Dataset Information

Teaching Clinical Reasoning to Medical Students: A Case-Based Illness Script Worksheet Approach.

ABSTRACT:

Introduction

Clinical reasoning is a fundamental part of a physician's daily workflow. Yet it remains a challenging skill to develop formally, especially in preclerkship-level early learners. Traditionally, medical students learn clinical reasoning informally through experiential opportunities during their clerkship years. This occurs in contrast to the more structured, explicit learning of the basic sciences and physical diagnosis during the preclerkship years. To address this need, we present a flipped classroom case-based approach for developing clinical reasoning skills based on problem representation and the use of a structured illness script worksheet as a model.

Methods

Students were given a short introduction via screencast to introduce clinical reasoning and related terminology such as problem representation and semantic qualifiers. They also received a case vignette and an illness script worksheet to prepare them for in-class discussion. Students used this worksheet to practice clinical reasoning in a small-group session that was held in our last organ system-based second-year course, prior to the start of the clerkships.

Results

In comparison to the traditional facilitator-led small-group sessions, where students would sequentially answer a set of defined content-based questions to explore a clinical case, 80% of students preferred the new framework that incorporates problem representation and the illness script worksheets. Faculty facilitators found the structure of the illness script worksheet helpful in leading a clinical reasoning small-group session.

Discussion

Based on the results of this pilot, we plan to systematically implement this clinical reasoning framework in our preclerkship curriculum.

SUBMITTER: Levin M

PROVIDER: S-EPMC6464440 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Publications

Teaching Clinical Reasoning to Medical Students: A Case-Based Illness Script Worksheet Approach.

Levin Michael M Cennimo David D Chen Sophia S Lamba Sangeeta S

MedEdPORTAL : the journal of teaching and learning resources 20160826

<h4>Introduction</h4>Clinical reasoning is a fundamental part of a physician's daily workflow. Yet it remains a challenging skill to develop formally, especially in preclerkship-level early learners. Traditionally, medical students learn clinical reasoning informally through experiential opportunities during their clerkship years. This occurs in contrast to the more structured, explicit learning of the basic sciences and physical diagnosis during the preclerkship years. To address this need, we ...[more]

PMID: 31008223

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Project description:PurposeGraduating medical students need broad clinical diagnostic reasoning skills that integrate learning across clinical specialties to deal with undifferentiated patient problems. The opportunity to acquire these skills may be limited during clinical placements on increasingly specialized hospital wards. We developed an intervention of regular general practitioner (GP) facilitated teaching in hospital placements to enable students to develop broad clinical diagnostic reasoning. The intervention was piloted, refined and delivered to a whole cohort of medical students at the start of their third year. This paper examines whether students perceived opportunities to improve their broad diagnostic clinical reasoning through our intervention.MethodsGP-facilitated teaching sessions were delivered weekly in hospital placements to small groups of 6–8 students for 90 mins over 6 weeks. Students practiced clinical reasoning with real patient cases that they encountered on their placements. Evaluation of learning outcomes was conducted through a student questionnaire using Likert scales with free-text boxes for additional explanation. Focus groups were conducted to gain a more in-depth understanding of student perspectives.ResultsAs high as 87% of students agreed that their broad clinical diagnostic reasoning ability had improved. Thematic analysis of the qualitative data revealed four factors supporting this improvement: practicing the hypothetico-deductive method, using real patient cases, composing student groups from different speciality placements and the breadth of the facilitators’ knowledge. Students additionally reported enhanced person-centredness in terms of understanding the patient’s perspective and journey. Students perceived that the added value of general practitioner facilitators lay in their broad knowledge base and knowledge of patient needs in the community.ConclusionOur results suggest that medical students can develop broad clinical diagnostic reasoning skills in hospital settings through regular GP-facilitated teaching. Our approach has the advantage of working within the established curricular format of hospital placements and being deliverable at scale to whole student cohorts.

