Milestone 1.H

Enable access to electronic health records (EHR) data and provide support for their integration with clinical and molecular data to build person-specific predictive models of disease and wellness and to enable disease sub-classification. These efforts should include better electronic phenotyping of AD through the application of machine learning methods.

Success Criteria

Hold an advisory meeting focused on understanding and overcoming barriers to sharing and usability of electronic health records in the US and globally.
Initiate a research program focused on electronic phenotyping of AD through the application of machine learning methods and integration of EHR data with genomic, molecular, clinical and other patient relevant data to build person-specific models of disease, to identify disease sub-types and to identify biomarkers and molecular signatures for these subtypes.

Research Implementation Area: Population Studies and Precision Medicine
Timeline: 2019–2022
Status: In Progress

Accomplishments/Implementation Activities

Funding Initiatives

Research Programs and Resources

Construct Large-Scale Phenomes of Diseases and Drugs and Develop Data-Driven Systems Approaches to Understand Genetic Links Between Alzheimer’s Disease and Neuropsychiatric Symptoms

Research Highlights

News: Electronic health records-based tool uses data to detect undiagnosed dementia

Relevant Recommendations

2018 AD Summit: 2G, 2H and 4K