Our health and care needs have changed dramatically since most modern healthcare systems were conceived. We now lead very different lifestyles, live considerably longer and increasingly with multiple long-term conditions such as diabetes, asthma, and dementia. At the same time, populations have soared and become much more diverse whilst health inequalities within them have widened.

All of this contributes to a huge increase in the volume and complexity of demand that our hospitals and other health and care providers are faced with. Factor in the impact of the Covid-19 pandemic and multiple global financial crises and we end with today’s situation where global health and care systems are at breaking point. The NHS is in complete crisis from ambulance response times to bed logjams to an exhausted, disaffected workforce and patient satisfaction at an all-time low.

Fundamentally, the way in which our health systems have been designed – to treat the patient once they become ill – is no longer fit for purpose.

We need to tackle the more complex challenge of how to prevent people from becoming ill in the first place? How do we identify individuals and groups at most risk of becoming ill, or most at risk of being unable or unlikely to access services? How do we design targeted interventions that proactively support people to manage their health and care in the community and therefore protect secondary care services for those that need them most?

What is population health management (PHM)?

Population health management is the process of understanding the circumstances and health needs across a defined local, regional or national population with the aim of developing tailored models of care and targeted interventions that improve physical and mental health outcomes, reduce health inequalities and make the best use of available resources.

Population health analytics produces the data-driven insights which inform PHM interventions. It involves the analysis of a range of social, economic, and environmental data known as wider determinants of health, in addition to health and demographic data, to create a holistic view of a population’s health and care needs.

PHM as a concept is well recognised, but its effective application has been stifled due to poor quality data, organisational siloes, challenges over data sharing and ethical concerns around connecting data sets. Advances in cloud and analytics, the advent of integrated care systems (ICSs) in England, and the urgency created by the COVID-19 pandemic are helping to overcome these barriers and as a result PHM is being applied with increasing scale and success.

Where can population health management be effective?

An area where PHM can deliver significant benefit is in the identification of groups within a population who are at high risk of developing a specific illness. Accurately identifying these individuals and providing them with treatment and protection is vital in protecting their health and the capacity of the wider healthcare system.

A prime example of this is BJSS’ work with NHS Digital, Oxford University and the Department of Health and Social Care in developing the COVID-19 Clinical Risk Assessment and Risk Stratification tools that identified an additional 1.7 million Clinically Extremely Vulnerable individuals to be added to the COVID-19 shielding list.

At the start of pandemic, it was not known who was most at risk, so the University of Oxford developed QCovid®, a revolutionary risk-prediction model capable of determining an individual’s risk of hospitalisation and death from Covid-19. NHS Digital and BJSS were then tasked with the application of this model across the adult population of England and with surfacing these results to clinicians. The combined team developed three distinct products to deliver this:

• An online Clinical Risk Assessment tool allowing healthcare professionals to search and understand a patient’s risk of dying from Covid-19
• A Risk Stratification tool to process England’s entire population through QCovid®
• An online Population Risk Assessment Viewer allowing GPs to view their patients’ QCovid® risk assessment outcomes securely.

The Clinical Risk Assessment tool was used thousands of times a day at the height of the pandemic and the Risk Stratification tool identified 1.7 million individuals to be added to the shielding list and later prioritised for vaccinations. These critical solutions were delivered within seven months, a vital  speed during a time of national crisis, and set a course for ongoing population health management tooling in the NHS, with the development of a new service to support this: Cohorting As A Service.

Read the full case study here.

What are the benefits of population health management?

• Low-Cost Intervention - intervening earlier in a patient’s journey prevents longer term costs. For example, identifying frail patients and installing protection is cheaper than them falling and needing hip surgery, physiotherapy and potentially costly assisted living. The earlier you can make these interventions the greater the savings you will ultimately provide, as well as impact to the individual.
• Efficiency - People identified through a data-driven approach via datasets collated from multiple sources (e.g., charities, priority services register, local authorities, GPs, Trusts and ICSs, etc.) can be provided with tailored and proactive care and advice which will lead to more efficient use of resources, both in the short and long term. This is essential in health care systems that are currently stretched to breaking point.
• Learning and improvements – Health and care organisations can better understand the impact, and measure the effects, of PHM interventions through the data that is collated and structured to enable them, allowing them to tweak and improve the approach as they go through continuous improvement. These learnings can be shared with other health bodies and applied at local, regional and national levels as appropriate.
• Reducing health inequalities - Organisations will be empowered to make informed decisions on the introduction of new interventions to the groups where the most difference can be made, delivering an equitable system where people get the care they need when they need it.

What are some of the challenges of population health management?

• Joining up data from disparate sources – To the surprise of many patients, data from primary care, secondary care, social services, and local authorities is not well connected, but the power it could yield if joined up would be enormous. An interesting practical example of this is identifying frailty through bin collection data - i.e., if somebody needs help with taking their bins out, it is likely that they are frail.
• It’s a different approach to healthcare - The challenge lies in helping citizens understand how interventions can improve their long-term health and wellbeing even if they aren’t unwell now. This is a departure from standard healthcare - of only treating those who are ill - and requires appropriate messaging and trust.
• Information governance – Rightly so, information governance is strict on the use of healthcare data even by public healthcare bodies. Getting access to the right data and ensuring it is used safely, ethically, and in a way that doesn’t degrade public trust will be essential to the longer-term success of PHM.
• Digital exclusion – A key aim of PHM is to reduce health inequalities and yet it could inadvertently exacerbate them, for example by missing people who don’t feature in certain data sets. It is essential that this non-digital population is not excluded from the benefits PHM brings.

Find out more about how we can help your healthcare organisation better visualise and action your data at bjss.com/health