Submission ID 78266
| Code | OC-1-5 |
|---|---|
| At the end of this workshop, participants will be able to: | |
| Category | Medical Education |
| Type | Oral |
| Will the presenter be a: | Student |
| Title | Using Learning Analytics to Examine How Preceptors Describe Chest Pain Symptoms in Male versus Female Patients |
| Background/Purpose | Coronary heart disease is the leading cause of death for females. Misunderstanding gender differences in heart disease symptoms results in misclassification of symptoms and underdiagnosis in female patients. To address this problem, we used learning analytics to explore how preceptors discuss chest pain presentations during clinical teaching. Specifically, we examined how often chest pain was described as 'atypical', and compared rates of 'atypical' designations between the sexes. |
| Methods | Learning analytics (secondary data analysis) of 12 years (July 2010 - June 2022) of archived FieldNotes (workplace-based formative assessments). FieldNotes include narratives capturing feedback to learners and descriptions of patient presentations, thus serving as a proxy for clinical teaching discussions. We first searched for FieldNotes about chest pain (example terms: "chest pain", "heart", "MI", etc.). Extracted FieldNotes were then searched for the term 'atypical', and to determine the sex of the patient. Analysis was descriptives and Chi-square goodness of fit to test the assumption that the proportion of 'atypical' classification was equal across sexes. |
| Results | The database (N = 64,942) search identified 677 (1.04%) FieldNotes about chest pain. Of those, 76 (11.2%) described symptoms as 'atypical'. 'Atypical' classification varied by patient sex (male = 11; female = 32; unspecified = 33). Female patients' chest pain symptoms were described as 'atypical' significantly more frequently (X2 = 18.24; df = 2; p = 0.00011). |
| Discussion | Our findings indicate a need for targeted faculty development. Our study demonstrates the value of learning analytics for examination of quality-of-care issues and practice quality improvement. |
| Keyword 1 | postgraduate |
| Keyword 2 | assessment |
| Keyword 3 | patient outcomes |
| Abstract content most relevant to: (check all that apply) | Residency Education |
| Abstract Track - First Choice | Assessment |
| Assessment | Competency-based assessment Written/Narrative |
| Authors | Zoe Brody Shelley Ross |
