Design and protocol of a pragmatic clinical trial to improve cognitive impairment detection in primary care

Background

The prevalence of cognitive impairment (CI) including Alzheimer's disease (AD) and related dementias (ADRD) continues to rise worldwide, but often goes undiagnosed leading to increased burden on patients and families. A clinical decision support system (CDSS) could improve care quality by assisting primary care clinicians (PCCs) to recognize, evaluate, diagnose, and manage patients with CI.

Methods

38 primary care clinics are randomized to receive the study intervention or usual care (UC). The study intervention consists of a cognitive impairment clinical decision support system (CI-CDSS) and a brief CI-focused training. The CI-CDSS utilizes electronic health record (EHR) data to alert PCCs of patients who may be at high risk for CI, determined by either an abnormal cognitive assessment or identification as high risk using a prototype prediction model developed for this study that estimates likelihood of developing CI in the next 3 years. It also provides tools and resources to evaluate and diagnose CI and gives recommendations for managing care of patients with CI.

Endpoints

The primary outcome is EHR documentation of CI diagnosis up to 18 months after accrual. Secondary outcomes include healthcare costs and PCC confidence in diagnosis and management of patients with CI.

Conclusion

This pragmatic, cluster-randomized, Phase III clinical trial aims to assess the effectiveness of a CDSS in increasing detection of CI in primary care. If successful, this system could provide up-to-date personalized recommendations for CI diagnosis and management to improve patient care.