Summary

In response to the Covid-19 pandemic, Central London Community Healthcare Trust (‘CLCH’) needed to rapidly reconfigure community services and redeploy resources to implement national emergency response measures, whilst effectively supporting system partners and maintaining high quality care for the local population. The core of the CLCH pandemic response to date has been evidence based, data led decision making and in support of this, CF developed an interactive demand and capacity (‘D&C’) modelling tool to support operational decision making. The interactive D&C tool enabled projected capacity constraints to be effectively managed, resource deployment to be optimised and provided assurance for service restitution planning.

Challenge

Gaining a comprehensive understanding of Trust capacity, how it could be effectively deployed to support rapidly evolving service demand and the impact of these changes on longer term community service provision

The impact of Covid-19 to date has placed unprecedented pressures on an already strained workforce, and in recognition of this, CLCH sought to evaluate the likely impact of the pandemic on their capacity to deliver safe, high quality care in the community. In addition, the Trust also recognised that the demand for community services would significantly increase and they were likely to have to support patients with higher acuity and greater care needs out in the community. Therefore, in order to effectively support staff and patients, the Trust sought clarity on the likely pattern of demand, the associated care requirements and the impact of meeting this on normal service provision in the community. 

Outcome: Enabling data led decision making and supporting operational teams to manage capacity constraints and implement plans

CF worked in collaboration with the Chief Operating Officer (‘COO’) and operational teams to develop a 3-month and 18-month interactive demand and capacity tool for bedded and non-bedded services across CLCH. This tool provided a view of projected capacity constraints across community services and identified potential ways to mitigate these challenges. 

The tool enables the user to modify a range of parameters to reflect the evolving nature of the pandemic and understand the impact on projected demand and capacity. These parameters can be seen in figure 1:

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Figure 1: D&C model parameters. *N.B. This list is not exhaustive

In addition, the CF team worked with operational teams to implement decisions taken utilising the D&C tool outputs, such as mobilising additional surge bed capacity, redeploying staff to manage capacity constraints and developing service restoration plans which factor in the impact of referral to treatment (‘RTT’) backlogs.

 

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Figure 2: Non-bedded D&C workforce dashboard. *N.B. please note this is dummy data.
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Figure 3: Bedded Trust-wide D&C output. *N.B. please note this is dummy data

Methodology

The interactive D&C tool was built in partnership with the COO to ensure that it was reflective of the way community services operate and interact with the wider system, and was continually tested and iterated with local operational teams

Data analysis and tool development – the CF team analysed historic Trust data, outputs from the CF pan-London modelling team and inputs from CLCH operational teams to inform the development of the D&C model and the supporting assumptions. The relevant components of the analysis was incorporated into additional operational tools to support local teams e.g. a staff redeployment tool and a waiting list management dashboard.

Consultation and refinement – the data within the D&C tool was regularly updated as actuals became available. As the national and pan-London picture evolved, the model itself was iterated, and additional functionality was built in, to support operational teams to meet emerging patient needs and provide reporting and assurance to system partners.

Training and handover workshops – the CF team delivered a series of handover workshops to upskill the local team and took them through a virtual simulation to put into practice what they had learnt.

Results

*Supported CLCH’s data-led decision-making approach through the first peak and upskilled local teams to take on both the demand and capacity modelling and modify the tool for future workforce planning

*Developed an interactive D&C tool for the Trust and a range of supporting operational tools

*Supported the CLCH data-led decision-making approach and supported the operational teams to implement key decisions

*Upskilled local teams in modelling and adapting the D&C tool for future Covid and non-Covid requirements

Testimonial

“The team delivered against a developing and complex brief at a time of rapid organisational change, ensuring that not only a tool was developed, but that insights were understood and embedded. Each member of the team was invaluable in terms of insight and professional delivery”

James Benson, Chief Operating Officer