A Technology-Driven Intervention to Improve Early Detection and Management of Cognitive Impairment

Most experts advocate for early detection of cognitive impairment (CI) so that patients and caregivers can be prepared for making difficult decisions and to improve quality of life, but studies show that screening alone isn't sufficient to change clinician actions related to early detection. Using predictive modelling developed with machine learning methods and sophisticated clinical decision support (CDS) tools, it is possible to identify patients at elevated risk for CI and make it much easier for primary care to engage and support patients and caregivers in meaningful care planning. The goal of this study is to implement and evaluate a low-cost, highly scalable CI-CDS system integrated within the electronic health record that has high potential to improve early CI detection and care and translate massive public and private sector investments in health informatics into tangible health benefits for large numbers of people.