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Improving health outcomes using our population health management tool

Improving health outcomes using our population health management tool

Home » Case studies » Improving health outcomes using our population health management tool

Using our population health management tool, we have helped identify people with clinical and social issues across Lancashire and South Cumbria, enabling early interventions to improve health outcomes.

Background
Population Health Management (PHM) is an approach that aims to improve physical and mental health outcomes, promote wellbeing and reduce health inequalities across an entire population, with the impact of Covid-19 further highlighting the impact of deprivation on health and wellbeing outcomes.

Our business intelligence specialists developed the PHM Segmentation Tool to enable a place-based approach to segmenting the population based on a number of similar health and wellbeing characteristics and needs, including wider determinants such as ethnicity, digital exclusion, housing quality and social isolation. This means they can target interventions more effectively and focus on prevention.

Action
The tool has been built and enhanced through partnership working with clinicians and strategic PHM leads across our client geographies, as well as multi-disciplinary expertise to support a blended offer to PHM segmentation. To respond to the Covid-19 support requirements, the tool was rapidly enhanced to incorporate Covid-19 risk factors as another way of segmenting cohorts of the population effectively.

Analytical expertise has also been provided to support Integrated Care Systems (ICSs), Place-Based Partnerships and Primary Care Networks (PCNs) with actionable insights of their population, as well as sharing best practice and relevant interventions from across our client geographies.

Impact
To date, we have helped identify and reach approximately 5,500 people with clinical and social issues, enabling the system to improve health outcomes at an early stage, avoiding patients becoming unwell, reducing hospital admissions and future healthcare costs. Our insight has helped decide where best to allocate funding to address needs and health inequalities, for example:

  • identifying the best location for a new community frailty service providing convenience to those most in need
  • reducing violence by placing additional community support at the electoral wards with highest levels of vandalism and crime
  • improving young people’s mental health by placing additional support at a list of schools with the most pupils at risk of having mental health issues
  • contacting 460 individuals with previously unknown issues to ensure they had access to the services and referrals they need given their personal and clinical circumstances
  • providing a list of patients with respiratory conditions who are likely to live in houses with a lack of adequate heating, which could exacerbate their condition.

“The tool enables me to identify clinical areas where the inequalities are widest across the area and also the wards that are outliers compared to their peers. This can help target interventions. This data can also be used strategically to target resources, although we are yet to test the success of that. The tool works well with the other PHM and PCN dashboards to provide a holistic picture of local health outcomes.”
Vicky Hepworth-Putt, Acting Consultant in Public Health, Cumbria County Council

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