Putting the Meta into the Data: Managing Data Processing for a Large Scale CDC Surveillance Project with SAS

There are myriad epidemiological and surveillance studies ongoing due to the pervasive COVID-19 pandemic, often embodying the definition of “big data” with thousands of participants, variables, and lab samples. Data can be utilized coming from many different streams in a given study, for example: REDCap software, electronic medical records (EMR), chart abstraction, laboratory records, etc. Different contractors can be managing different aspects of the same project, the data is changing minute to minute, and the deliveries are required at a fast and furious pace. Wrangling all the different data sources requires robust data management routines, and SAS® can help, with tools to obtain data via APIs and PROC HTTP, metadata resources, and programming techniques. This paper and presentation will outline best practices for managing multiple aspects of large scale CDC surveillance projects, using SAS.

About the Presenter

Louise Hadden presented at her first SAS conference in 1996 and has never looked back, presenting at multiple conferences across the continent over the years. She supports analytic processing at Abt Associates Inc., a social science research company, and specializes in reporting, data management, and data visualization in the division of health and environment. Most recently her work portfolio has included large scale surveillance projects for the CDC and claims-based quality measure development, as well as the creation of data visualizations.