The COVID-19 pandemic is putting significant strain on health systems across the world. Whilst there has been a huge effort to try to plan for healthcare delivery to maximise access to beds, ventilators and ICU capacity for COVID-19 patients, and PPE for those delivering this care, one research area currently largely neglected is supporting the planning for End of Life Care delivery.
It is an unfortunate reality that, regardless of the capacity of health services to care for those with COVID-19, and mitigate symptoms, it is currently an incurable disease, and so a percentage of people, particularly those who are elderly or who otherwise have complex care needs, will die. Therefore, it is vital that adequate “stuff” and “staff” end of life care resources are in place to ensure that those who die from the disease have as comfortable and painless a death as possible.
Unfortunately, with end of life care resourcing already stretched, there is a real need to understand the potential additional resourcing requirements to meet incoming demand and continue to provide high quality end of life care.
Organisations such as the WHO and NICE highlight the importance of individualised care at the end of life, and there is a growing recognition that end of life care planning has, thus far, been neglected in planning for the pandemic.
1. To develop a generic simulation model of end of life care needs for COVID-19 patients, along with the associated resourcing of “stuff” and “staff”, in order to predict the level of resourcing needed to meet demand from COVID-19 patients. 2. To populate the model with data from Bristol, North Somerset and South Gloucestershire, and use it to predict resource needs in the locality. 3. To make the model available nationally and internationally as free and open source software. 4. To write a paper for submission to a peer-reviewed journal outlining the development of the model and its use to predict COVID-19 end of life care resources in the Bristol, North Somerset and South Gloucestershire locality.
The model is being developed as a Discrete Event Simulation model using the Python-based SimPy framework, and will be made freely available as open source software using the Google CoLaboratory platform. The model captures the incoming rate of COVID-19 end of life care activity in three settings – at home, in a care home and in hospital, and incoming rates may be increased or decreased to capture growth or decline in cases over time.
Each patient in the model has a randomly sampled duration for their end of life care, and is allocated a “bundle” of resources that differs depending on their care setting and the complexity of their needs. Each bundle specifies the resources needed to deliver end of life care, along with the frequency with which these resources are needed.
There are seven resources in the model – five “staff” resources (District Nurse time, Care Assistant time, Specialist Palliative Care (local hospice support) time, GP time and Hospital Nurse time) and two “stuff” resources (Anticipatory Medicine bundles to alleviate symptoms such as pain, breathlessness and nausea, and Syringe Pumps to deliver some of these medications). The model calculates the resource utilisation over a simulated period of time.
- Charlotte Chamberlain, Bristol Medical School
- Rohan Kandasamy, University Hospitals Bristol and Weston
- Sara Robbins, University Hospitals Bristol and Weston