Project description:BackgroundRepeated formative assessments using key feature questions have been shown to enhance clinical reasoning. Key feature questions augmented by videos presenting clinical vignettes may be more effective than text-based questions, especially in a setting where medical students are free to choose the format they would like to work with. This study investigated learning outcomes related to clinical reasoning in students using video- or text-based key feature questions according to their individual preferences.ObjectiveThe aim of this study was to test the hypothesis that repeated exposure to video-based key feature questions enhances clinical reasoning to a greater extent than repeated exposure to text-based key feature questions if students are allowed to choose between those different formats on their own.MethodsIn this monocentric, prospective, nonrandomized trial, fourth-year medical students attended 12 computer-based case seminars during which they worked on case histories containing key feature questions. Cases were available in a text- and a video-based format. Students chose their preferred presentation format at the beginning of each case seminar. Student performance in key feature questions was assessed in formative entry, exit, and retention exams and was analyzed with regard to preceding exposure to video- or text-based case histories.ResultsOf 102 eligible students, 75 provided written consent and complete data at all study exams (response rate=73.5%). A majority of students (n=52) predominantly chose the text-based format. Compared with these, students preferring the video-based format achieved a nonsignificantly higher score in the exit exam (mean 76.2% [SD 12.6] vs 70.0% [SD 19.0]; P=.15) and a significantly higher score in the retention exam (mean 75.3% [SD 16.6] vs 63.4% [SD 20.3]; P=.02). The effect was independent of the video- or text-based presentation format, which was set as default in the respective exams.ConclusionsDespite students' overall preference for text-based case histories, the learning outcome with regard to clinical reasoning was higher in students with higher exposure to video-based items. Time-on-task is one conceivable explanation for these effects as working with video-based items was more time-consuming. The baseline performance levels of students do not account for the results as the preceding summative exam results were comparable across the 2 groups. Given that a substantial number of students chose a presentation format that was less effective, students might need to be briefed about the beneficial effects of using video-based case histories to be able to make informed choices about their study methods.

Project description:PurposeDeveloping medical students' clinical reasoning requires a structured longitudinal curriculum with frequent targeted assessment and feedback. Performance-based assessments, which have the strongest validity evidence, are currently not feasible for this purpose because they are time-intensive to score. This study explored the potential of using machine learning technologies to score one such assessment-the diagnostic justification essay.MethodFrom May to September 2018, machine scoring algorithms were trained to score a sample of 700 diagnostic justification essays written by 414 third-year medical students from the Southern Illinois University School of Medicine classes of 2012-2017. The algorithms applied semantically based natural language processing metrics (e.g., coherence, readability) to assess essay quality on 4 criteria (differential diagnosis, recognition and use of findings, workup, and thought process); the scores for these criteria were summed to create overall scores. Three sources of validity evidence (response process, internal structure, and association with other variables) were examined.ResultsMachine scores correlated more strongly with faculty ratings than faculty ratings did with each other (machine: .28-.53, faculty: .13-.33) and were less case-specific. Machine scores and faculty ratings were similarly correlated with medical knowledge, clinical cognition, and prior diagnostic justification. Machine scores were more strongly associated with clinical communication than were faculty ratings (.43 vs .31).ConclusionsMachine learning technologies may be useful for assessing medical students' long-form written clinical reasoning. Semantically based machine scoring may capture the communicative aspects of clinical reasoning better than faculty ratings, offering the potential for automated assessment that generalizes to the workplace. These results underscore the potential of machine scoring to capture an aspect of clinical reasoning performance that is difficult to assess with traditional analytic scoring methods. Additional research should investigate machine scoring generalizability and examine its acceptability to trainees and educators.

Project description:Background: Clinical reasoning refers to a thinking process including medical problem solving and medical decision making skills. Several studies have shown that the clinical reasoning process can be influenced by a number of factors, e.g. context or personality traits, and the results of this thinking process are expressed in case presentation. The aim of this study was to identify factors, which predict the quality of case summary statements as an indicator of clinical reasoning of undergraduate medical students in an assessment simulating the first day of residency. Methods: To investigate factors predicting aspects of clinical reasoning 67 advanced undergraduate medical students participated in the role of a beginning resident in our competence-based assessment, which included a consultation hour, a patient management phase, and a handover. Participants filled out a Post Encounter Form (PEF) to document their case summary statements and other aspects of clinical reasoning. After each phase, they filled out the Strain Perception Questionnaire (STRAIPER) to measure their situation dependent mental strain. To assess medical knowledge the participants completed a 100 questions multiple choice test. To measure stress resistance, adherence to procedures, and teamwork students took part in the Group Assessment of Performance (GAP) test for flight school applicants. These factors were included in a multiple linear regression analysis. Results: Medical knowledge and teamwork predicted the quality of case summary statements as an indicator of clinical reasoning of undergraduate medical students and explained approximately 20.3% of the variance. Neither age, gender, undergraduate curriculum, academic advancement nor high school grade point average of the medical students of our sample had an effect on their clinical reasoning skills. Conclusion: The quality of case summary statements as an indicator of clinical reasoning can be predicted in undergraduate medical students by their medical knowledge and teamwork. Students should be supported in developing abilities to work in a team and to acquire long term knowledge for good case summary statements as an important aspect of clinical reasoning.

Dataset Information

Teaching Clinical Reasoning to Medical Students: A Case-Based Illness Script Worksheet Approach.

Introduction

Methods

Results

Discussion

Publications

Teaching Clinical Reasoning to Medical Students: A Case-Based Illness Script Worksheet Approach.

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