Using analytics to inform service change

Case study on Covid-19 capacity modelling work undertaken by the north east London Analytics Team 

Across our north east London (NEL) sustainability and transformation partnership, we had to react quickly to the Covid-19 pandemic and make sure we continued to deliver our health and care services in the best way possible. At the same time, we needed to know that any changes we were making in response to the pandemic were having the desired positive impact for our local people. To do this, we used the skills of our analytics team to really make a difference.

Supporting system recovery in primary care

Primary care is a good example of the work that took place. Working with the NEL Primary Care Team, we established a sub-group working with clinicians to develop a model that supported a ‘total triage’ model for general practice.   

Total triage means that every patient contacting the practice for an appointment, first provides some information on the reason(s) for the contact. The purpose of total triage is to get patient needs met by the most appropriate person or service with the minimum amount of hand-off. 

It aims to help practices better meet patient demand within their existing capacity by using the skill-mix of the wider team, using online services, telephone and video consultations as well as face-to-face consultations when needed. To produce an effective operational model, we needed to know what the right service pathways were and we needed excellent analytics.

Initially, this was about looking into pre-Covid-19 demand and capacity, which was then broken up into points of entry for the system, looking at, for example, total number of appointments and consultations per practice and referrals into primary care from NHS 111. We have built on relationships between clinical and commissioning colleagues to work through the process iteratively. Analytics played a vital role to help understand and drive questions around service improvement.

Innovative approach to modelling

Analysts from the Waltham Forest and East London (WEL) Financial Strategy Team came together with a small group of clinicians and with commissioners from NEL Primary Care Team to look at demand and capacity modelling.

Katie Brennan, Deputy Director of Financial Strategy for WEL CCGs, was instrumental in making this happen. She explains, “the team used advanced modelling and analytic techniques to interrogate data, including the data set developed in NEL that links patient records across care settings. Joint working between analysts, clinicians, commissioners and colleagues at provider organisations has been critical to inform inputs into the analysis – and ensure analysis addresses questions that matter most to clinicians and the system.”

Katie also chairs the NEL Covid-19 Analytics Working Group, a regular forum for analysts, clinicians and public health consultants, CCGs, providers, local authorities and analytic service providers within NEL. This group offers a setting to share analytic outputs, receive feedback on modelling outputs and address data questions with analytically minded colleagues across NEL.

The Financial Strategy Team developed a local model for predicting, tracking and monitoring demand for care related to the Covid-19 pandemic. This model has supported demand and capacity planning in acute, community and primary care sectors and has evolved into a decision support tool for future peaks of the virus i.e. if Covid-19 cases are increasing locally, what primary care or community support can be scaled up to support patients.

The modelling and analytics work has helped to shape a solid offer to take up some of the slack around community and out of hospital care. Analysis has been drawing on epidemiological models to look at the curve of demand around Covid-19 and also looking at the assumptions and clinical knowledge around discharge pathways.

“The hard work continues,” says Katie. “As we move into the recovery phase, we are working collaboratively with colleagues across the system. As part of this work we are supporting the out of hospital strategy to meet the 18% targeted reduction in acute non-elective, non-Covid care. East London NHS Foundation Trust (ELFT) and commissioning colleagues in WEL have been instrumental in this and we are also working with colleagues from local authorities to map the important role social care has in supporting local populations and helping the system respond to local needs over the coming months.” 

The impact so far

Katie says: “We have been able to illustrate the tangible benefits of moving to a triage model by using an economic evaluation. The model for the evaluation was developed in collaboration with primary care colleagues from Jubilee Street GP practice in Tower Hamlets”. This practice has been using a triage model of access since 2016 and the evaluation was undertaken pre-Covid.

The evaluation with Jubilee Street Practice showed that although the changes didn’t impact on A&E activity, it did have a significant sustained reduction on overall acute activity and spend, including admissions. This was an interesting dynamic and highlighted where the impact of effective primary care is realised at a system level; by reducing the need for acute hospital activity for patients with more complex needs and co-morbidities. It demonstrated a positive impact, which was evidence-based.”

Katie adds: “This approach to combining analytics and collaborative working with frontline clinicians and service design to inform best outcomes has really made a difference. Analytics is able to inform discussions about what a new approach to care would look like, and the potential impact it would have on people and the system, so that informed debates can take place about the best way forward.

“As well as demonstrating the analytic skills which exist within our teams, it is also an excellent example of how a collaborative process adopting matrix working has enabled us to do a tremendous amount of work in a short space of time. We presented updates at the WEL System Recovery Steering Group, which includes providers Barts and ELFT, and to other NEL-wide governance and system development groups.”

“The great thing about a lot of this work is that while it is supporting Covid-19 directly, it is also in-line with the direction of travel outlined in the NHS Long Term Plan, e.g. providing care closer to home and treatment in less intensive care settings where appropriate. Part of the work is to identify and target where there are opportunities to shift care to different settings and scale up services where required.”

The WEL Financial Strategy Team are also applying these analytical techniques to other areas, such as:

  • Looking at leading indicators which might flag a coming wave of Covid-19. They found measures that went up before a spike in hospital admissions and have put together an analytics dashboard that tracks these and looks at things like the R number within NEL and across London
  • Data on footfall at public transport stations (currently showing that it is still significantly less than pre-Covid levels)
  • Demand modelling for Covid-related testing in NEL
  • Demand modelling for PPE
  • Community care and social care demand modelling
  • Supporting London Covid-19 modelling work and work with academic partners around Covid-19 demand. Plus building bottom-up local modelling to support operational planning and system intelligence.