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The Simulated Cardiology Clinic: A Standardized Patient Exercise Supporting Medical Students' Biomedical Knowledge and Clinical Skills Integration.

ABSTRACT: Introduction:Development of cardiac disease-related diagnostic skills-including hypothesis-driven data gathering, heart sound interpretation, and ECG interpretation-is an important component of medical student training. Prior studies indicate trainees' performance of these skills is limited. Simulation provides students with opportunities to practice integrating their developing knowledge in a relevant clinical context. We developed a simulated clinic activity for second-year medical students consisting of standardized patient (SP) cases representing cardiovascular (CV) diseases. Methods:Student small groups rotated through four SP encounters. For each case, one student performed the history, after which the whole small group listened to audio files of heart sounds, interpreted an ECG, and collaboratively developed a prioritized differential diagnosis. The CV course director met with students for a large-group debrief, highlighting key learning points. We collected learners' evaluations of the event through an online survey. Results:Of students, 276 participated in this activity over the course of 2 years. Nearly all students assessed the activity as extremely or quite effective for applying learning content from the CV course (97%, 2018; 93%, 2019), and for practicing how to approach chest pain, shortness of breath, palpitations, and fatigue (100%, 2018; 95%, 2019). The most helpful aspects were reinforcement of CV disease illness scripts, hypothesis-driven data gathering practice, ECG interpretation, and applying knowledge and skills in a realistic context. Discussion:SP encounters representing CV conditions can effectively provide opportunities for students to integrate basic science knowledge and clinical skills. Students assessed the activity as helpful and engaging.

SUBMITTER: Jackson JM

PROVIDER: S-EPMC7597946 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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The Simulated Cardiology Clinic: A Standardized Patient Exercise Supporting Medical Students' Biomedical Knowledge and Clinical Skills Integration.

Jackson Jennifer M JM Stacey R Brandon RB Korczyk Sharon S SS Williams Donna M DM

MedEdPORTAL : the journal of teaching and learning resources 20201028

<h4>Introduction</h4>Development of cardiac disease-related diagnostic skills-including hypothesis-driven data gathering, heart sound interpretation, and ECG interpretation-is an important component of medical student training. Prior studies indicate trainees' performance of these skills is limited. Simulation provides students with opportunities to practice integrating their developing knowledge in a relevant clinical context. We developed a simulated clinic activity for second-year medical stu ...[more]

PMID: 33150203

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Project description:The modern biomedical research and healthcare delivery domains have seen an unparalleled increase in the rate of innovation and novel technologies over the past several decades. Catalyzed by paradigm-shifting public and private programs focusing upon the formation and delivery of genomic and personalized medicine, the need for high-throughput and integrative approaches to the collection, management, and analysis of heterogeneous data sets has become imperative. This need is particularly pressing in the translational bioinformatics domain, where many fundamental research questions require the integration of large scale, multi-dimensional clinical phenotype and bio-molecular data sets. Modern biomedical informatics theory and practice has demonstrated the distinct benefits associated with the use of knowledge-based systems in such contexts. A knowledge-based system can be defined as an intelligent agent that employs a computationally tractable knowledge base or repository in order to reason upon data in a targeted domain and reproduce expert performance relative to such reasoning operations. The ultimate goal of the design and use of such agents is to increase the reproducibility, scalability, and accessibility of complex reasoning tasks. Examples of the application of knowledge-based systems in biomedicine span a broad spectrum, from the execution of clinical decision support, to epidemiologic surveillance of public data sets for the purposes of detecting emerging infectious diseases, to the discovery of novel hypotheses in large-scale research data sets. In this chapter, we will review the basic theoretical frameworks that define core knowledge types and reasoning operations with particular emphasis on the applicability of such conceptual models within the biomedical domain, and then go on to introduce a number of prototypical data integration requirements and patterns relevant to the conduct of translational bioinformatics that can be addressed via the design and use of knowledge-based systems.

Dataset Information

The Simulated Cardiology Clinic: A Standardized Patient Exercise Supporting Medical Students' Biomedical Knowledge and Clinical Skills Integration.

Publications

The Simulated Cardiology Clinic: A Standardized Patient Exercise Supporting Medical Students' Biomedical Knowledge and Clinical Skills Integration.

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