Teaching Physical Examination to Medical Students on Inpatient Medicine Teams: A Prospective, Mixed-Methods Descriptive Study

¹Medical College of Wisconsin Affiliated Hospitals, Milwaukee, Wisconsin. At the time of this study, Dr. Bergl was with the Division of General Internal Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin. ²Medical College of Wisconsin, Milwaukee, Wisconsin.Physical examination (PE) is a core clinical skill in undergraduate medical education.¹ Although the optimal approach to teaching clinical skills is debated, robust preclinical curricula should generally be followed by iterative skill development during clinical rotations.^2,3

The internal medicine rotation represents a critical time to enhance PE skills. Diagnostic decision making and PE are highly prioritized competencies for the internal medicine clerkship,⁴ and students will likely utilize many core examination skills^1,2 during this time. Bedside teaching of PE during the internal medicine service also provides an opportunity for students to receive feedback based on direct observation,⁵ a sine qua non of competency-based assessment.

Unfortunately, current internal medicine training environments limit opportunities for workplace-based instruction in PE. Recent studies suggest diminishing time spent on bedside patient care and teaching, with computer-based “indirect patient care” dominating much of the clinical workday of internal medicine services.^6-8 However, the literature does not delineate how often medical students are enhancing their PE skills during clinical rotations or describe how the educational environment may influence PE teaching.

We aimed to describe the content and context of PE instruction during the internal medicine clerkship workflow. Specifically, we sought to explore what strategies physician team members used to teach PE to students. We also sought to describe factors in the inpatient learning environment that might explain why physical examination (PE) instruction occurs infrequently.

We conducted a prospective mixed-methods study using time motion analysis, checklists on clinical teaching, and daily open-ended observations written by a trained observer from June through August 2015 at a single academic medical center. Subjects were recruited from internal medicine teaching teams and were allowed to opt out. Teaching teams had 2 formats: (1) traditional team with an attending physician (hospitalist or general internist), a senior resident, 2 interns, a fourth-year medical student, and 2 third-year students or (2) hospitalist team in which a third-year student works directly with a hospitalist and advanced practitioner. The proposal was submitted to the Medical College of Wisconsin Institutional Review Board and deemed exempt from further review.

All observations were carried out by a single investigator (A.T.), who was a second-year medical student at the time. To train this observer and to pilot the data collection instruments, our lead investigator (P.B.) directly supervised our observer on 4 separate occasions, totaling over 12 hours of mentored co-observation. Immediately after each training session, both investigators (A.T. and P.B.) debriefed to compare notes, to review checklists on recorded observations, and to discuss areas of uncertainty. During the training period, formal metrics of agreement (eg, kappa coefficients) were not gathered, as data collection instruments were still being refined.

Observation periods were centered on third-year medical students and their interactions with patients and members of the teaching team. Observed activities included pre-rounding, teaching rounds with the attending physician, and new patient admissions during call days. Observations generally occurred between the hours of 7 AM and 6 PM, and we limited periods of observation to 3 consecutive hours to minimize observer fatigue. Observation periods were selected to maximize the number of subjects and teams observed, to adequately capture pre-rounding and new admissions activities, and to account for variations in rounding styles throughout the call cycle. Teams were excluded if a member of the study team was an attending physician on the clinical team or if any member of the patient care team had opted out of the study.

Data were collected on paper checklists that included idealized bedside teaching activities around PE. Teaching activities were identified through a review of relevant literature^9,10 and were further informed by our senior investigator’s own experience with faculty development in this area¹¹ and team members’ attendance at bedside teaching workshops. At the end of each day, our observer also wrote brief observations that summarized factors affecting bedside teaching of PE. Checklist data were transferred to an Excel file (Microsoft), and written observations were imported into NVivo 10 (QRS International, Melbourne, Australia) for coding and analysis.

Checklist data were analyzed using simple descriptive statistics. We compared time spent on various types of rounding using ANOVA, and we used a Student two-tailed t-test to compare the amount of time students spent examining patients on pre-rounds versus new admissions. To ascertain differences in the frequency of PE teaching activities by location, we used chi-squared tests. Statistical analysis was performed using embedded statistics functions in Microsoft Excel. A P value of <.05 was used as the cut-off for significance.

We analyzed the written observations using conventional qualitative content analysis. Two investigators (A.T. and P.B.) reviewed the written comments and used open coding to devise a preliminary inductive coding scheme. Codes were refined iteratively, and a schema of categories and nodes was outlined in a codebook that was periodically reviewed by the entire research team. The coding investigators met regularly to ensure consistency in coding, and a third team member remained available to reconcile significant disagreements in code definitions.