Sustained Clinical Performance During Surgical Rotations Predicts NBME Shelf Exam Outcomes

Comparing the Performance of Popular Large Language Models on the National Board of Medical Examiners Sample Questions

INTRODUCTION

Large language models (LLMs) have transformed various domains in medicine, aiding in complex tasks and clinical decision-making, with OpenAI's GPT-4, GPT-3.5, Google's Bard, and Anthropic's Claude among the most widely used. While GPT-4 has demonstrated superior performance in some studies, comprehensive comparisons among these models remain limited. Recognizing the significance of the National Board of Medical Examiners (NBME) exams in assessing the clinical knowledge of medical students, this study aims to compare the accuracy of popular LLMs on NBME clinical subject exam sample questions.

METHODS

The questions used in this study were multiple-choice questions obtained from the official NBME website and are publicly available. Questions from the NBME subject exams in medicine, pediatrics, obstetrics and gynecology, clinical neurology, ambulatory care, family medicine, psychiatry, and surgery were used to query each LLM. The responses from GPT-4, GPT-3.5, Claude, and Bard were collected in October 2023. The response by each LLM was compared to the answer provided by the NBME and checked for accuracy. Statistical analysis was performed using one-way analysis of variance (ANOVA).

RESULTS

A total of 163 questions were queried by each LLM. GPT-4 scored 163/163 (100%), GPT-3.5 scored 134/163 (82.2%), Bard scored 123/163 (75.5%), and Claude scored 138/163 (84.7%). The total performance of GPT-4 was statistically superior to that of GPT-3.5, Claude, and Bard by 17.8%, 15.3%, and 24.5%, respectively. The total performance of GPT-3.5, Claude, and Bard was not significantly different. GPT-4 significantly outperformed Bard in specific subjects, including medicine, pediatrics, family medicine, and ambulatory care, and GPT-3.5 in ambulatory care and family medicine. Across all LLMs, the surgery exam had the highest average score (18.25/20), while the family medicine exam had the lowest average score (3.75/5).  Conclusion: GPT-4's superior performance on NBME clinical subject exam sample questions underscores its potential in medical education and practice. While LLMs exhibit promise, discernment in their application is crucial, considering occasional inaccuracies. As technological advancements continue, regular reassessments and refinements are imperative to maintain their reliability and relevance in medicine.

New Heuristics to Stratify Applicants: Predictors of General Surgery Residency Applicant Step 1 Scores

OBJECTIVE

In 2022, United States Medical Licensing Examination (USMLE) Step 1 scores will become pass/fail. This may be problematic, as residency programs heavily rely on USMLE Step 1 scores as a metric when determining interview invitations. This study aimed to assess candidate application metrics associated with USMLE Step 1 scores to offer programs new cues for stratifying applicants.

DESIGN

Retrospective cohort study analyzing interviewed applicants to one general surgery residency program in 2019 and 2020. Applicant data analyzed included USMLE Step 1 scores, number of publications, clerkship scores, letter of recommendation scores (out of 2, scored by 0.25 interval), interview overall score (out of 5, scored by integer level), and standardized question score (out of 10). Each year, applicant's answers to one standardized behavioral question during their interview were scored by interviewers.

SETTING

Tertiary medical center, academic general surgery residency program.

PARTICIPANTS

Interviewed applicants at one general surgery residency program whose applications contained complete demographic information (203 out of 247).

RESULTS

Multiple Linear Regression revealed that higher surgical clerkship (β = 0.19, p = 0.006) and higher standardized interview question (β = 0.32, p < 0.001) scores were positively associated with applicant USMLE Step 1 score (F[7, 195] = 6.61, p < 0.001, R2 = 0.19). Letter of recommendation score, number of peer reviewed publications, gender, race, and applicant type (preliminary/categorical) were not associated with USMLE Step 1 scores.

CONCLUSIONS

With USMLE Step 1 scores transitioning to pass/fail, surgical residency programs need new selection heuristics. Surgery clerkship scores and standardized behavioral questions answered by applicants prior to the interview could provide a holistic view of applicants and help programs better stratify candidates without USMLE Step 1 scores.

Surgical clerkship: Do examination scores correlate with clinical performance?

BACKGROUND

This study aims to determine if there are correlations between clinical performance and objective grading parameters for medical students in the third-year surgery clerkship.

METHODS

Clerkship grades were compiled from 2016 to 2020. Performance on clinical rotations, NBME shelf exam, oral exam, and weekly quizzes were reviewed. Students were divided into quartiles (Q1-Q4) based on clinical performance. Standard statistical analysis was performed.

RESULTS

There were 625 students included in the study. Students in Q1+Q2 were more likely than those in Q3+Q4 to score in the top quartile on the shelf exam (29% vs. 19%, p = 0.002), oral exam (24% vs. 17%, p = 0.032), and quizzes (22% vs. 15%, p = 0.024). However, there was negligible correlation between clinical performance and performance on objective measures: shelf exam (R² = 0.027, p < 0.001), oral exam (R² = 0.021, p < 0.001), and weekly quizzes (R² = 0.053, p = 0.092).

CONCLUSIONS

Clinical performance does not correlate with objective grading parameters for medical students in the third-year surgery clerkship.

Evaluating knowledge and skill in surgery clerkship during covid 19 pandemics: A single-center experience in Indonesia

Backgrounds

Surgery clerkship for medical students has been changed in response to clinical exposure limitation due to this pandemic. This study aim to evaluate knowledge and skill of students in surgery clerkship in covid 19 pandemics.

Methods

Cross-Sectional design comparing surgery clerkship before and during COVID-19.A total of 270 fourth and fifth-year medical students have enrolled in surgery clerkship from June 2019–October 2020 were selected for this study. Each student had completed education and training in the hospital for nine weeks in the rotation.

Results

There is no significant difference in MCQs scores before and during the pandemic. However, a significant difference was found in OSCE scores.

Conclusions

Combining virtual platforms and in-person clinical rotation is an effective surgery clerkship curriculum, particularly in pandemic covid 19. There are no different skill and knowledge results before and during the pandemic analyzed from MCQs and OSCE exam.

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An observational study compared knowledge and skills-based exam scores before and during the COVID-19 period in surgery clerkship.

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Knowledge score exam was found no difference before and during the COVID-19 period.

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The skills-based exam was found significantly better in students during the COVID-19 period.

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A combination of online and offline learning in surgery clerkship is an effective method in this pandemic era.