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Distributionally robust chance-constrained program surgery planning with downstream resource

Operation room (OR) is one of the key service resources in healthcare resources and plays an important hub role in hospital operation management. We study surgery planning on a given planning period and take service time uncertainty and downstream resource requirements into consideration. Based on the mean and covariance of service time distribution, we develop a distributionally robust chance-constrained programming framework that minimizes operating costs, allocation costs and peak demand of hospital beds under OR capacity constraints. Decisions including which operating rooms to open, allocation of surgeries to ORs on a given planning period. Mathematically, the proposed model can be reformulated as a tractable second order cone programming (SCOP). Finally, we collect real data from public hospital in Beijing and test the proposed framework to explore some managerial insights for hospitals.