How One School Trains Future Doctors with VisualDx

Katherine Vaillancourt, a 2nd year medical student at Quinnipiac University, shares how VisualDx is used in class.

The second year of classes at Quinnipiac University’s Frank H. Netter MD School of Medicine is studded with thrice-weekly problem-based learning sessions affectionately called PBLs. Students are split into groups of seven to eight students, and each group goes through a paper case that relates to the week’s lecture materials.

The first week of the 2017-2018 academicyear, we had a young African American patient with a history of sickle cell who had a rash. During the course of the case, she began to show signs of disseminated intravascular coagulation (DIC), and it was the group’s job to determine why. The catch was, we didn’t have an image of the rash, only a basic description.

 

Previously, group members had used VisualDx to confirm diagnoses based on a differential, but this exercise allowed us to use VisualDx to create our differential instead of narrowing it. We explored what our patient’s rash could look like using the images in the platform, learning from each explanation and from the variety of graphics, different bodies, angles, skin tones, and ages shown in the images. Ultimately, with a broad differential built from VisualDx and the other case data, we were able to diagnose our patient of the week with parvovirus B19 in the setting of sickle cell anemia that caused DIC. Since then, our group has used VisualDx in many cases, most recently exploring the presentations of acanthosis nigricans in diabetic patients. 

Katherine Vaillancourt is a second year medical student at Frank H. Netter School of Medicine at Quinnipiac University. Katherine has a passion for caring for women and children in underserved communities throughout the world, and has a special relationship with the people of Likoma Island, Malawi, where she is researching community perspectives on birthing care and perinatal mortality.

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