Exploring Medical Career Choice to Better Inform Swiss Physician Workforce Planning: Protocol for a National Cohort Study (Preprint)

Abstract

BACKGROUND Medical student career choice directly influences the physician workforce shortage and the misdistribution of resources. Individual and contextual factors related to career choice have been evaluated separately, but their interaction over time is unclear. Secondly, actual career choice, reasons for this choice, and the influence of national political strategies are currently unknown in Switzerland. OBJECTIVE The overall objective is to better understand the process of Swiss medical student career choice and to predict this choice. Our specific aims will examine (1) the static and dynamic variables that predict the career choice of Swiss medical school students as well as their interaction, and (2) the evolution of Swiss medical students’ career choice and their ultimate career path including an international comparison with French medical students. METHODS We will conduct a longitudinal national investigation over 4 years for 4 cohorts of medical students across all Swiss medical schools. Data will be collected using questionnaires at Years 4 and 6 and we will perform a follow-up during postgraduate training year 2 for medical graduates between 2018 and 2022. For Aim 2, in collaboration with the Swiss Institute for Medical Education (SIME) we will implement a national career choice tracking system and identify the final career choice of 2 cohorts of medical students who graduated from 4 Swiss medical schools in 2010-2012. Data analysis will be conducted using inferential statistics and machine learning approaches will be used to refine the predictive model. RESULTS We will explore the dynamic factors influencing Swiss medical students’ career paths from students’ intention to postgraduate medical training and final specialization. We will also identify the relative influence of factors such as gender, motives for specific career choices, individual factors (personality traits, motivation, anxiety) and contextual factors (learning context perceptions). We will assess the differences between different Swiss medical schools and examine the effect of new medical master programs in terms of career choice and location of practice. Finally, using machine learning approaches we will develop a model to predict final career choice of future Swiss medical students. CONCLUSIONS Our research will inform national stakeholders and medical schools on the prediction of students’ future career choice and on key aspects of physician workforce planning. We will identify targeted actions that may be implemented during medical school and may ultimately influence career choice and encourage the correct number of physicians, in the right specialties, to fulfill the needs of currently underserved regions. Potentially, these results could contribute to better management of the medical workforce by balancing future physician distribution and in turn increase the healthcare system efficiency and meet the needs of Swiss society.