0322 Development of Complex Data Platform for the Stanford Technology Analytics and Genomics in Sleep (STAGES) Study. (12th April 2019)

• Record Type: Journal Article
• Authors: Leary, Eileen B; Seeger-Zybok, Rebekka K; Mazurek, Marcin; Voronoy, Alexey; Lawlor, Benjamin; Stephenson, Cheryl Liane; Kushida, Clete; Mignot, Emmanuel
• Is Part Of: Sleep. Volume 42(2019)Supplement 1
• Page Start: A132
• Page End: A132
• Publication Date: 2019-04-12
• Subjects: Sleep -- Physiological aspects -- Periodicals; Sleep disorders -- Periodicals; Sommeil -- Aspect physiologique -- Périodiques; Sommeil, Troubles du -- Périodiques; Sleep disorders; Sleep -- Physiological aspects; Sleep -- physiological aspects; Sleep Wake Disorders; Psychophysiology; Electronic journals; Periodicals; 616.8498
• DOI: 10.1093/sleep/zsz067.321
• Languages: English
• ISSNs: 0161-8105

Abstract

Abstract: Introduction: The Stanford Technology Analytics and Genomics in Sleep (STAGES) is a prospective cross-sectional, multi-site study charged with collecting and disseminating data to the scientific community. The following data elements will be obtained from 30, 000 adult/adolescent sleep clinic patients: (1) in-lab polysomnography, (2) online questionnaire (Alliance Sleep Questionnaire), (3) blood sample (DNA, serum, plasma), (4) University of Pennsylvania's computerized neurocognitive test battery (CNB), (5) 3D photo, (6) 2-weeks of actigraphy with sleep diary, and (7) clinical data from the electronic health record. The multifaceted nature of the project required a robust data platform employing creative techniques to receive, organize, and share an array of electronic data elements aggregated from multiple external systems. Methods: STAGES partnered with Prometheus Research, LLC to design and build a customized platform using their open source integrated research registry, RexStudy. The teams met regularly to develop a system that would meet the project needs. Requirements included: mechanisms to securely transfer data from multiple disparate data sources and match to correct subject, patient portal to enroll participants via electronic consent and accommodate electronic case report forms, extensive data validation and error reporting, granular access privileges for different user classes, sophisticated querying and analytic tools, and ability to export all data for complete portability. Each phase of the project, including creation of custom APIs, was heavily tested in a user acceptance testing (UAT) environment before being deployed to production. Results: The STAGES data platform currently holds data from the 530 enrolled research participants. Fifty members of the STAGES team have accounts for entering, analyzing, or monitoring the 75 plus data tables, and so far, there are more than 20 queries for data monitoring and quality control. Conclusion: The STAGES data platform was successfully deployed and is being used to collect, monitor, and analyze data from multiple external sources. We are continuing to add functionality to enhance the system's utility. Support (If Any): Klarman Family Foundation