Introduction: National organizations have identified a need for the creation of novel approaches to teach clinical reasoning throughout medical education. The aim of this project was to develop, implement and evaluate a novel clinical reasoning mapping exercise (CResME).
Methods: Participants included a convenience sample of first and second year medical students at two US medical schools: University of Central Florida (UCF) and Uniformed Services University of Health Sciences (USUHS). The authors describe the creation and implementation of the CResME. The CResME uses clinical information for multiple disease entities as nodes in different domains (history, physical exam, imaging, laboratory results, etc.), requiring learners to connect these nodes of information in an accurate and meaningful way to develop diagnostic and/or management plans in the process.
Results: The majority of medical students at both institutions felt that the CResME promoted their understanding of the differential diagnosis and was a valuable tool to compare and contrast elements of a differential diagnosis. Students at both institutions recommended using the CResME for future sessions.
Discussion: The CResME is a promising tool to foster students' clinical reasoning early in medical school. Research is needed on the implementation of the CResME as an instructional and assessment strategy for clinical reasoning throughout medical school training.
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http://dx.doi.org/10.1007/s40037-018-0493-y | DOI Listing |
Diagnosis (Berl)
January 2025
MedStar Washington Hospital Center, Washington, DC, USA.
Objectives: Published clinical reasoning curricula are limited, and measuring curricular impact has proven difficult. This study aims to evaluate the impact of a broad-reaching, multi-level reasoning curricula by measuring utilization of clinical reasoning terminology in published abstracts.
Methods: In 2014, the University of Pittsburgh Medical Center (UPMC) created a clinical reasoning curriculum with interventions at the student, resident, and faculty levels with the goal of bringing reasoning education to the forefront.
J Prosthodont
January 2025
Department of Advanced Prosthodontics, Graduate School of Medical and Dental Sciences, Institute of Science Tokyo, Tokyo, Japan.
Purpose: This study aims to evaluate the effectiveness of a case-based reasoning (CBR) system in predicting the design of definitive obturator prostheses for maxillectomy patients.
Materials And Methods: Data from 209 maxillectomy cases, including extraoral images of obturator prostheses and occlusal images of maxillectomy defects, were collected from Institute of Science Tokyo Hospital. These cases were organized into a structured database using Python's pandas library.
Int J Clin Pharm
January 2025
Division of Pharmacoepidemiology and Clinical Pharmacology, Department of Pharmaceutical Sciences, Utrecht University, PO Box 80082, 3508 TB, Utrecht, The Netherlands.
Background: Moral case deliberation has been successfully implemented in multidisciplinary groups of secondary care professionals to support ethical decision making. It has not yet been reported for community pharmacists.
Aim: This study investigated whether moral case deliberation fosters moral reflectivity in community pharmacists.
BMC Med Educ
January 2025
Department of Neurology, the First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, 518000, China.
In the modern medical education system, teaching of clinical neurology in outpatient settings is crucial for training future neurologists. The neurology outpatient clinic is a pivotal setting for both initial consultations and follow-up visits. It plays a significant role in the prevention, diagnosis, treatment, and ongoing monitoring of neurological disorders, and is a critical platform for clinical education.
View Article and Find Full Text PDFBackground: Early detection and personalized care for Alzheimer's Disease (AD) mitigate the devastating consequences for millions of people around the globe. In the current scenario, there is a lack of user-friendly AI applications for predicting and understanding the progression of AD. The application should address the critical need for a predictive analytics tool that offers timely and transparent insights by utilizing the patient data.
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