Jack Ettinger on PHM

17 January 2023

The role of health economics and a framework for resource allocation in PHM

The Health Economics Unit, in partnership with the Midlands Decision Support Network, have been working with the team at Nottingham and Nottinghamshire Integrated Care Board (ICB) on Population Health Management (PHM). Keen to share the core concepts and benefits of PHM more widely across different professions and providers, we designed a series of bespoke interactive workshops on the topic of PHM and partnership working. Health economist Jack Ettinger explains the theory and practice in using this methodology for improving your population’s health.

PHM is an intelligence-led technique for local health and care partnerships to design new models of proactive and joined-up care. The goal is to collaboratively deliver improvements to long-term health and wellbeing in the local population by making the best use of collective resources. It is often talked about in abstract terms, essentially leaving analysts to figure out for themselves how to implement it. Our activities with the ICB were designed to provide clear real-world examples of PHM analytics in practical terms, helping attendees understand more about the role of health economics and ‘value’ in PHM decision-making.

While the ICB has already effectively embedded PHM into many of its practices, attendance at these sessions was open to absolutely anyone within the system to try and increase awareness and understanding. Our first sessions focussed on introducing different ways to approach PHM, specifically looking at allocative efficiency.

Allocative vs technical Efficiency

Allocative efficiency means how to maximise the health gain for a population  from a given set of resources.

A system, pathway or process can be considered allocatively efficient when it is not possible to increase value by moving resources from one area to another. In other words it measures whether we are doing the right things. This is a key concept in healthcare and other public sector services. Where budgets are limited, we need to make sure we are spending our money and resources in ways that derive the most value.

This contrasts with technical efficiency, which looks at doing things right. Technical efficiency is about achieving the most output given a set of inputs. Policies centred around reducing the length of stay following an operation are looking to improve the technical efficiency of the surgical department. Fewer bed days per patient means you can do more operations.

However, striving for  technical efficiency in using a resource to deliver care can lead to an increase in consumption of that resource (referred to as Jevon’s paradox after the economist who first noticed this phenomenon). Fewer bed stays may mean more operations. This may be all well and good, but it may be that doing more operations might not be the best option. Spending the money elsewhere, perhaps on preventing someone needing an operation in the first place, may be a better option.

How to put allocative efficiency into practice

PHM encourages us to look at modifiable risk factors, or wider determinants of health. These are generally considered to be health behaviours, social and economic factors, physical environment and clinical care. This can help us see that if we focus all our efforts on improving one element, access to clinical care for example, then we can only ever make around a 20% impact on overall population health and we miss out on 80% where we can have an impact. (Hood et al., 2016)

However, while we have good access to information on costs, we know relatively little about the benefits to patients of different interventions, meaning it can be challenging to make fully informed decisions about resource allocation.


A framework for resource allocation

There are different levels on which resource allocation decisions need to be made. At the national level the government looks at allocating resources between different sectors, such as health, justice, and transport. Within the health sector the National Institute of Health and Care Excellence (NICE), through health technology assessments. NICE uses cost-utility analysis to compare the costs and health gain (in terms of quality adjusted life years), to determine whether NHS will allocate funding and resources to certain treatments. ICBs and integrated care teams also need to be able to determine how they allocate resources across a pathway of care. However, the methods employed by NICE rely on evidence in the form of randomised controlled trials and budgets not available to local health planners.

The STAR (socio-technical allocation of resource) approach was developed by the London School of Economics and the Health Foundation. It is a simple and pragmatic way of evidencing allocative efficiency for a pathway, using data that is readily available to most health organisations.

There are two main parts to putting the STAR approach into practice. Firstly – the key is in the name – there is a socio element using ‘decision conferencing’, which is essentially bringing all the people involved in the pathway under discussion into a room together. This should include representatives from every area of the pathway including decision makers, clinicians, experts and patients. First the group discusses the key priorities for the different parts of the system and then estimate the health gain (through methods grounded in health economic principles) of each of the components of the current pathway.

The ‘value’ of the current care pathway is then visualised in an easy to interpret graph plotting population health benefit against cost using ‘cost-effectiveness triangles’.

In these triangles, an intervention with good value for money will have a triangle with a steep slope, to represent high value at low cost; and one with poor value for money will have a slope close to horizontal, to represent low value at a high cost.

Then stakeholders are invited to develop ways in which they can improve the allocative efficiency of the current care pathway. This information is then taken away and built into visual models which demonstrate the potential impact those interventions could have on the pathway.

This information can then be used to help inform the priorities for the system and develop recommendations for moving forward.

Further information

If you would like to find out more about how the Health Economics Unit can support you in applying the STAR approach, or in offering similar training for your teams, please just get in touch.

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