Although it is only 18 months since the launch of the Health Data Research Hubs, with over 300 contracts across academia, industry and the NHS, it is clear their services are valuable and attractive to the health ecosystem. Their industry partnerships are having a significant impact, particularly in regard to COVID-19, with the development of new tools, AI-powered risk models, and evidence to inform new treatments. Developing strong partnerships with industry helps the Hubs, and in turn the UK, to remain at the forefront of cutting-edge discoveries and innovation, for the benefit of patients and the public.
From pharmaceutical companies to digital health SMEs and software providers, industry endeavour to find solutions to complex health challenges and require access to the knowledge, expertise and tools to do so. In parallel, the Hubs are centres of excellence, which contain the knowledge, tools, expertise, and access to rich datasets, but are only as useful as the questions being asked of it.
As the Hub data improves and is utilised to address a variety of research questions, such as disease detection, outcomes, treatment burden, treatment response, and modelling, industry interest has started to emerge. By working in partnership, industry gains expertise, knowledge and talent. For the Hubs, benefits of partnerships include opportunities to work relevant innovations to address challenging problems, as well as enabling the sustainability of the Hubs.
Impacts and Outcomes
Joining up with commercial partners has had a significant impact, particularly around COVID-19, including the development of diagnostic tools, using AI to predict patients’ risk of deterioration, and gaining understanding of the impact of the pandemic on other disease areas.
The Hubs have been working on Artificial Intelligence (AI) projects including PIONEER’s work with Microsoft as part of its Project InnerEye, using machine learning technology to build tools for the automatic, quantitative analysis of 3D medical images. This helped to make COVID-19 related medical images unidentifiable and clinical data to be analysed using AI techniques to form a rapid diagnostic and prognostic tool. BREATHE has partnered with Savana on the BigCOVIData study, using data captured from hospital electronic health records (EHRs) to develop a model that predicts risk of deterioration and COVID-19 severity using AI. This unique approach uses Natural Language Processing (NLP) technology to incorporate all EHR data, including previously inaccessible free text information, to provide a much richer picture of an individual’s care and outcomes than was previously possible.
The pandemic placed a huge pressure on hospital capacity resulting in the rapid uptake of remote monitoring solutions to help keep patients safe at home. This saw Discover-NOW repurpose established work with Hub partner, AstraZeneca, on integrating innovative remote monitoring and near-patient testing into existing pathways for patients with Type 2 Diabetes, to be used to support North West London’s COVID-19 ‘Hot Hubs’. AstraZeneca, through working with NHSX and SME Huma, enabled oxygen saturation and breathlessness scores of patients with mild to moderate COVID-19 to be quickly and efficiently remotely monitored by GPs in the ‘Hot Hubs’. The NHS’s digital transformation arm, NHSX, reached out to Discover-NOW for support with the national response for COVID-19 remote monitoring, as a direct result of a collaboration with AstraZeneca in building digital remote monitoring solutions for patients with Type 2 Diabetes. Over four months of implementation (April-July 2020) 100% of patients using the HUMA app in primary care were able to recover across the pilot sites, with an average 3 minutes saved per Hot-Hub patient per day.
A bespoke dataset generated through INSIGHT supported the analysis of the impact of COVID-19 on patients with age-related macular degeneration (AMD), one of the leading causes of blindness. The project – initiated by Moorfields Eye Hospital and University Hospitals Birmingham with data science and analytical expertise from Roche-Genentech – provided the first reliable estimates of the scale and severity of the vision loss arising from delays in treatment for newly diagnosed ‘wet AMD’ during the COVID-19 period, informing NHS providers on strategies to optimise care of patients.
Projects unrelated to COVID-19 have also been established, such as DATA-CAN’s collaboration with Roche Products Ltd. Their dataset on early triple-negative breast cancer (eTNBC) – from cancer centres at Leeds Teaching Hospitals NHS Trust and NHS Lothian – have been deployed to understand the feasibility of delivering a real-world data study on eTNBC, with outputs potentially being used to support drug development plans and patient access to medicines. Metadata about the combined dataset and details of the common data model will be published via the Gateway, ensuring that members of the wider research community can benefit from this work. The improved evidence can inform the adoption of new drugs by the NHS, as well as the understanding of the treatment of eTNBC in two major cancer centres, benefiting both patients and the NHS.
The Hubs continue to generate interest from industry, due to the continued development of their services, their rich datasets, and proven successes across different sectors and disease areas.
Our Open Access Publication of the Month – November 2021
8 November 2021
Investigating severe COVID-19 outcomes after vaccination and tracking development assistance for health and for COVID-19.
PIONEER’s public conscience – reflections on the first year of the Data Trust Committee
29 October 2021
PIONEER, the Health Data Research Hub for Acute Care, reflects on the impact that their Data Trust Committee has had on access to health data for research.
Redefining β-blocker response in heart failure patients with sinus rhythm and atrial fibrillation: a machine learning cluster analysis
22 October 2021
Overview Researchers have used new artificial intelligence (AI) techniques to identify which patients with heart failure do, or do not, benefit from beta blockers. Their approach interrogates data...