Workload estimation and balancing in home care organizations

Resource planning results to be crucial in Home Care (HC) organizations, due to the large number of human and material resources that have to be properly managed in order to avoid process inefficiencies, treatment delays and poor quality service level. Moreover a large number of variables and unpredictable events affects the service delivery, making the activity amount highly uncertain and mining the feasibility of resource plans. The estimation of patient requirements would support HC providers in human resource planning before the care execution, thus improving the service efficiency. Aim of this work is to develop a stochastic patient model to estimate the patient requests along his care pathway, and to use these estimates for a workload balancing model among the operators. Historical data of one of the largest Italian public HC providers were adopted to develop and validate the model. Numerical results prove the patient model reliability and applicability in practice. As regards the working balancing model, preliminary results show the capability to balance the workload among the operators preserving the continuity of care.