Diabetes MellitusDePICtionNCT06711718
Diabetes in Primary Care - Improving Classification
An observational study of Diabetes Mellitus, run by University of Exeter at 9 sites in United Kingdom.
Trial summary
This study aims to evaluate the clinical utility and acceptability to patients and practitioners of running diabetes classification algorithms on primary care data to help improve diagnosis of diabetes subtypes in adults diagnosed with diabetes under the age of 50. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Diabetes Mellitus
- What is being tested?
- Qualitative interview (patients) and Qualitative interview (staff)
- How many people
- 21 participants
- Where
- 9 sitesUnited Kingdom
- Study dates
- 25 Jun 2024to 31 Mar 2026
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Patients who have had a review of their diabetes diagnosis as a result of the running of the tool will be invited to interview. Clinical practice staff (GP and/or nurse) who have been involved in reviewing patients flagged following running of the tool will be invited to interview. Practice Manager or administrator who has run the searches and tool will be invited to interview.
Who may be able to join
- Patients
- Able to give written informed consent
- 18 years of age or over at the time of study participation
- Diabetes diagnosed at or under the age of 50
- Registered with a participating GP practice
- Sufficient understanding of the English Language to enable completion of the interview
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- Staff
- Able to give written informed consent
- 18 years of age or over
- Working at a participating General Practice and directly involved with the study procedures (eg running the decision support tool, responsibility for clinical care of diabetes patients)
Who cannot join
- Patients
- Unable to give written informed consent
- Under 18 years of age
- No diabetes or diabetes diagnosed over the age of 50.
- Not registered with a participating GP practice
- Insufficient understanding of the English Language to enable interview completion
Show all 12Show fewer
- Have an opt-out code where patient has declined electronic medical records examined
- Considered by their General Practitioner(s) to be inappropriate to recruit due to psycho-social reasons, participating in another related clinical trial or significant health reasons, e.g. terminal illness/diagnosis.
- Staff
- Unable to give written informed consent
- Under 18 years of age
- General Practice staff not involved with the study procedures.
Trial locations and contacts
9 sites in 1 country.
9 sites in 1 country
United Kingdom9 sites
Ivybridge Medical Practice (Beacon Medical Group)
Ivybridge, Devon, PL21 0AJ
Hucknall Road Medical Centre
Nottingham, Nottinghamshire, NG5 1NA
Parkside Medical Practice
Nottingham, Nottinghamshire, NG6 8QJ
Chilwell Valley and Meadows Practice
Nottingham, Nottinghamshire, NG9 6DX
Tamar Valley Health
Plymouth, Cornwall, PL17 7AW
Roborough Surgery
Plymouth, Devon, PL6 6PH
Pathfields Medical Group
Plymouth, Devon, PL7 1AD
Plympton Health Centre (Beacon Medical Group)
Plymouth, Devon, PL7 1AD
Chaddlewood Surgery (Beacon Medical Group)
Plymouth, Devon, PL7 2QP
About this study
Official title: Diabetes in Primary Care - Improving Classification (DePICtion)
This study aims to evaluate the clinical utility and acceptability to patients and practitioners of running diabetes classification algorithms on primary care data to help improve diagnosis of diabetes subtypes in adults diagnosed with diabetes under the age of 50. The outputs from this research will help provide initial data on how best to use these algorithms in primary care and the optimal design of a decision support tool that could be taken forward to a full trial.
Read the detailed description
Part 1:
Using a successful approach from previous research, and experience from existing online diabetes classification calculators, we will test the feasibility of developing a decision support tool that would run the algorithms in these calculators on electronic healthcare record data at participating GP sites. We will work with a company that will develop a decision support tool that will search and extract relevant healthcare data in GP systems, run our algorithms on these data, and produce a display, highlighting patient records where there is a potential misclassification of diabetes and/or records where there are potential data quality issues (e.g. mis-coding or missing information). The decision support tool will only run on extracted data (rather than being embedded in the GP system).
Participating GP sites will be offered an introductory education session on classification of diabetes subtypes and identification of MODY (Maturity Onset Diabetes of the Young) and training on running and interpreting the decision tool.
