Device Connect for Fitbit connects Fitbit data to Google Cloud and makes it available alongside clinical data for analytics and care decisions.
What Is Device Connect for Fitbit?
Device Connect for Fitbit enables a more holistic view of patients with connected Fitbit data on Google Cloud. It solves data integration challenges for Fitbit and other data with an open, standards-based approach.
Google Cloud describes the benefits as better device interoperability that can accelerate time to insight for care teams, help increase productivity, and ease workloads and burnout. It also aims to give the healthcare ecosystem visibility into rich patient data to better understand what is driving variability in outcomes.
Core Features
- Enrollment and consent app: Pre-built web and mobile app providing permissions, transparency, and control over what data is shared and how it is used
- Fitbit data connector: Open source connector with automated data normalization and integration into BigQuery
- Pre-built analytics dashboard: Interactive Looker dashboard, customizable for different clinical settings
- AI and machine learning tools: AutoML Tables for models built directly from BigQuery, plus the Gemini Enterprise Agent Platform for custom models
Typical Use Cases
Pre- and Post-Surgery
According to Google Cloud, supporting the patient journey before and after surgery can lead to higher patient engagement and more successful outcomes. Fitbit tracks multiple behavioral metrics including activity level, sleep, weight, and stress, giving care teams visibility into what happens outside the hospital.
Chronic Condition Management
Better understanding of how lifestyle factors affect disease indicators enables more personalized care and tools that support healthy lifestyle changes.
Population Health
Support better management of community health outcomes with a focus on preventative care. Fitbit users can share data with partners that deliver lifestyle behavior change programs.
Clinical Research
Clinical trials depend on rich patient data. Fitbit can enrich trial endpoints with longitudinal lifestyle data and can improve patient retention and compliance with study protocols.
Benefits
- Open, standards-based approach: Support for emerging standards such as Open mHealth
- Interoperability with clinical data: In combination with the Cloud Healthcare API for cohort building and AI training pipelines
- Faster insights: Pre-built Looker dashboard instead of custom development
- Control for individuals: Consent app with transparency over data use
Integration with innFactory
As a certified Google Cloud partner, innFactory supports you with Device Connect for Fitbit: assessing data protection requirements, connecting to BigQuery and the Cloud Healthcare API, and customizing the analytics.
Typical Use Cases
Technical Specifications
Frequently Asked Questions
What is Device Connect for Fitbit?
According to Google Cloud, Device Connect for Fitbit enables a more holistic view of patients with connected Fitbit data on Google Cloud. It addresses data integration challenges for Fitbit and other data with an open, standards-based approach.
What components are included?
Google Cloud names four building blocks: a pre-built enrollment and consent app for web and mobile, an open source Fitbit data connector, a pre-built Looker dashboard for visualization, and AI and machine learning tools.
How is the data integrated?
The open source data connector provides automated data normalization and integration with Google Cloud BigQuery for advanced analytics. It can support emerging standards like Open mHealth and, when used with the Cloud Healthcare API, enables interoperability with clinical data for cohort building and AI training pipelines.
What control do users have over their data?
The pre-built patient enrollment and consent app enables organizations to provide their users with the permissions, transparency, and frictionless experience they expect. Users have control over what data they share and how that data is used.
What analysis options are available?
The pre-built interactive Looker dashboard can be customized for different clinical settings and use cases. For modeling, AutoML Tables can build models directly from BigQuery, and the Gemini Enterprise Agent Platform supports custom models.
Note: All product information on this page has been compiled with care, but is provided without guarantee and may be outdated or incomplete. Cloud services evolve rapidly — features, pricing, SLAs, and availability change frequently. Authoritative and up-to-date information can only be found on the official product page of Google Cloud (official documentation). This page does not represent an offer by Google Cloud.
