Identifying undetected dementia in UK primary care patients: a retrospective case-control study comparing machine-learning and standard epidemiological approaches.

ABSTRACT:

Background

Identifying dementia early in time, using real world data, is a public health challenge. As only two-thirds of people with dementia now ultimately receive a formal diagnosis in United Kingdom health systems and many receive it late in the disease process, there is ample room for improvement. The policy of the UK government and National Health Service (NHS) is to increase rates of timely dementia diagnosis. We used data from general practice (GP) patient records to create a machine-learning model to identify patients who have or who are developing dementia, but are currently undetected as having the condition by the GP.

Methods

We used electronic patient records from Clinical Practice Research Datalink (CPRD). Using a case-control design, we selected patients aged

SUBMITTER: Ford E 

PROVIDER: S-EPMC6889642 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature