Process management in healthcare.Sant Camil Hospital case study

Nowadays due to the crisis, some government measures are aimed at reducing healthcare spending, affecting in some level or another the quality offered. Process management is said to be a useful tool for reducing healthcare costs by improving management without any additional economic investment. That is doing more with the same resources and without reducing the quality offered. In this study an empirical case of a Catalan hospital is presented. Overall, the usefulness of process management in the healthcare sector is shown and some tips are provided for those managers that want to implement this management system in their hospitals. This work is also interesting for those managers responsible for the National Healthcare System due to a big question is stated: what would happen if process management was implemented in the whole healthcare system?

Flood risk management: What are the main drivers of prevention?

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Risk management for mathematical optimization under uncertainty

We present a general multistage stochastic mixed 0-1 problem where the uncertainty appears everywhere in the objective function, constraints matrix and right-hand-side. The uncertainty is represented by a scenario tree that can be a symmetric or a nonsymmetric one. The stochastic model is converted in a mixed 0-1 Deterministic Equivalent Model in compact representation. Due to the difficulty of the problem, the solution offered by the stochastic model has been traditionally obtained by optimizing the objective function expected value (i.e., mean) over the scenarios, usually, along a time horizon. This approach (so named risk neutral) has the inconvenience of providing a solution that ignores the variance of the objective value of the scenarios and, so, the occurrence of scenarios with an objective value below the expected one. Alternatively, we present several approaches for risk averse management, namely, a scenario immunization strategy, the optimization of the well known Value-at-Risk (VaR) and several variants of the Conditional Value-at-Risk strategies, the optimization of the expected mean minus the weighted probability of having a "bad" scenario to occur for the given solution provided by the model, the optimization of the objective function expected value subject to stochastic dominance constraints (SDC) for a set of profiles given by the pairs of threshold objective values and either bounds on the probability of not reaching the thresholds or the expected shortfall over them, and the optimization of a mixture of the VaR and SDC strategies.