Discover-NOW has built a service offer which has been developed and refined in collaboration with our stakeholders across industry, large, SME, NHS and academia on what they aim to achieve with Real World Evidence and how the outcomes can support the health system. This insight alongside our Public, Patient, Involvement and Engagement is allowing us to continually improve the quality and agility of our approach.
This offer is spread across high demand research areas and is under-pinned through the implementation of a high-performance Trusted Research Environment (TRE).
A retrospective analysis of pathways, resource use and outcomes in Type 2 Diabetes (T2DM) is underway using the Discover data and in collaboration with Imperial College London and Imperial College Health Trust.
AstraZeneca partnered with Imperial College London and the NHS in NWL to improve T2DM care pathways and assess how new technologies could be used to improve care for high-risk patients. The Discover-NOW team have developed a new model of personalised, remote care allowed high risk patients to be identified and treated earlier.
Discover-NOW is also collaborating with ICHP to undertake an economic and outcomes evaluation of this new T2DM digitally enhanced pathway, this involves recruitment of patients from the NWL Health Research Register.
This example shows the unique digital and data innovation test bed service offer in development: from service baseline, to pathway redesign, pilot and evaluation.
This work has enabled research and evaluation into other diseases and treatments such as new HF digital interventions and pathways through collaborating with AstraZeneca, Imperial College London, Eko Duo, and the NHS.
The study aims to baseline treatment pathways and quantification of the care delivered for HF and compare to national predefined standards. The outcomes of this study will directly impact the NHS by identifying variation, good practice, and targeting opportunities to improve care.
Next, we are undertaking an economic analysis on a medical device product for HF patient pathway improvement, Eko Duo. Eko Duo should improve accuracy of HF diagnosis and improve pathway efficiency. Discover-NOW is working with the NHS to design and implement this tool and use the data generated to evaluate impact.
Discover-NOW can also help to train and test AI and machine learning algorithms.
The Bristol Myers Squibb-Pfizer Alliance has created an algorithm to predict who may be at risk of developing atrial fibrillation (AF) using CPRD, a national primary care data set.
Once an algorithm has been trained, it needs to be tested in a different environment to make sure it still works. Discover-NOW has provided this agile testing environment, applying the same AF algorithm to the Discover data. The Discover scale and breadth is unique, providing an ideal algorithm training and testing environment, this retrospective study has since been published in the European Journal of Preventative Cardiology (Sekelj, 2020).
The Alliance is now undertaking an economic evaluation of the algorithm as a further phase of the project with Discover-NOW.
Our approach has also enabled the creation of a High Impact Intervention Tool with Amgen.
Featured in The Guardian newspaper, our collaboration is creating a tool to quantify care gaps in terms of detection, treatment and management of patients with high cholesterol levels. The tool can be used to target high impact interventions such as lifestyle interventions and reviewing lipid levels. It will use predictive modelling using a leading enterprise AI technology embedded into the Discover data, DataRobot, to establish the impact of addressing these gaps on reduction of CVD events and costs.
The flexibility of our approach is such that cohorts can easily be defined and followed up, our service made even more powerful through Discover data Consent to Contact flags of the NWL Health Research Register (an investment by Discover-NOW).
A medical device start-up has used this service to recruit hypertensive patients for a clinical trial. An initial feasibility assessment was undertaken and Discover-NOW made it possible to recruit and follow-up patients for the trial.
Using the representative pre-consented population, the client has been able to quickly identity and on-board eligible patients, a target they struggled to reach prior to working with Discover-NOW.
A pharma company is using the Discover-NOW testbed service to create machine learning algorithms and build a robust evidence-base for change, specifically for cardiovascular disease and hypercholesterolaemia pathways.
By identifying patient cohorts most at risk and amenable to interventions, clinicians and commissioners will be able to better target resources to reduce cholesterol levels supporting NHS England Long Term Plan aims of saving lives by reducing heart attacks and strokes.