All three projects are collaborative efforts between AHSN, Integrated Care Boards (ICBs), Public Health teams and Voluntary, Community and Social Enterprise (VCSE) organisations aimed at improving access to innovations for deprived and marginalised communities in the clinical area of cardiovascular diseases (CVD). 

In Somerset, we are addressing the unmet needs of CVD prevention and treatment in deprived areas as defined by the Index of Multiple Deprivation and in the local homeless and rough sleeper populations in Somerset. Working alongside the Somerset Homeless and Rough Sleeper Network and its users, the project will co-design an approach to reach and engage this underserved population and offer them improved and personalised interventions.    

The project in North Devon aims to target inequality by optimising treatment of heart failure. The approach will include a remote monitoring (digital) service for heart failure patients to support optimisation and access to NICE-approved innovations, particularly for those in more rural and deprived areas, and patients who experience mental illness, learning disability and/or neurodiversity.  

The CIOS ICB project aims to use a novel preventative approach to tackle cardiovascular disease by proactively finding and engaging those that live in deprived areas as defined by the IMD and who are at high risk of disease.  Patients will have access to a suite of lifestyle advice and innovative NICE recommended medications to help improve their condition and improve health outcomes.   

• Potential clinical impact: reductions in CVD-related deaths, reduction in the prevalence of CVD, reduction in health inequalities  

• Economic impact will be realised in the long-term by preventing interventions to treat diseases, by preventing unnecessary admissions into secondary care, and through cost-effective ways to monitor disease. 

To develop a robust approach to evaluating InHIP and capturing learning from the work, the South West AHSN was asked by the AHSN Network and AAC to support fellow AHSNs in developing and embedding logic models, evaluation frameworks and learning approaches.