On receipt of the outputs from the decision support tool, practice staff will be advised to review the records of potentially misclassified patients to explore any mis-codings and to consider further testing/referrals as relevant and in line with the standard clinical care pathway for diabetes.
At the end of the study, the data extraction/decision support tool may be re-run to determine whether there have been changes and whether additional testing (eg C-peptide or islet autoantibody) or referral to a diabetes specialist team has been carried out.
Part 2:
To assess the acceptability of the diabetes classification tools to potential users, and to consider how best to implement them in clinical practice long term for maximum benefit, we will explore the views and experiences of general practice teams and people with diabetes on the use of the diabetes classification tools.
A sample of clinical and admin staff at participating GP sites, and diabetes patients flagged by the tool as misclassified, will be invited to take part in a semi-structured interview about their views \& experience.
- Conditions
- Diabetes Mellitus
- Being tested
- Qualitative interview (patients), Qualitative interview (staff)
- Medical subject headings
- Diabetes Mellitus
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Qualitative interview (patients)Other
Qualitative interviews to be carried out by an experienced researcher with patients who have had their diabetes diagnosis reviewed as a result of the running of the tool.
Qualitative interview (staff)Other
Qualitative interviews to be carried out by an experienced researcher with practice staff who have run the tool and reviewed patients flagged by the tool.
| Study group | Role | What they receive |
|---|---|---|
| Patients qualitative interviews | 1. Patients reviewed by their GP as a result of Stage 1 (running of tool) are invited to a qualitative interview.
2. Consenting participants interviewed by the research team.
3. Information used to assess the impact and potential benefit of using the diabetes classification tool in general practice. Receives: Other: Qualitative interview (patients) | |
| Practice staff qualitative interviews | 1. Practice staff (clinical and administrative) who have been involved in Stage 1 (running of tool) are invited to a qualitative interview.
2. Consenting participants interviewed by the research team.
3. Information used to assess the impact and potential benefit of using the diabetes classification tool in general practice. Receives: Other: Qualitative interview (staff) |
What is being measured
The primary outcome is the main question the study is designed to answer.
Number and Proportion of patients flagged by the tool
Number and Proportion of patients flagged by the tool at each practice. Mean number of patients flagged by the tool across the practices.
Measured: Months 12-18.
Secondary outcomes (1)
Assessment of acceptability of the DePICtion Tool
Semi-structured, one-to-one interviews with staff and patients to evaluate (A) experiences of implementing the tool in this study and (B) views regarding the use of a diabetes classification tool in primary care in the future, including the impact and potential benefits.
Measured: Interviews to be conducted from 2 weeks to 6 months after implementing the tool in practice.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted2 Dec 2024
- Study start25 Jun 2024
- Primary completion5 Mar 2026
- Study completion31 Mar 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Diabetes MellitusStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Other
- Enrolment
- 21 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Exeter
- Sponsor type
- University, hospital or other
- Collaborators
- University of Bristol, University of Nottingham, National Institute for Health Research, United Kingdom
- Responsible party
- Sponsor
- Investigators
- Beverley Shields, Professor, Principal investigator, University of Exeter
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06711718
- Sponsor's protocol ID
- 2022-23-18
- Acronym
- DePICtion
- Status last verified
- Apr 2026
- First submitted
- 4 Jul 2024
- Last updated
- 30 Apr 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 30 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Diabetes in Primary Care - Improving Classification (DePICtion)
- ClinicalTrials.gov ID
- NCT06711718
- Acronym / sponsor ID
- DePICtion / 2022-23-18
- Conditions
- Diabetes Mellitus
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 21 participants (actual)
- Lead sponsor
- University of ExeterUniversity, hospital or other
- Collaborators
- University of Bristol, University of Nottingham, National Institute for Health Research, United Kingdom
- Study start
- 25 Jun 2024 (actual)
- Primary completion
- 5 Mar 2026 (actual)
- Study completion
- 31 Mar 2026 (actual)
- First posted
- 2 Dec 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study aims to evaluate the clinical utility and acceptability to patients and practitioners of running diabetes classification algorithms on primary care data to help improve diagnosis of diabetes subtypes in adults diagnosed with diabetes under the age of 50. The outputs from this research will help provide initial data on how best to use these algorithms in primary care and the optimal design of a decision support tool that could be taken forward to a full trial.
