Evaluating Risk Prediction Tools for Complications in Type 2 Diabetes

Using the NWL Health Research Register to Recruit Patients

Using the NWL Health Research Register to Recruit Patients image
  • 10th September 2018

What is the title of the research/project?

RADAR (Risk Algorithms for Decision Support and Adverse Outcomes Reduction). This is an HDRUK, and Health Foundation funded project as part of the Better Care Programme.

This project used the NWL Health Research Register (NWL HRR) to recruit patients for its final phase, an evaluation of risk prediction tools developed as part of the project. The NWL HRR is a consent-to-contact research register for all adults in NWL. The Register has over 6,500 registrants to date, including over 500 people living with Type 2 Diabetes.

What is the background?

Diabetes is one of the greatest challenges currently facing the NHS. In NWL more than 150,000 people have been diagnosed with type 2 diabetes and a further 150,000 are at high risk of type 2 diabetes.  The annual cost of treating diabetes is over £600m and 40% of admissions to hospital are for people with diabetes.

Evidence demonstrates that through assessing the risk of complications and providing targeted and early interventions to those at highest risk can reduce mortality, complications, and hospital admissions (1). Data driven solutions may be able to deliver scalable low-cost management and/or self-management support to clinicians and patients to improve the outcomes, safety, and quality of life for patients and reducing the health care burden.

What was the aim of the research?

  1. To make the use of diabetes risk prediction models developed in Scotland by My Way Digital Health.  
  2. Apply these to the North West London (NWL) population, by revalidating in NWL’s longitudinally linked dataset, Discover. 
  3. To consider and develop prototypes for tools that will ultimately use risk prediction to drive clinician and patient behaviour change impacting on clinical decision making and patient self-management behaviour.
  4. Work with clinicians and people living with diabetes to understand their requirements.
  5. Test prototypes with clinicians and patients to gather their feedback on the usability and acceptability of these tools. 

Who did the research?

This project was led by the NWL Health and Care Partnership (NWL HCP), in collaboration with five project partners: The Institute of Global Health Innovation (IGHI), Imperial College London, Imperial College Healthcare Trust, Imperial College Health Care Partners (ICHP) Discover-NOW Hub, MyWay Digital Health (MWDH) and AstraZeneca (AZ).

How was the research carried out?

This project ran from May 2020 to May 2021. For more information on the wider project please see here.

The project evaluation of the prototype risk prediction tools was led by IGHI. This phase of the project took place in April 2021. This involved ‘Think aloud’ sessions in which patients and clinicians were asked to use the tools and feed back on their usability and acceptability.

Participants with Type 2 Diabetes were recruited using the NWL Health Research Register.  The NWL research register was used to invite people who had Type 2 Diabetes and who consented to take part in the research. 13 participants in target areas were identified by ICHP recruiters, of which 6 were eligible and consented by the IGHI research team. Participants were aged between 32 and 70 and represented a mix of ethnic backgrounds, with half of participants coming from Black, Asian, and Minority Ethnic (BAME) backgrounds. Figure 1. Shows the ethnicity breakdown of patients on the register when compared with the NWL population.

This study was approved by the Imperial College London Research Ethics Committee and the use of the NWL Health Research Register was subsequently approved by the NWL Data Access Committee.



Participants provided feedback on the usability and acceptability of the tools for risk prediction, this has been fed back to the MWDH development team for further improvements to be made to improve the tools which have the potential to reduce complications for patients with Type 2 Diabetes. Further work is planned to assess the impact of these tools on clinical outcomes.

The team plan to publish the results of this evaluation, and the overall project in a peer reviewed journal.

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