Frimley Integrated Care System uses segmentation and remote monitoring to reduce hospital and GP visits for high risk patients

The segmentation of high risk patients and subsequent remote monitoring is providing impressive results in Frimley Integrated Care System (ICS), demonstrating a reduction in workload for primary care teams, a reduction in hospital and GP visits for patients and enhanced patient outcomes.

The problem

With the primary care workforce under immense pressure, and patients who were not optimised for their long-term conditions (LTCs), Frimley ICS’s Connected Care team wanted to identify and look after complex and frail patients who had the highest risk of experiencing unexpected illness and deterioration over the winter, and prevent these patients going into crisis.

The Connected Care team wanted to build on the excellent work they had done with population health management and remote monitoring that started in Covid, which then expanded into remote monitoring in care homes and a focus on monitoring those with LTCs.

Moving from a reactive to a proactive model of care

The team used data, technology and their workforce to move towards a more proactive and holistic model of care. Since the pandemic, the team has used population health management analytics to identify and segment patients and then work with Graphnet’s sister company, Docobo to provide remote patient monitoring with excellent results.

Anna Fishta, Programme Lead – Connected Care, Frimley ICS says:

As we had a mature integrated record and population health management system, and we had worked so successfully before with the team at Graphnet and Docobo, we were able to build on our learning and progress the project at pace.

Remote monitoring is integrated into our shared care record - wherever the patient presents that information is available at point of care. We were already doing remote monitoring successfully, we just needed to scale up and get ready for our growing programme of work.

To read more about how Frimley are ICS are utilising advanced population health analytics tools in their remote monitoring programme and the results, download the full case study.