The NHS Digital Weight Management Programme is an NHS England initiative. As part of this public health pilot programme University Hospitals of North Midlands NHS Trust (UHNM)  implemented a fully automated, data driven patient referrals process, incorporating Patients Know Best for the Patient Portal element.  The process identifies patients from the Trust’s waiting lists who meet the programme eligibility criteria and asks for referral consent through the use of numerous, existing IT technologies that can easily lend themselves to be adapted and flexed for use in other patient centric activities. 

This end-to-end automatic referrals process requires minimal administrative overhead and brings enormous clinical benefit for the patient while minimising obesity related procedure cancellations for the hospital.

The University Hospital of North Midland is piloting a national programme to refer patients living with obesity and on waiting lists to the NHS Digital Weight Management Programme. The aim is to support patients with a BMI exceeding thirty, and whose procedures are not planned in the next 18 weeks, to help manage their health whilst they wait.

At the start of the pilot, the Trust had 2,226 eligible patients on waiting lists for identified procedures who needed to be verified prior to referral. Patient BMIs were not readily available for reporting. Information was recorded via numerous systems as a height and weight. The process involved collecting and collating the latest height and weight data from multiple systems and when not available, required additional staff time to ask patients directly. Additional patients were also being added daily so processes needed on-going resources.

Typically administrative time to manage this process involves phone calls explaining the initiative and collecting patient  information to determine appropriateness for referral.  This averages about a 20 minute phone call and up to 75 minutes per referral overall.  Based on UHNM’s initial waiting list of 2,226 patients this equated to 742 hours or 99 days of phone calls alone. 

UHNM wanted to establish  an automated digital solution to assess current and future patients for referral.  The aim was to use IT systems and technologies already available within the Trust. With this reasoning, with minimal expenditure, it could minimise overhead on existing staff and negate the need for recruitment to manage the project.

UHNM had recently implemented Patients Know Best (PKB).  The Trust now had an opportunity to use PKB for electronic patient contacts.  “Consent” and “height and weight” questionnaires were developed to directly contact patients through the PKB portal.  

UHNM used PKB’s functionality to send notifications to their patients to make them aware of potential referral. By completing a short questionnaire, patients were able to give their consent, and be asked for height and weight measurements when needed.  With due diligence and Information Governance associated, the tools were there for a timely and workable solution.  Data captured from the patient through PKB was pulled back into UHNM through the various FHIR and HL7 API calls.

Now with the patient consent and a reliable BMI reading available, the Trust needed a method to refer the patient to the service through the NHSE website.  Daily automation of CSV file extracts for upload to this web based referral portal was set-up through a RPA (BluePrism) digital worker.  Lastly a PowerBi dashboard provided oversight of the whole process.

*Information on the NHS Digital Weight Management Programme can be found through this url

Whereas other hospitals involved in the programme had to use administrative or clinical teams to contact patients, UHNM made smart use of their existing technology with no additional investment.

The system went live in June 2023. In the first week of operation the Trust saw:

• 1447 Patients sent questionnaires (64 days saved)
• 76 patients were referred to the weight management service
• 142 patients provided height and weight information
• Only 8 patients with a high BMI declined referral
• 732 patients were excluded as their BMI was low
• 216 patients were excluded as their TCI (To Come In) date was too soon to allow full participation in the weight loss programme

Focussing on 1,447 sent questionnaires. These equated to 64 days of essential phone calls being negated and an almost immediate referral for all Trust patients waiting for included surgery.

As expected there were and still are some dropouts if patients do not register with PKB or decline to respond.  Data is collected for dropouts allowing the Trust  to send follow-up campaigns to encourage patients to opt-in to the Portal or send a subsequent invite via semi-automated mail.

UHNM’s approach is entirely digitally data driven which results in virtually no human interaction and no additional demands for staffing. Clinical teams have been asked to promote the NHSE Weight Management service and in so doing they are encouraging patients to register themselves onto the Trust’s PKB Patient Portal.  Posters and communications have been sent widely within the hospitals promoting this.  This automated referral process has wide support and communications surrounding it are helping to boost registrations into PKB and therefore improve the future use of our patient portal for similar future patient contacts.

Being a very different and digital approach, the Trust has presented its methodology to NHS England and other hospitals.  This process is very new but UHNM is  supportive in sharing learnings and assisting other Trusts with this or similar automation approaches.  Locally, within UHNM, the Trust  has now established a process that works and a process that has potential to be adapted for numerous other uses too.

As a result of these outcomes and benefits the trust is now looking to expand and enhance the automation of questionnaires. For the BMI weight management questionnaire it is envisaged the trust will upgrade to PKB’s new advanced questionnaires which will improve the functionality and data quality of the questionnaires.