NELFT’s Pat Smith, Head of Unplanned Care/Rehabilitation & Therapy Lead and Ingrid Lampey, Nurse Consultant, Adult Community Nursing, met with Ashish Mohanty, Demand and Capacity Technical Manager, and Wendy Rees, ECIST Improvement Advisor from NHS England Improvement to talk through a prototype demand and capacity modelling tool designed specifically for community urgent response teams.
Ashish Mohanth and Pat Smith
Most of us will know what it feels like, when we, or someone we know, are waiting for support with an urgent need. So, how do we make sure that people can access services as quickly as possible and how do we align resources with demand, enabling our workforce to do what they come to work for: to provide good care for patients?
Robust demand and capacity planning is crucial to building plans that are realistic and deliverable. Demand and capacity models for acute services have been established for some time now, and are being used by acute trusts to better plan their services. There is however a gap that exists in models for community services, a gap that the NHS England Improvement’s Demand and Capacity Team is aiming to bridge.
Community teams have a multi-faceted and diverse workload, supporting people in their own home or to return home quickly if admitted to hospital. The way community teams work, and the information gathered in these organisations, differs significantly from acute providers. This means it is not a simple case of adapting the established demand and capacity tools that acute services are using.
Pathways in community settings can vary across teams and organisations as they respond to local need, requiring different skills and response timeframes. This, and the variability in the data infrastructure in community organisations, means it is essential to establish what information is already collected, and what gaps need to be bridged. In some cases, time and effort may need to be invested to ensure that the data required is captured and easily available, but ultimately, this is something that has a real potential to improve team effectiveness and improve outcomes for patients.
The Demand & Capacity Team have been working alongside the Emergency Care Improvement Support Team (ECIST), reaching out into the community to learn how a modelling tool may help plan and deliver services to patients. The response has been positive, and front-line teams are shaping the development of an urgent response demand and capacity modelling tool.
Waltham Forest Rapid Response team
The Waltham Forest Rapid Response team provides a range of highly specialised urgent care services to patients managing varying levels of demand across the day and night. The service provides assessment, treatment and support to patients who are experiencing a crisis and who might otherwise be admitted to hospital. The team also provides an urgent assessment service for worsening health problems, minor injuries and minor illnesses and works closely with GPs, social and community services including care homes, to ensure patients are supported in a home environment wherever possible.
The variety of services offered to patients, by the team, includes full assessment within 2 hours of referral, support visits, IV antibiotics, ECG, unscheduled and urgent venepuncture, and sub-cut fluids for hydration support, making demand and capacity modelling more complex, but not impossible. The Waltham Forest Rapid Response team feel having a tool which can assist in demand and capacity modelling would be helpful to inform the way the multi-professional workforce is planned, and also predict the impact of changes in demand, such as new commissioned pathways.
Here is an example of output from the modelling tool:
Wendy and Ash said “Talking to Pat and Ingrid was so valuable – we learnt about the challenges of delivering urgent care in the community, balancing the demand from patients at home, families, GPs and other health care professionals, alongside the demand from acute hospitals to avoid admissions and reduce length of stay.”
Feedback from NELFT alongside other community teams, including those providing urgent mental health services, has enabled a prototype tool to be developed. The model will predict what resources need to be deployed in the community, and where. This can support service planning, helping ensure patients in the community receive the care they need in a timely fashion.
The model is now in the testing phase with a view to produce a working tool before spring 2020.