SMILE-PD: Similarity Matching In Longitudinal Electronic Patient Data

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PROJECT SUMMARY The NIH All of Us (AoU) Research Program is a national research initiative launched by the National Institutes of Health (NIH) in May 2018 with the goal of advancing precision medicine, which aims to provide personalized medical treatment and prevention strategies based on an individual's unique genetic, environmental, and lifestyle factors. Analysis of real world data like AoU typically requires creation of cohorts that are clinically similar with the exception of the characteristic(s) being evaluated. If the creation of compared cohorts is not conducted with care, results may be confounded by systematic difference in the characteristics of patients assigned to the compared cohorts. This proposal, Similarity Matching In Longitudinal Electronic Patient Data (SMILE PD), will apply a sophisticated patient matching algorithm within an easy- to-use interface to help Investigators to create suitable analytical cohorts to enable generation of accurate, reproducible real world evidence from the rich content of the All of Us data. The project has 4 Aims : • Aim 1. Develop algorithms that learn patient similarities from AoU data in a comprehensive manner. • Aim 2: Develop approaches that can integrate drug and disease information from publicly available data sources to improve the quality of learned patient similarities. • Aim 3: Implement an interactive user interface to specify similarity matching criteria and demonstrate the learned patient similarities • Aim 4 : Apply the patient similarity matching algorithm and interface to conduct an initial assessment of the impact of mental illness and its treatment on chronic disease outcomes The patient similarity matching interface created through this proposal will enable investigators to conduct predictive analytics, risk assessments and comparative effectiveness research in a more robust and reproducible fashion.