Digital Health Expertise
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Digital health research involves an interdisciplinary effort that draws on aspects of design, ethics, engineering, and data science. Since 2014, Sage Bionetworks has built teams and technologies described below to execute on the different aspects of conducting a digital health study. If you are interested in partnering with us, reach out to start a conversation about your project. Also, learn more about our digital health assessments.Let's Get Started
Measure Validation and Study Design
Given the different modes for collecting digital measures, such as the possibility for collecting high frequency longitudinal sampling or data in uncontrolled environments, there are multiple study design considerations. At Sage we actively are involved in adopting study protocols as digital measures are added. We can assist with study design, protocol development as well as developing completely novel measurements. When developing new measures, we can assist in collection and evaluation of validation data. To date, we have developed dozens of digital measures across diverse areas of health spanning cognition, neurodegeneration, and cardiorespiratory fitness.
eConsent, Privacy, and Ethics
Sage’s eConsent process was designed from its inception to be remotely completed by a potential study participant on a phone, tablet, or computer screen, with available support via email, phone, or text. We have developed the Elements of Informed Consent Toolkit to share our knowledge base and best practices for developing an effective consenting process. These best practices formed the foundation of Apple’s ResearchKit eConsent process and has been used in the All of Us Research Program. Given recent well-publicized data breaches and consumer privacy violations, designing technologies that are transparent and respectful of end-users’ privacy is an ethical and legal mandate. To this end, we have developed the Privacy Toolkit, an open-source repository that provides biomedical researchers with a catalogue of design best practices and patterns to increase transparency of how end-user data is being collected and used in mHealth studies.
Our goals are to design a digital experience that both creates value for the study participants and generates novel, high quality data for researchers. Our UX research team employs a user-centered design process ranging from formative interviews to usability studies to create, validate and improve the experience for a participant in a digital health study. We frequently enlist patient representatives to guide the design and development of our research studies. In analyzing our work across over 30 digital health studies, we have codified our best practices into the Design System. This resource serves as a foundation for our UX/UI design, and is freely available to the research community.
Sage has developed a variety of native iOS and Android apps for digital health research studies in collaboration with academic institutions, pharmaceutical companies, non-profit institutions, and tech companies. These studies have enrolled over 100,000 participants and have included large-scale remote monitoring of health conditions, measuring disease symptoms in clinical trials, and validating novel digital measures. Sage was instrumental in establishing the open source ResearchKit and ResearchStack frameworks, and these serve as the foundation for our app development along with other Sage SDKs. These front-end applications communicate with our HIPAA-compliant Bridge Server via our iOS SDK, Android SDK, or via our REST API. Whether it’s through building a custom research app, or providing tools, code libraries, and technical advice to external development teams, Sage’s mobile engineering team can greatly accelerate a digital health study.
Digital Data Collection
Data from digital health research can be generated from an increasingly diverse set of sources. To enable data collection in this context, we have built a set of web services collectively called Bridge to securely aggregate data from smartphones, wearable devices, and other data services. Aggregated data is made accessible to researchers through a collaborative data analysis platform called Synapse that allows API access through common analytical tools (e.g. R, Python, web, or command line). These platforms also provide active monitoring of study participation and compliance as well as possible integration with existing clinical collections such as RedCap. Although our infrastructure is open source, many researchers integrate the technology into their studies under a software-as-a-service model. Sage’s platforms are HIPAA-compliant, HI-TRUST certified and built on top of AWS to manage digital health research data in a secure and ethical fashion. The platform has supported over 30 different research apps developed by Sage or one of our partners. To translate a study design to a digital experience within our platform, we have developed the Bridge Study Manager to allow research teams to configure, manage, and monitor their study once it has been deployed.
Data Analysis and Benchmarking
Digital health research has opened up novel methods for performing research, but deriving insights from these data requires careful consideration of statistical approaches, quality control and analytical approaches for turning raw sensor data into measures of disease or health. At Sage, we actively work to develop software tools, discover best practices, and benchmark methods for use in digital health studies. We can assist in developing statistical analysis plans , data processing and QC as well as help evaluate your measures.
Open datasets for evaluation of new algorithms, data analysis and benchmarking is essential to our approach to open science. We make available to the research community digital health data that has been consented for broad reuse. We do this for studies both going through our infrastructure but also provide data curation, and governance services to make other researchers data accessible. Data can be shared on the Digital Health Data Portal. This portal contains open source digital health data from numerous studies hosted on our Synapse platform. Data from our digital health studies is deposited into Synapse, a collaborative data science platform that allows individuals and teams to share, track, and discuss their data and analysis in projects. Synapse hosts many research projects and resources. It also hosts crowdsourced competitions, including DREAM Challenges. Sage Bionetworks provides Synapse services free of charge to the scientific community through generous support from various funding sources.