Clinical decision support app for dementia
Research type
Research Study
Full title
Development of a hybrid computational model based app to standardise and improve the quality of dementia assessment data used to support clinical decision-making
IRAS ID
230077
Contact name
Kongfatt Wong-Lin
Contact email
Sponsor organisation
Ulster University
Duration of Study in the UK
0 years, 8 months, 29 days
Research summary
More timely and accurate diagnosis of dementia can lead to better and earlier interventions, which promote independence. Additionally, improved diagnosis permits planning for end-of-life care and reduces institutionalisation, thereby reducing direct and indirect health and social care costs burdens. It has been estimated that identification of risks and early diagnosis, which lead to the proper treatments or interventions, can delay the onset of dementia by 2-5 years and reduce the prevalence by 20-50%. The aim of this project is to make use of clinical data from N. Ireland to refine our hybrid computational approach to standardising and improving the quality of dementia assessment data, and thus to develop an app to support clinical decision-making. To address this aim a databank will be created of key clinical data linked with the assessment and diagnosis of dementia from patients currently living with diagnosed dementia (mild cognitive impairment, Alzheimer’s dementia, and non-Alzheimer’s dementia) and attending the N. Ireland Memory Assessment Service (WHSCT). Data mining methods will be employed to identify the strengths of the assessment tools used in predicating the dementia diagnosis. The information will be incorporated into an app for use by patients within the clinical setting, providing clinical decision-makers with standardised, high-quality and prompt dementia assessment information.
REC name
HSC REC B
REC reference
17/NI/0142
Date of REC Opinion
16 Aug 2017
REC opinion
Favourable Opinion