Enhancing the diagnostic pathway for dementia using DECODE
Research type
Research Study
Full title
Enhancing the diagnostic pathway for dementia using DECODE
IRAS ID
251351
Contact name
David Llewellyn
Contact email
Sponsor organisation
University of Exeter Medical School
Clinicaltrials.gov Identifier
EP/N510129/1, EPSRC - The Alan Turing Institute ; 877812, The Halpin Trust; EP/N014391/1, EPSRC Centre for Predictive Modelling in Healthcare
Duration of Study in the UK
1 years, 3 months, 28 days
Research summary
Many people with dementia are never diagnosed, or are diagnosed during the later stages of the condition, when a diagnosis may be less helpful. A substantial investment was therefore made to set up a network of specialist Memory Clinics across the UK, so that patients could be referred directly by their general practitioner (GP). However GPs are still under considerable pressure, and only have a few minutes to make sense of patients complex signs and symptoms, which inevitably means mistakes are made. Currently around 50% of patients referred to Memory Clinics, do not have mild cognitive impairment, or dementia. This adds increased pressure to the waiting times for Memory Clinic assessments, as there is simply not enough capacity in the system to see everyone.
We developed the DEmentia identification COmputerized DEcision support system (DECODE) to help busy clinicians to make better informed decisions about the likelihood of dementia. DECODE can be used by GPs as part of routine consultations, or as a triage tool by Memory clinic staff, when patients are referred by the GP.We have secured funding to conduct a feasibility trial, in four GP practices across Devon, and the Devon Partnership Trust Memory Clinic. The trial will investigate whether DECODE can be successfully implemented in these setting, assessing its acceptability and usability.
If successful the feasibility trial will be a prelude to secure funding for a full evaluation of the software.
The trial will stand alongside existing clinical assessments and judgement. The trial will allow us to be able to work with clinicians and patients, in order to further refine the software and ensure that is adapted to fit with the needs of the service, clinicians and patients.
If feasible, we hope that the software will be adopted as a tool in clinical care.
REC name
London - Central Research Ethics Committee
REC reference
19/LO/0412
Date of REC Opinion
5 Apr 2019
REC opinion
Unfavourable Opinion