Population Health and Risk Stratification — Time to get Serious

In October this year NHS Clinical Commissioners published a document called Local Solutions to National Challenges. It is worth a read, not least because it re-states the raison d’être of Clinical Commissioning Groups (CCGs).

This is important because in the document there is an acceptance that the Five Year Forward View (5YFV) is a game changer and that transformation is not an option. Unsurprisingly the not so hidden sub-text is that Clinical Commissioning Groups are key agents of that change.

In fairness I suspect that the great majority of CCGs understood the need for change well in advance of the 5YFV landing on their desks. The need for service transformation has been a CCG mantra since their birth in 2012 and in the end analysis transformation is just another word for change.

So in support of the 5YFV, we have NHS Clinical Commissioners, on behalf of their members, re-stating their desire to invest in primary, mental health and community provision. In this the large acute hospital and traditional care models are firmly in their sights.

In noting that the aims and vision of CCGs are aligned with those of the 5YFV, the document asserts that “clinical commissioners have an unrivalled knowledge of the health needs of their populations.” CCGs it is claimed have “an understanding of their local populations second-to-none.”

These statements leapt out of the page at me because I take a view — controversially maybe — that more work may be required in terms of the creation of an evidence base to support a precise and nuanced understandings of the health needs of local populations.

Let us take risk stratification as a case in point. Whilst risk stratification is still relatively new to the NHS, most parts of the system now have access to, and experience of, some kind of risk stratification tool.

From the outset these tools focused on patient level risk stratification. In this context the principle application was for case finding purposes, the primary aim being to support direct patient care. Even more narrowly, recently activities have been centred on the identification of individuals most at risk of an emergency admission. For most GP practices at least activity here is being driven by the Avoiding Unplanned Admissions DES (Direct Enhanced Services) which was introduced in April 2014.

But it is analytics at a population level that offers the greatest opportunity for transformation and service re-design.

Setting aside the many other ways in which case finding can benefit individuals and groups, it is my experience at least that CCGs have spent less time on population level risk profiling, that is, the analysis of disease prevalence and morbidity distribution across populations. But it is analytics at a population level that offers the greatest opportunity for transformation and service re-design.

For CCGs to claim a full understanding of the needs of their local populations then they require an understanding of local patterns of morbidity and comorbidity which drive demand. Only when they adopt a case-mix approach to risk adjustment can they fully understand unexplained system variation.

Recent studies in the UK by Johns Hopkins, working with local health economies, demonstrate the importance to CCGs of understanding the need to manage multi-morbid populations. Population health analytics has shown that across a CCG multi-morbidity is the norm and that — for example — it is multi-morbidity rather than say age that is the key driver of risk and cost. Furthermore these studies show that rather than focus intervention efforts on patients with a single condition, the greatest rewards might be found targeting cohorts of patients that are multi-morbid.

With the right tools in the right hands, data can be used to highlight and quantify the degree of comorbidity and multi-morbidity that exists within a population. Furthermore case-mix adjustment across a population can help confirm and quantify variation between GP practices across a CCG. Case-mix adjustment enables a much fairer method of analysing variation and activity. Benchmarking — as a learning aide as opposed to a performance management tool (carrot not stick) — can often deliver insights of real value to change agents charged with the delivery of new care models.

This is not to devalue the importance of case finding. It is simply to say that when considering the real heavy lifting required to deliver service transformation, CCGs might want to look beyond the narrow confines of emergency admission avoidance.

In any case the jury is still out on the extent to which initiatives such as the unplanned admissions DES have acted as a genuine lever for change and to that end have truly helped transform services and create new care models. Read any discourse on population health management and the starting point is the identification of cohorts of individuals across the care continuum. In summary the need to define target populations and with it their health and social care needs.

It is only when CCGs and their service transformation partners fully embrace a population health management perspective that they will truly be able to claim a complete and nuanced understanding of the local populations that they exist to serve.

Are you looking to implement a population health management strategy?
Read our Five Steps to Population Health Management article.