Long-term care (LTC) includes the range of health, social and voluntary support services provided to those with chronic illness, physical or mental disability. LTC has been widely studied in the literature, in particular due to concerns surrounding how future demographic shifts may impact the LTC system’s ability to cater to increasing amounts of patients not withstanding what the future cost impact might be. With that said, few studies have attempted to model demand at the local level for the purposes of informing local service delivery and organisation. Many developing countries with mature and developed systems of LTC in place are under pressure to reduce health care spend, whilst delivering greater value for money. We suggest that the lack of local studies in LTC stems from the lack of a strong case for the benefits of demand modelling at the local level in combination with low quantity and incomplete social care data. We propose a mathematical model to show how savings may be generated under different models of commitment with third party providers. Secondly, we propose a hybrid-fuzzy demand model to generate estimates of demand in the short to medium term that can be used to inform contract design based on local area needs – such an approach we argue is more suited to problems in which historic activity is incomplete or limited. Our results show that commitment models can be of great use to local health care planners with respect to lowering their care costs, at the same time our formulation had wider generic applicability to procurement type problems where commitment size in addition to the timing of commitments needs to be determined
