Solutions

The Inverse Care Law describes the relationship between the need for health care and how it is used, acknowledging that often, people who are in most need of health care are the least likely to receive it. Throughout the COVID-19 pandemic it was noted that those living in more disadvantaged areas had worse outcomes, once again shining the spotlight on inequalities. 

When there is acute demand (e.g. hospital waiting lists following the pandemic) it can be difficult to allocate spend to prevention, but this is the only way to reduce further acute demand at a later time point. Tools such as Return on Investment and Social Return on Investment can be helpful. 

When planning and delivering healthcare services, there are many tools and techniques that can be applied to reduce inequalities. These include the use of health impact assessment, health needs assessment, and economic assessments. 

Decisions on services are based on data: information from the people in need (e.g. health needs assessment and epidemiological data), where it is best to spend resources (e.g. NICE guidelines or return on investment studies) and data on reducing inequalities (e.g. health impact assessment or integrated impact assessment). Investment is often driven by need and data but this is not always the case.  

Multi-criteria Decision Analysis and Programme Budgeting and Marginal Analysis

As a tax-funded system, the NHS is under constant strain as the demand for healthcare is close to infinite, whilst healthcare resources are finite. To create a balance between finite resources and infinite wants and needs, choices are necessary and consequently costs and benefits must be compared. Prioritisation is also required to assist this decision-making so resources are used in a way that maximises their benefit. 

Multi-criteria Decision Analysis (MCDA) and Programme Budgeting and Marginal Analysis (PBMA) are tools that aid decision-making and resource allocation so that benefits are maximised. They offer a framework to identify interventions that are cost-effective and address socio-economic equity, that improve productivity and keep people in work in Wales (e.g. addressing musculoskeletal issues and mental health). These frameworks require information on quantifiable indicators for interventions, for example how many people access services; what services cost; their reach; whether they are evidence-based and cost-effective; their benefits (e.g. how many people quit smoking as a result of the intervention). These frameworks can also assist in the development of key performance indicators prior to undertaking an evaluation.

Useful Resources