Detailed description
Part 1:
Using a successful approach from previous research, and experience from existing online diabetes classification calculators, we will test the feasibility of developing a decision support tool that would run the algorithms in these calculators on electronic healthcare record data at participating GP sites. We will work with a company that will develop a decision support tool that will search and extract relevant healthcare data in GP systems, run our algorithms on these data, and produce a display, highlighting patient records where there is a potential misclassification of diabetes and/or records where there are potential data quality issues (e.g. mis-coding or missing information). The decision support tool will only run on extracted data (rather than being embedded in the GP system).
Participating GP sites will be offered an introductory education session on classification of diabetes subtypes and identification of MODY (Maturity Onset Diabetes of the Young) and training on running and interpreting the decision tool.
On receipt of the outputs from the decision support tool, practice staff will be advised to review the records of potentially misclassified patients to explore any mis-codings and to consider further testing/referrals as relevant and in line with the standard clinical care pathway for diabetes.
At the end of the study, the data extraction/decision support tool may be re-run to determine whether there have been changes and whether additional testing (eg C-peptide or islet autoantibody) or referral to a diabetes specialist team has been carried out.
Part 2:
To assess the acceptability of the diabetes classification tools to potential users, and to consider how best to implement them in clinical practice long term for maximum benefit, we will explore the views and experiences of general practice teams and people with diabetes on the use of the diabetes classification tools.
A sample of clinical and admin staff at participating GP sites, and diabetes patients flagged by the tool as misclassified, will be invited to take part in a semi-structured interview about their views \& experience.
Study design
- Observational model
- Other
- Time perspective
- Other
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Patients qualitative interviews | – | Other: Qualitative interview (patients)1. Patients reviewed by their GP as a result of Stage 1 (running of tool) are invited to a qualitative interview. 2. Consenting participants interviewed by the research team. 3. Information used to assess the impact and potential benefit of using the diabetes classification tool in general practice. |
| Practice staff qualitative interviews | – | Other: Qualitative interview (staff)1. Practice staff (clinical and administrative) who have been involved in Stage 1 (running of tool) are invited to a qualitative interview. 2. Consenting participants interviewed by the research team. 3. Information used to assess the impact and potential benefit of using the diabetes classification tool in general practice. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Patients who have had a review of their diabetes diagnosis as a result of the running of the tool will be invited to interview. Clinical practice staff (GP and/or nurse) who have been involved in reviewing patients flagged following running of the tool will be invited to interview. Practice Manager or administrator who has run the searches and tool will be invited to interview.
Key inclusion criteria (10 listed)
- Patients
- Able to give written informed consent
- 18 years of age or over at the time of study participation
- Diabetes diagnosed at or under the age of 50
- Registered with a participating GP practice
Key exclusion criteria (12 listed)
- Patients
- Unable to give written informed consent
- Under 18 years of age
- No diabetes or diabetes diagnosed over the age of 50.
- Not registered with a participating GP practice
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Qualitative interview (patients)Qualitative interviews to be carried out by an experienced researcher with patients who have had their diabetes diagnosis reviewed as a result of the running of the tool. | Other | Patients qualitative interviews |
| Qualitative interview (staff)Qualitative interviews to be carried out by an experienced researcher with practice staff who have run the tool and reviewed patients flagged by the tool. | Other | Practice staff qualitative interviews |
Primary outcome
Number and Proportion of patients flagged by the tool
Time frame: Months 12-18.
Number and Proportion of patients flagged by the tool at each practice. Mean number of patients flagged by the tool across the practices.
1 secondary outcome
Assessment of acceptability of the DePICtion Tool
Time frame: Interviews to be conducted from 2 weeks to 6 months after implementing the tool in practice.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 30 Apr 2026.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Beverley Shields, Professor principal investigator
University of Exeter
9 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Diabetes Mellitus, run by University of Exeter at 9 sites in United Kingdom.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 10 inclusion and 12 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 30 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 9 sites in United Kingdom. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Number and Proportion of patients flagged by the tool (time frame: Months 12-18.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 30 Apr 2026.