference EBVM can make to the veterinary profession.