With the ageing population in developed countries, the growing prevalence of chronic diseases and national trends to move away from treating patients in hospitals, community care is becoming increasingly important to relieve pressure from acute care settings. Unlike hospital beds though, capacity in community care is typically organised on a slot basis, with care professionals visiting patients at their home or some other appropriate community facility. At the start of their engagement with community care, patients are often in need of more frequent visits by care professionals, with the need decreasing over the length of the engagement. While there are examples in the literature of modelling slot-based capacity, this particular aspect of community care makes the development of simulation models more intriguing. We present a time-driven simulation model we developed in the R programming language and software environment. The aim of our study was to help with estimating capacity for those community teams who deliver care to patients whose care needs decrease over time. We used the model to conduct a number of what-if and sensitivity analyses using the case of a stroke rehabilitation and care service. Simulation results showed that, perhaps unsurprisingly, the different approaches of introducing the differential care need of patients in the model has an impact on capacity estimation.
|Publication status||Published - 2019|
|Event||30th European Conference on Operational Research - Dublin, Ireland|
Duration: 23 Jun 2019 → 26 Jun 2019
|Conference||30th European Conference on Operational Research|
|Period||23/06/19 → 26/06/19|
Vasilakis, C., De Prez, M., & Wood, R. (2019). Supporting visits-based capacity planning in community care through novel computer simulation models. Abstract from 30th European Conference on Operational Research, Dublin, Ireland.