2 METHODS

This is a retrospective cohort study using Stanford Healthcare data from 1999 to 2022. The use of this data for this study was approved by Stanford's Institutional Review Board. Our data are formatted in the Observational Medical Outcomes Partnership (OMOP) model. 6 The cohort consists of 157,804 (MCI and non-MCI) patients, who had at least one primary care visit after reaching the age of 65; with an average age of 73 and 57.7% were females. 15.1% of patients were Asian, 6.4% were Black, 0.2% were American Indian, 0.9% were Native Hawaiian, 64.3% were White, and 13.1% had other/unknown races or declined to state their race. Our study includes two main components:(a) MCI prediction and (b) MCI to AD progression prediction. We extracted 531,387 primary care visits (for all 157,804 patients in our cohort; each patient has multiple visits) where the patients were at least 65 years old at the time of their appointment. All historical EHR records, including diagnoses, prescriptions, procedures, and clinical notes before the primary care visits, were extracted. Note clinical note features are pre-processed and extracted in the form of standardized SNOMED structure concepts from patients' notes as part of OMOP data model. 7 The OMOP Common Data Model standardizes healthcare data for research. By standardizing the representation of patient information and healthcare data elements, OMOP enables researchers to produce reliable evidence, conduct large-scale and multisite studies, and develop predictive models using data from multiple institutions, enhancing our understanding of health outcomes and treatment effectiveness.