Employing Operations Research to Improve Health Care Resource Utilization and Planning

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My overall objective is to apply operations research methods to novel issues not yet addressed and extend the scope of these methods to address new relationships, constraints, or other system parameters for the purpose of developing quantitative, evidence based tools which can be used to inform decisions and improve the efficiency of the health care system. In particular, I seek to develop tools to support the improved use, planning and accessibility of health care resources. For the next five years, I aim to particularly focus on the application, scope and methods of system dynamics (SD) modelling. SD is a stochastic, continuous modelling method which simulates systems as a series of stocks and flows through which entity cohorts flow; the flows can be affected by feedback loops. This powerful computer simulation method has not been extensively applied within the health care sector; hence there is substantial opportunity for both new areas of application and for advancing modelling methods. My proposed research program will include at least four major SD research studies including (1) a model of the Canadian orthopaedic surgeon workforce; (2) a model for magnetic resonance imaging (MRI) resource demand and allocation; (3) a province-wide osteoarthritis (OA) patient flow model; and (4) a cancer care pathway model in the Saskatoon Health Region. Each of these studies expands the scope and use of SD modelling in their respective areas. The orthopaedic surgeon workforce model will expand on previous surgical workforce models by including the effects of demand backlogs, surgery and clinical demand interactions, and provider emigration. The MR resource model proposed will also be novel, as no such resource allocation model has yet been developed using SD. The OA model is the first to include co-morbidities and quality of life outcomes in a patient flow model spanning the complete continuum of care for a chronic condition. The cancer model will be the first to simulate the flow of all types of cancer patients, and will be the first to incorporate and simulate the competition that exists for constrained resources and the resulting delays in care.