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Diabetes in Primary Care - Improving Classification
Sponsor: University of Exeter
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. 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.
Official title: Diabetes in Primary Care - Improving Classification (DePICtion)
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
45
Start Date
2024-06-25
Completion Date
2026-03-31
Last Updated
2025-09-23
Healthy Volunteers
Yes
Conditions
Interventions
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.
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.
Locations (9)
Tamar Valley Health
Plymouth, Cornwall, United Kingdom
Ivybridge Medical Practice (Beacon Medical Group)
Ivybridge, Devon, United Kingdom
Roborough Surgery
Plymouth, Devon, United Kingdom
Pathfields Medical Group
Plymouth, Devon, United Kingdom
Plympton Health Centre (Beacon Medical Group)
Plymouth, Devon, United Kingdom
Chaddlewood Surgery (Beacon Medical Group)
Plymouth, Devon, United Kingdom
Hucknall Road Medical Centre
Nottingham, Nottinghamshire, United Kingdom
Parkside Medical Practice
Nottingham, Nottinghamshire, United Kingdom
Chilwell Valley and Meadows Practice
Nottingham, Nottinghamshire, United Kingdom