We have begun working on a project to help deliver “synthetic” healthcare records using APIs. Providing realistic, but virtualized patient records for use in the delivery of APIs in healthcare. Providing a set of APIs that emulate real-world production APIs, but provide synthetic electronic healthcare records that will help developers develop, testing, and eventually deploy useful healthcare applications, without working with sensitive production healthcare records–offering a safe environment to potentially improve healthcare outcomes with APIs.
While the APIs we are deploying synthetic data for as part of this round are basic web APIs, we are already beginning to plan for streaming editions of these sandbox APIs. Considering how we might emulate real-world scenarios where patient data is being updated in realtime, or possibly the streaming of data from healthcare devices, and personal wellness devices. Planning for a variety of electronic healthcare and healthcare Internet of Things scenarios where data should be delivered in real time using streaming APIs, over polling of existing web APIs, and focusing on not just real time, but also efficiently delivering potentially life saving information.
Using Streamdata.io, to deliver synthetic healthcare data using APIs isn’t that complicated. All you have to do is design and deploy a virtualized API that reflects the request and response structure of a regular API, but then emulate real-world POSTs to that API. If the web API is proxied with Streamdata.io the data will stream as it is POSTed (added) to the datastore behind the API. Emulating the production healthcare API, schema, and hopefully a variety of real-time scenarios. We could even queue up the different scenarios in a sandbox environment, and let developers trigger a variety of situations to test out different functionality in their applications. Proving that they can respond to a variety of real-world healthcare scenarios they will come across in a production environment.
This work has gotten us thinking about other synthetic streaming data scenarios across other industries. Emulating different financial and banking scenarios, or possibly support, chat, and scripted messaging situations developers might encounter operating their applications. We are focused on virtualized healthcare data at the moment, but once we’ve developed a suite of synthetic data scenarios for a healthcare API labs environment, we will explore beyond just this use case. Brainstorming on what is possible when you provide not just real-time streaming capabilities, but emulate these environments in a sandbox, virtualized, and laboratory environment, that allows developers to experiment in a safe and controlled space. Helping improve real-world outcomes, but done so in a way that is much more private, secure, and controlled.
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