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.

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.’

Advanced population health analytics and tools 

The team already had in place robust population health management analytics to identify patients and had also rolled out remote patient monitoring. They use Graphnet’s advanced population health tools to identify and target their most complex and frail patients. Connected Care integrates with the Johns Hopkins ACG® System to provide patient profiling. By using the ‘Patient Need Group’ (PNG) segmentation tool within the ACG System, the team were able to identify and target high risk patients in the area.  The population health analytics solution looks at patient diagnoses and patient needs, enabling the Frimley team to identify and target high risk patients in the top two PNGs that are comprised of the most complex patients.

Anna says: ‘We wanted to use our data and technology differently to support high risk patients – those who might be at danger over winter. We used our advanced population health platform to drill down and carry out segmentation to identify higher risk patients, using the PNGs to identify those at risk of polypharmacy. We didn’t want to refer individual patients into remote monitoring – as this would be extremely time consuming – using the solution we were able to quickly and easily identify a suitable cohort.’

Results

24 practices are now part of the service, with over 4,500 patients having been identified as suitable to be part of the initiative. 1,700 high risk patients are now being supported by remote monitoring, with the digital health team dealing with 98% of the alerts.

Frimley ICS has carried out preliminary evaluation of 545 patients against a control group of high-risk patients not enrolled in remote monitoring.

The team plotted the change in admissions before and after intervention, this is compared to their expected admissions if they exhibited the same trend as the control group.

The control group was set as any patient currently in the top two Patient Need Groups not enrolled in the programme. For enrolees, the team compared 12 months of activity pre-enrolment to activity post enrolment (average follow period of 2.6 months). For controls they compared monthly activity 12 months before the programme started (Dec 21 – Nov 22) to the 3 months since the programme have started (December 22 – February 23).

Key Insights

How does the remote monitoring programme work?

• Once the potential patients have been identified using the population health analytics / ACG System, patient lists are sent to community providers set up to provide first line support for remote monitoring.
• Patients receive a phone call to onboard them onto the remote monitoring scheme and are offered a clinically defined complex care package.
• Patients are then visited and given necessary equipment and trained on what to submit and when – either using their own device or a smart device known as CAREPORTAL^®.
• The remote monitoring consists of a ‘weekly question set’ to complete and a monthly question set for patients who are stable. There is also an ‘unwell and deteriorating’ question set for the patient to use if they feel unwell outside of these times. The questions cover a range of areas from clinical and mental health to social wellbeing and health promotion.
• Once the patient fills in the questions on their device, this is automatically submitted to the digital health team / virtual care hub – a nurse-led clinical team – and triggers a RAG-rated response.
• Based on an agreed standard operating procedure, the team can escalate to an appropriate service such as a duty doctor, urgent treatment centre or emergency services.
• The patients’ data could be monitored for a minimum of two weeks – and up to six months.

Exceptional patient feedback from the project

Anna continues: ‘Patients have offered thanks for the ongoing care and advice and checking in on their welfare. By offering the patient simple advice – such as closing your mouth when taking your temperature, warming hands before SpO2, increasing fluid intake during day or reducing salt and cholesterol-high foods, patients are gaining more knowledge on their health. One patient was put on daily monitoring by the nurses on the remote monitoring team, due to anomalies, the patient was then escalated and received a diagnosis which could have been life threatening if not picked up and treated. A gentleman, who, to begin with was not very keen on being part of the remote monitoring service, however as the weeks are passing, the patient is now very glad to be part of the service, he has more insight into his health and becoming more aware of his ongoing conditions.’

‘As duty GP we received a call from the monitoring team which allowed us to get the right support to the patient before they went into crisis and keep the patient at home.’ – Local GP