How we created a tool to predict what workforce we would need based on COVID-19 waves
As the COVID-19 pandemic kicked in, it was clear that pressure on acute and community health services would be heightened. We showed a commitment to acting as part of the wider health system to ensure that the right staff could be circulated to the right services at the right time. In our Lancashire children’s community services alone, we trained more than 100 staff to be part of a redeployment bank to support our adult community services team in West Lancashire, the local acute trust and to be part of a new care home swabbing team for the county.
As this activity progressed however, it became apparent that the pandemic would not just bring a swift peak and then settle, but rather would be a series of waves over a longer period of time. Therefore, we needed to be able to predict how our workforce requirements would shift more regularly so that we could make sure we had the right staffing throughout. This would also enable us to be able to confidently release staff to the wider system and draw on that same system for support when it was needed the most.
We created a capacity and demand tool that takes data relating to local COVID-19 cases, profiled from acute trusts, and predicts what the workforce requirements will be each day for our community services teams, drilling down to what demand will be for different types of care, eg. end of life care, active COVID-19 cases being cared for in the community etc.
We also included a ‘resilience allowance’ which factored in the amount of time staff would need to have adequate capacity for breaks, downtime, and donning and doffing PPE, in order to manage the impact on staff wellbeing during this difficult time.
Once figures started to be inputted, what started as a prediction tool ended up becoming a management tool that had the ability to plot and read impact.
The tool was launched in our Kent community services to support district nursing. We worked with our commissioners to align their system demand predictions with a local service plan. The tool allowed the service to predict capacity and workforce needs and also in realtime prioritise workload to manage demands as needed. As a result, we were able to feed information to the CCG so they could have an overview of an impact on their whole system.
In West Lancashire, we took data from the local discharge cell, including the exact numbers of COVID-19 cases in the acute trust, and entered the dates that we expected the peak to arrive for our community services team. This tended to hit 14 days after the hospital peak. Once we had inputted this information, the tool was able to show how many patients we could expect each day and therefore what workforce we would require. This informed the successful redeployment strategy for the area.
In West Lancashire, the tool enabled early identification of issues around workforce capacity due to COVID and data shows that, as a result, we remained within the safe staffing threshold throughout.
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