Needs assessment of essential anatomy: The perspective of adult primary care resident physicians

Abstract

Curricular development and modification involve first identifying a problem and then performing a needs assessment, which can guide the design of curricular components.Pedagogical changes, coupled with reductions in curricular time for gross anatomy, pose challenges and impose restrictions within medical school curricula. In order to make anatomy education effective and efficient, it is important to determine the anatomy considered essential for medical education through a targeted needs assessment. In this study, 50 adult primary care resident physicians in family medicine (FM) and internal medicine (IM) were surveyed to assess the importance of 907 anatomical structures, or groups of structures, across all anatomical regions from a curated list based on the boldface terms in four primary anatomy texts. There were no statistically significant differences in the ratings of structures between the two groups for any anatomical region. In total, 17.0% of structures, or groups of structures, were classified as essential, 58.0% as more important, 24.4% as less important, and 0.7% as not important. FM residents rated tissues classified as skeleton, nerves, fasciae, anatomical spaces, blood vessels, lymphatics, and surface anatomy (p < 0.0001) significantly

A Survey of Essential Anatomy from the Perspective of Anesthesiology, Emergency Medicine, Obstetrics and Gynecology, and Orthopedics Resident Physicians

“…The present study, in combination with Hankin et al (2023), which surveyed primary care residents, contributes to a database of anatomical structures assessed from a clinical perspective that may be considered when determining foundational anatomy for UME curriculum, as well as for graduate medical education.…”

“…Furthermore, the subjective interpretation of a given rating value may vary from person to person, and it is generally considered inappropriate to use parametric descriptive statistics such as means and standard deviations with ordinal data (Allen and Seaman, 2007). Therefore, to interpret this study's ndings, a post-hoc classi cation system rst described by Hankin et al (2023) was utilized to account for the limitations associated with ordinal data. This classi cation system rst collapsed the 4-points in the rating scale into a binary variable: ratings of 1 and 2 were combined to form the lower component and ratings of 3 and 4 formed the higher component of the variable (the higher component will be referred to as "3 + 4%").…”

“…The present study, which followed the research design of Hankin et al (2023), surveyed a sample of nonprimary care resident physicians in anesthesiology, emergency medicine, obstetrics and gynecology, and orthopedics at Beaumont Hospital/OUWB regarding their opinion of the anatomy considered most important for their specialties. The response rates varied from 33.3% for AN residents to 84.0% for OR, with a combined response rate of 50.5%, which was similar to those reported in Wilson et al, (2024) for students (52.0%), and slightly lower for healthcare professionals and faculty (59%).…”

Essential anatomy for core clerkships: A clinical perspective

“…The survey in the present study was based on an earlier instrument used in Hankin et al, 43 which included 907 structures/groups of structures. The survey in the present study consolidated many of these individual structures into 97 anatomical topics, each of which referenced numerous anatomical structures (see Supplemental file S1).…”

“…As a result, the subjective interpretation of a value in ordinal measurements can vary by individual, and it is generally considered inappropriate to use parametric descriptive statistics such as means and standard deviations with ordinal data 44 . Consequently, the present study adopted the classification system used by Hankin et al, 43 that accounts for the limitations associated with ordinal data and provides a categorical basis for interpreting the findings. This classification system collapsed the four‐point scale ratings into a binary variable: ratings 1 and 2 were combined to form one category and ratings 3 and 4 were combined to form the second category.…”