An effective admission policy is an essential part of successful management of a patient care system. This admission policy should consider the future availability of resources, e.g. number of beds or budgets available. All possible pathways through the whole patient care system need to be identified to better understand the process dynamics of a care system. In the current paper we show how such patient pathways can be used to predict the care resource requirements in the future. The patient pathways, developed using Markov chain modelling, are used to design an appropriate admission policy to meet future resource availability for the care system. We demonstrate an application of control theory to manage current admission rates to meet future scarce budgetary resource availability. This model can also be used to estimate the effect of an admission policy. Geriatric Patients' data from a London hospital are used to illustrate the approach. An optimization technique is also presented to reduce the implementation complexity and time.