We use cookies.

To make your experience the best it can be, we use cookies and similar technologies on our site. We need your permission to allow these technologies, which will maximise browsing experience. For more information on how we use cookies and how to change your cookie settings, please see our cookies and privacy policy.



Please complete this short form to get in touch with a member of our team and we will get back to you as soon as we can.



Sign up to our newsletter by completing the form below.

Header image for the current page Using data to drive better diabetes care in Bedfordshire, Luton and Milton Keynes

Using data to drive better diabetes care in Bedfordshire, Luton and Milton Keynes

Share this page

By Prasanth Peddaayyavarla, Head of Data Science at NHS Arden & GEM, and Buz Dodd, Associate Director of Contracting and Business Intelligence at NHS Bedfordshire, Luton and Milton Keynes ICB

Over 70,000 people in Bedfordshire, Luton and Milton Keynes (BLMK) are living with diabetes. To help improve quality of life for patients and reduce adverse outcomes, clinicians needed a tool to help them improve care delivery and identify unmet need. BLMK Integrated Care Board (ICB) and NHS Arden & GEM’s Advanced Analytics Unit have co-developed a diabetes Early Warning System (EWS) which is enabling proactive, personalised interventions within primary and community care.

The challenge

Nearly 6.5% of the BLMK population has been diagnosed with diabetes, with a significant proportion from ethnic minority backgrounds and residing in high-deprivation areas. Studies show that proactive completion of eight care process checks including HbA1c blood tests, blood pressure and kidney function, reduces mortality, improves quality of life and reduces adverse outcomes. However, completion of these processes varied among practices and in 2022/23, only 57% of patients across BLMK had received all eight checks.

Existing sources of patient data (the National Diabetes Audit and clinical systems) provided limited functionality to support effective monitoring. In creating the diabetes EWS, BLMK ICB wanted to take a holistic approach, using population health management data to create a comprehensive system that would enable targeted interventions based on need, and provide benchmarking data to support commissioners. This meant bringing together multiple data sets that would support more efficient working for clinicians and better outcomes for patients.

A collaborative approach

In scoping the development of an EWS, the ICB outlined a number of aims which included:

From the outset, this was a collaborative project, with widespread engagement across primary and specialist care, to build ownership and investment in the project across the system. A dedicated project group met fortnightly and included participants from primary and specialist care, ICS partner organisations and the ICB.

Data-driven activity

The diabetes EWS brings together over 16 million records, spanning three years, covering events for BLMK diabetes patients from a range of sources. The EWS enables practices to proactively monitor care process completion and diagnostic data updates, correlating this with other elements such as prescribing and hospital attendance.

A case-finding tool helps clinicians easily identify and better understand who could benefit from immediate attention. Users can interrogate the data to produce a prioritised list of patients for proactive intervention based on bespoke parameters e.g. by age group. Individual patient records can be selected to view longitudinal clinical and event information, including risk scoring and historic admission information.

Role-based data access

To deliver the benefits intended for individual patients, clinical users with appropriate access can reidentify patients from aggregate data. Access to personal confidential data (PCD) has been authorised by individual GP practice Caldicott Guardians/IG leads for records of patients within a named practice. Additional approvals, including PCN Clinical Directors and ICB SIROs, are in place where staff, such as those working in the Bedfordshire Integrated Community Diabetes Service, need access to PCD across multiple practices.

Non-clinical stakeholders have access to aggregate benchmarking and summary views for the entire ICB. The summary view at a PCN and practice level shows prevalence levels and recent diagnosis figures. This insight supports referrals to structured education programmes as well as identifying gaps in care.  


The EWS is enabling clinicians to shift from reactive to proactive care, by making it easier to identify and prioritise patients requiring additional care, leading to earlier, more effective interventions and improved outcomes. The risk stratification tool is helping to identify patients at risk of hospitalisation, leading to targeted interventions which will in turn lead to a subsequent decrease in hospital admissions.

Clinicians are using the case finding feature to implement more timely and effective interventions including lifestyle programmes, pharmacological interventions or structured education, depending on individual needs.

“What we’re able to do with the diabetes EWS is truly proactive working. We can quickly and easily identify issues or opportunities, and then introduce proactive streams of work to improve adherence and overall care quality for patients. I am very excited about the potential of this tool.”

Julia Pledger, Consultant Diabetes Nurse, Integrated Community Diabetes Service for Bedfordshire

Access to timely, relevant, and well-presented information is also supporting staff to streamline processes and improve access which reduces the strain on an incredibly stretched workforce. Furthermore, the collaborative approach and input from multiple stakeholders has led to a more holistic approach to patient care.

We are now using the learning from this project to develop an EWS for COPD, with scoping underway for further projects to support other long term conditions.

The full blog was originally published by Healthcare Leader.

Picture of Prasanth Peddaayyavarla

Author: Prasanth Peddaayyavarla |

As Head of Data Science, Prasanth oversees the development of products that support improvement in healthcare using latest technologies and research. In his 15 years of experience at various NHS related organisations, he was responsible for the delivery of a range of analytical tools, statistical analysis and machine learning models. He is passionate about creating tools that empower decision makers in improving patients' healthcare and generate value to his organisation.