We’ve got you covered
Digital health from start to finish.
The whole stack.
What’s possible with Open mHealth?
You need to be able to write applications that can process and create data, regardless of where the data came from. We can help with that. Our platform is built on structured health data, which helps companies, organizations, and individuals exchange data and reuse code. It also makes the data easier to understand.
We use schemas to define the structure of health data. We’ve brought together top clinical experts, data scientists, developers and software architects to come up with simple, extensible, and clinically valid schemas for the most common and important types of data in healthcare.
Whether you’re processing and analyzing health data or serving it to an application for visualization, you’re going to need to store the data in such a way that other components can access it. Our RESTful API lets components read and write health data without needing to know how the data is stored or where it came from. The API consumes and produces data that conforms to schemas, and authorizes access using OAuth 2.0.
If you’d like to download an implementation of the API, check out our open-source reference implementation. It’s backed by MongoDB and is easy to deploy using Docker.
Integrate disparate data streams
Get access to the digital health data your users create on 3rd party products and apps. Open mHealth’s open-source adapters pull in health and related data from the APIs of large providers like RunKeeper, Fitbit, Google and Apple, and convert it to match our schemas. This data can then be processed or visualized regardless of where it came from, letting you quickly prototype ideas or build production-ready applications.
You can see a list of the data providers we’ve integrated with and the measures they support.
Share your data with others
Make your structured health data available to others in the Open mHealth ecosystem.
Our RESTful storage API is already understood and used by companies, organizations, and individuals. If you want to provide your health data to others, either implement the API or use our storage component and point your collaborators to it. And this API leverages OAuth 2.0 to let your users decide who can access their data, giving them the control they demand and deserve.
Uncover deep insights from the health data collected from sensors, apps, and consumer devices. You may need to compute statistics, implement decision support, or create models, for example.
While some processing is specific to your application, some processing tasks are common to many scenarios.
Seeing is understanding. By combining raw health data, contextual data, and processed data into a single user interface, help your users better understand and act on the data that has been gathered and created.
We’ve put together a library of visualization examples which will allow you to get started with visualizing health data without building from scratch.
Integrate data from health apps and devices, EHRs, or Apple’s HealthKit
Fast, free, open-source.
Shimmer: the first open-source health data aggregator
Shimmer makes it easy to pull health data from popular third-party APIs like Runkeeper and Fitbit. It converts that data into an Open mHealth compliant format, letting your application work with clean and clinically meaningful data.
Within hours, you’ll be integrating health app and device data without spending a cen
Granola: save HealthKit data off-device
If you’re a developer interested in building iOS apps that store HealthKit data off the device -perhaps a remote server for analysis or backup – Granola can help you format your data.
Granola spares you the effort of mapping HealthKit’s API to JSON yourself, and emits JSON that validates against schemas developed by Open mHealth to ensure the data is intuitive and clinically meaningful.
Pulse: import and export EHR data in a more clinically meaningful way
Pulse helps you map HL7 data to Open mHealth’s clinically meaningful schemas. This helps you get your application’s data into EHRs – where providers are more likely to see it – in a more uniform way.
It also helps you get data out of EHRs in a standard format, so that you can do whatever you need with it.