Patients with chronic conditions offered personalised care through population health management

Case study summary 

A group of patients at high risk of becoming unwell due to a chronic physical health problem and depression were identified using a population health management (PHM) approach in North and North East Cumbria.

PHM enables clinicians to identify and understand patients’ health problems through linked data sets, helping to predict future health and care needs, reduce health inequalities and make better use of resources.

As part of the national PHM Development programme, Valens Primary Care Network (PCN) identified a cohort of 34 people who were struggling with issues affecting their health such as finance, housing, mood and lifestyle.

A working group of health and care professionals including a public health consultant, GPs, a social prescribing link worker (SPLW) and the clinical commissioning group (CCG) medical director used data from SystmOne to find the group.

The patients, aged 35 to 55 with at least one chronic health condition and co-morbid depression, were proactively contacted by a social prescribing link worker to ask if there were any environmental factors preventing them from successfully managing their conditions.

Organisation            

Valens Primary Care Network, part of North East and North Cumbria Integrated Care System (NENC ICS).

The idea for the project was conceived by Judith Stonebridge, a public health consultant from Northumbria Healthcare Foundation Trust and Dr Robin Hudson, Northumberland CCG Medical Director. They engaged with Dr David Cummins (Valens PCN), a GP fellow in public health and Alex Hall (Lintonville Medical Group, Valens PCN), a social prescribing link worker. All stakeholders had a strong interest in reducing health inequalities.

What was the aim?

 This project aimed to identify and address the issues affecting the health and wellbeing of a cohort of young patients with both a chronic condition and co-morbid depression. Particular focus was placed on early mental health support, debt and benefits, social isolation, and cardiovascular health – including smoking cessation and access to physical activity and weight management services.

Dr David Cummins, a local GP and Clinical Lead for PHM at NHS Northumberland CCG said: “Two-thirds of UK adults over 65 are predicted to be living with multiple health conditions by 2035.

“Our aim was to identify those at highest risk of becoming the next generation of 65-year-olds with multiple problems and start proactive, personalised support to improve their health and wellbeing”.

 What was the solution

 Data came from the practice’s SystmOne database as this was all that was needed to identify the cohort.

The team searched the practice’s SystmOne records for patients (male and female) aged 35 to 55 with a coded diagnosis of depression (new, last 24 months, and ongoing).

They also required patients to have at least one of the Quality and outcome framework (QOF) chronic conditions: at risk of diabetes, T2DM (type 2 diabetes), cardiovascular disease (peripheral arterial/artery disease, stroke, coronary heart disease/ischaemic heart disease, aortic disease), hypertension, rheumatoid arthritis, or obesity.

From the searches they identified 34 patients who were then invited to participate in a semi-structured interview with the social prescribing link worker.

 They aimed to identify and address the issues affecting each individual’s physical and mental health and to make appropriate interventions to prevent them from becoming irreversible. To date, 13 telephone interviews have been conducted.

Phone interviews with patients focused on the wider determinants such as family and friends, lifestyle, work and volunteering, money and managing symptoms.

Social prescribers also used the Wellbeing Star as a tool to help understand personal health management. This information helped improve each patient’s physical and mental health by means of personalised, community-based interventions to prevent disease progression.

Particular focus was placed on early mental health support, debt and benefits, social isolation, and cardiovascular health – including smoking cessation and access to physical activity and weight management services.

Short, medium and long-term aims included: empowering patients to self-manage their conditions and understand the support available, long-term physical and mental health improvements, and improved Wellbeing Star outcomes.

What were the challenges

 The social prescribing link worker resource was limited, as this project was supplementary to their normal work activity. Obtaining informed consent to publish case studies has also proven difficult.

 What were the results

Evaluation has been limited so far but we have found it crucial in understanding patients’ views of the service and how it helped them improve their health and wellbeing. To achieve this we included a mix of open and closed questions as a means of gathering both qualitative and quantitative results. We also used the Wellbeing Star as a tool to compare feedback with the baseline score.

Alex Hall explained how they helped Paul.

Paul, 41, was unemployed, and his money worries were adding to his depression. He had little contact with family and friends and was being passed back and forth between mental health and counselling services.

Alex said: “I’ve been able to help with his applications for personal independence payment, a bus pass and a work capability questionnaire for Universal Credit.

“Paul now says he feels more confident in managing his mental health and says the programme has made a positive difference to his life”.

Read more about Paul’s story in our seven minute read case study on the PHM Academy (you will need to register for a FutureNHS account).

 What were the learning points?

 At the time, the team chose only to focus on Lintonville patients and only had S1 data at their disposal – this was all we needed to find the cohort. However, in hindsight, had we had access to local authority we would have been able to target our resources (social prescribing link worker time, etc) at those who were most in need.

With the linked data sets we would have been able to see who amongst the 34 patients in the cohort were struggling with rent arrears or debt, for example, so we would have contacted them first. It has illustrated to us the importance of data sharing agreements to allow more focused insight.