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Wednesday, June 29 • 11:20am - 11:25am
Automated clinical research tracking and assessment using R-Shiny

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Many database tools enjoying widespread use in academic medicine, such as REDCap, provide only limited facilities for study monitoring built-in. They often do, however, provide the ability for analysts to interact with data and metadata via Application Program Interfaces (APIs). This offers the possibility of automated monitoring and web-based reporting via the use of external tools and real-time interaction with the API. nnIn this presentation we provide a framework for automated data quality and participant enrollment monitoring in clinical research using R Shiny Server. To illustrate, we demonstrate linkage of R Shiny to a REDCap database via its API, streamlining the process of data collection, fetching, manipulation and display in one process. Automated display of to-the-minute enrollment, protocol adherence, and descriptions of enrolled samples, are provided in a format consistent with NIH reporting requirements. Additionally, we demonstrate the flexibility of this system in providing interactivity to address investigator queries in real-time; for instance, investigators may select sample subgroups to display, or inquire as to the risk profile of an individual with an extreme baseline measurement on an important screening variable. This approach offers the potential to greatly increase efficiency and maintenance of data quality in research studies.

avatar for Joseph Rickert

Joseph Rickert

Program Manager, Microsoft
Joseph is a Program Manager at Microsoft having come to Microsoft with the acquisition of Revolution Analytics. He is a data scientist and R language evangelist passionate about analyzing data and teaching people about R. He is a regular contributor to the Revolutions blog and an... Read More →

avatar for Hao  Zhu

Hao Zhu

Institute for Aging Research

Wednesday June 29, 2016 11:20am - 11:25am PDT