Health Care Operations Management

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The objectives of my research program are to improve understanding about the ways in which various health care systems operate and to develop mathematical models to support design and planning in health care. Recently, the focus of scholarly work in operations research and operations management has shifted toward greater emphasis on empirical investigation of fundamental assumptions made in the mathematical models that researchers in these fields have developed. There is increasing evidence, for example, that "servers" (for example, line workers in factories or nurses in hospitals) do not process work at a constant rate. Servers adapt to their environment (the amount of work that needs to be done and the number of coworkers available to do the work) and they slow down when they become fatigued. What is less clear are the implications of such adaptive server behaviors for capacity planning. There is a tradeoff between increasing model complexity, by incorporating a more realistic description of human and system behavior, and the additional information that more realistic models provide for planning purposes. How suboptimal are capacity recommendations that are derived from constant processing rate models? Do capacity recommendations change in systematic ways when adaptive server behavior is incorporated into capacity planning models?