Restructuring the resident training system for improving the equity of access to primary care


Published: 20Apr2017

Authors: Anna Graber-Naidich, Michael W. Cartera, Vedat Verter

Publication: European Journal of Operational Research, Volume 258, Issue 3, 1 May 2017, Pages 1143–1155


Many countries experience maldistribution of health professionals, represented by a mismatch between the spatial distribution of inhabitants and that of the providers. Various policies are employed by the governments to attract workforce to underserved communities. For example in Canada, such policy initiatives as alternative models of care for rural areas, promotion of rural medicine programs and financial incentives and many more were used to try and improve the situation. Despite these efforts, the disparity continues. Empirical evidence suggests that the most pertinent factor affecting health professionals’ choice to practice in underserved and rural communities is their background. In particular, research shows that trainees of rural background are much more likely to practice in rural areas, once training is finished. The proposed MIP optimization model concentrates on education as a means to improve the spatial distribution of professionals. It incorporates interests of two main stakeholders, namely the regulator (in the objective function) and the health professionals (directly incorporating the choice patterns of the graduates), and provides the optimal training locations and required backgrounds of trainees in each location. A realistic case for designing the postgraduate family-medicine education program of Ontario is provided. We have demonstrated that depending on the choice patterns of the trainees, an improved distribution of professionals can be achieved by better positioning locations of residency training. More importantly, we demonstrate that in some cases, expanding the programs and training a larger number of trainees without taking their backgrounds into consideration can worsen the future inequity.

Read full abstract: European Journal of Operational Research