Changes in Resident Graduate Characteristics in a Large Pathology Training Program, 1994 to 2013

Abstract

The field of pathology has changed dramatically over the recent decades and has become more complex with emphasis toward subspecialization. These changes potentially influence resident training as programs and trainees search for cutting-edge skills in the evolving field. Over the last 20 years, our institution’s residency education was modified profoundly to emphasize subspecialty practice. Furthermore, efforts were made to search for and recruit candidates who desired such training. In this study, we examined a 20-year time period to determine how these changes may have influenced the characteristics of our resident graduates. For each trainee who graduated from our pathology residency program (1994-2013), the following parameters were evaluated: highest academic degree, gender, graduating medical school, type of training, number of publications during residency, enrollment in fellowships, and type of career position. The data collected were divided into 4 time periods. Fisher exact test and 2-tailed t test were used for statistical analyses comparing the first half (1994-2003) to the latter half (2004-2013) of the study. In the second half, there were more graduates who pursued single track pathology training—anatomic pathology or clinical pathology versus combined anatomic/clinical pathology training (P = .035), more first author and total publications per graduate during residency (P < .001), more graduates who enrolled in fellowships (P < .001), and a greater tendency toward an academic career position than all other types combined (P = .034). In parallel to the subspecialization trends in our department, we witnessed changes in the characteristics of our resident graduates whose interests and career choices have become more focused.

How to Succeed in Fellowship Acquisition: A Survey of Pathology Residents

“…In the past 2 decades, the number of pathology trainees who have pursued pathology subspecialty training after residency has increased, 9,10 and this has led to a highly competitive atmosphere among residents. However, it is difficult for pathology trainees to have adequate exposure to and understanding of how to best pursue and acquire their desired fellowship.…”

Seeing the random forest through the decision trees. Supporting learning health systems from histopathology with machine learning models: Challenges and opportunities

“…69,70 Besides refining their visual recognition capabilities, 69,70 they are expected to learn a conceptual framework and the field-specific terminology to make diagnoses. 59,60,[70][71][72][73][74][75] Once graduated, with the proper clinical/surgical data and relevant auxiliary tests' results (e.g., obtained with immunohistochemical or molecular studies), pathologists make diagnoses by comparing the visual information they extract from patients' tissues/samples against sets of diagnostic/classification criteria (i.e., only after confirming that a tissue/sample meets some diagnostic/classification criteria do pathologists assign a disease name/classification category to it). 56,60,76,77 These sets of diagnostic/classification criteria are listed in histopathology classifications such as the WHO Classification of Tumours 78 and generally use concepts 60,79,80 to describe the presence/absence and the spatial distribution of some normal/abnormal cells and tissue components.…”