A patient stochastic model to support human resource panning in home care

A large number of variables and unpredictable events affect the quality of home care (HC) services. Changes in patient clinical and social conditions and troubles in service organisation are only some examples that can make the management of HC activities quite difficult. The estimation of patient requirements would support HC providers in human resource planning before the care execution, thus improving the service efficiency. This article proposes a stochastic model to represent the patient’s care pathway; on the basis of historical data of an HC structure, the model provides predictions on the major variables of interest: how many patients are followed up in the course of time and, for each of them, the duration of care and the amount of required visits. The predicted variables of interest provide information about the future workload of each operator. This becomes a useful support tool for human resource planning in the medium and short terms. Numerical results prove the applicability of the proposed stochastic model in practice.