11 Aug 2020
Population health management is a proactive approach to managing the health and well-being of a given population. It involves stepping back and considering the needs of different groups of people and organising services around them. It is a move away from demand-led, reactive care provision to a more proactive, tailored, and holistic approach to care.
It involves segmenting the population into groups of people with similar characteristics and then using predictive analytics to understand how likely they are to develop more complex health needs. Some groups may need more intensive support, whereas care for others will focus on prevention. Services are designed around holistic needs and targeted to the relevant groups and the individuals within them.
By organising services around the different groups of people, population health management ensures people have access to the health and wellbeing services they need in the right place at the right time. This inevitably improves outcomes for these individuals as the care they receive is far more proactive and in line with their own preferences. Indeed, a big part of population health management is ensuring the patient has a voice in what good healthcare looks like to them, which is also important in designing services around the individual.
For population health management to work effectively, different parts of the system must work together seamlessly. This includes primary care, secondary care, mental health, community care and social care. Without integration, the different parts will still be competing against each other. This makes it difficult to achieve the triple aim of improving patient outcomes, improving patient experience and reducing per capita cost. One of the catalysts to greater integration is aligning incentives along the care pathway. In addition, it is impossible to provide holistic care to patients if different parts of the system are not working together in a multi-disciplinary way.
There are several challenges facing any healthcare system looking to improve outcomes and reduce costs through population health management. One of the most significant is poor data quality. With different providers across the system recording information, there are few national information standards that are common across primary care, community care and secondary care. Data sharing is also a challenge as the ability to pull data from different providers can sometimes be undermined by information governance. Finally, it is often the case that the skills and experience needed to make the most of population health analysis are lacking.
Primary care has a critical part to play as this is often the start of a care pathway for a patient. It is the first opportunity outside of public health for the NHS to implement services and interventions that prevent patients from developing more complex health needs and ending up in hospital. We are currently working with primary care clinicians in Lambeth to help them identify the high-risk patients in their priority cohorts and easily track which patients have not received interventions. This will help to improve their outcomes and decrease the use of healthcare resources.
Analytics is a vital component across all population health management. It helps us to segment the population using statistical techniques to identify the different at-risk groups of people. We can then use it to forecast the resources these groups will need going forward and then to predict how likely they are to develop more complex health needs. Finally, we can use analytics to design metrics to measure outcomes and evaluate how effective new services and interventions have been after a period of time.
A demand-led, reactive approach is still what many patients experience today. Here, patients are treated in different parts of the system in silos without care being integrated and they are not treated holistically and in a joined-up way. In a demand-led system, patients typically end up being pushed around the system with a worse experience and poorer outcomes. It is also resource inefficient as diagnostics and other tests are often repeated several times as data isn’t readily shared between organisations.
Population health management is considered effective because it avoids many of the challenges of a siloed healthcare system. Furthermore, it allows us to take a predictive and preventive care approach, which means finding people at risk of developing serious and complex conditions before they happen.
Linking data from all the different parts of the system is useful because it gives us a full picture of the needs and characteristics of different groups of people. As a minimum, when we carry out population segmentation analysis, we link primary and secondary care data. This gives us enough information about clinical conditions and comorbidities. Combined with the important wider determinants of health we can then start to predict how many times a patient will end up in hospitals and at what cost.
For example, when we linked these datasets in Bradford, we were able to compare secondary care costs for patients with different numbers of long-term conditions, those living or not living in care homes and those who were housebound or not. We were also able to identify the groups of people where we could have the biggest impact on outcomes and reduction in cost.
The other benefit of linking primary and secondary care data is that we get a better understanding of care pathways starting in primary care. By linking the data, we can see what patients are experiencing compared to best practice and agreed pathways. This enables us to identify the variation, often referred to as gaps in care, and work with healthcare practitioners to close these gaps in care, again resulting in improved outcomes for patients.
Absolutely. By providing proactive and preventative care, we can improve the health and wellbeing of people and reduce the number of times they need healthcare interventions. There is a large opportunity in secondary care where costs are high, and often A&E attendances and emergency admissions can be avoided. For example, if primary care can help diabetics manage their condition better, adverse outcomes such as foot ulcers and amputations can be avoided leading to significantly lower costs, and of course much better outcomes for the patients.
Yes, this is a critical but often neglected part of population health management. When new services and interventions are implemented for groups of people, they should be evaluated for effectiveness. We help NHS organisations do this by measuring outcomes and cost before and after services and interventions have been implemented. This tells them whether they should continue with a particular intervention, or whether they should try something different or consider a service for redesign. It also helps to build a bank of evidence that is helpful to other organisations looking to implement the same of similar interventions.
The prerequisites for successful population health management are linked with system readiness, that means having good quality data that can be shared and having the skills and resources to analyse – find people at risk, determine the benefit of early interventions and then working out whether the intervention was a success.
Our analyst team can support your organisation to identify patients or patient groups for targeted care, prevention and gaps in care across the health and care system to improve patient outcomes and save costs. View information on our population health management service to find out more.