Utilizing open-source platforms to build and deploy interactive patient-reported quality of life tracking tools for monitoring protocol adherence

Purpose: Tracking patient-reported outcomes (PROs) and quality-of-life response rates is essential for clinical trials. Historically, rates are monitored through scheduled reports, which can require gathering, merging, and cleaning data from multiple databases. At the end of this process, if gaps are found, new data are entered and the cycle repeats, leaving a trail of reports that are not up-to-date or immediately accessible to the investigator. The financial and person-hour cost of utilizing clinical research staff for this purpose is impractical. Online dashboards are continuously updated to monitor data, providing on-demand access to promote successful research. Methods: Dashboard implementation utilizes R, an open-source statistical programming language, RMarkdown, a markup language, Flexdashboard, which creates structural elements, and Shiny, allowing investigators the ability to interact with data within the dashboard. By leveraging these four elements, powerful, cost-effective interactive dashboards can be built. Results: Numerous dashboards have been utilized to identify potentially missing data and increase protocol adherence. Immediate patient consultation can occur to retrieve protocol-related forms, reducing research staff and patient burden while improving trial effectiveness. Dashboards can monitor PROs, enrollment, demographics, toxicity, and biomarker data, clinical outcomes, and implemented predictive models, creating a single hub for on-demand clinical trial monitoring. Conclusion: By employing a set of freely available tools, the burden of utilizing study staff to continuously monitor trials is greatly reduced. These tools allow users to rapidly build and deploy dynamic dashboards capable of meeting the research needs of any investigator while limiting missing data through simplified monitoring of protocol adherence.