We're the Douglas Neuroinformatics Platform[1], and we've been working on Open Data Capture, a web-based electronic data capture (EDC) platform for continuous clinical and research data collection. You can use it to administer instruments (like forms and interactive tasks) either in-person or remotely.
The platform is based on a fundamentally longitudinal data model. Unlike other EDC platforms, which are centered around the concept of a study with rigid timepoints, Open Data Capture is designed for continuous data capture. Data is associated with a given session, which includes metadata such as date, time, and mode (i.e., in-person or remote).
We've designed the system around the core restriction that many hospital institutions demand that data remain on-premise, while clinician-researchers often want to evaluate clients outside the institution with research questions. This has resulted in our innovative gateway concept, where assigned remote assessments are pushed onto an internet accessible service, and responses are encrypted in-place with HPKE[2] until the backend pulls them into the backend database. This makes the deployment firewall-friendly provided you can launch a minimal VPS or VM host somewhere globally accessible.
We're also a big fan of making things easy to deploy, so we supply a docker-compose stack which can bring up a demo instance easily to run locally.
The platform is free, open source, and written in TypeScript, with a NoSQL database underneath. Users can write instruments in TypeScript using a type-safe declarative form system (with native i18n support built in) or wrap and integrate completely arbitrary interactive tasks written in JavaScript (with optional support for TypeScript and JSX). Under the hood, this is based on dynamic imports and native ESM. There’s a browser-based IDE (the Instrument Playground) with live reloading and full Intellisense where you can try creating your own instruments.
We have a local deployment going live at our institution and appropriately-licensed (free) instruments we're deploying here will be integrated directly into the codebase.
Our future plans include expanding our instrument types to allow for binary data storage with an s3-like backend, and with abstractions for data types, like actigraphy, and MRI.
Check it out on GitHub[3], try the Instrument Playground[4], or see the Live Demo[5].
Would love to hear everybody’s thoughts!
Links:
[1] https://github.com/DouglasNeuroInformatics/
@gdevenyi @joshunrau
[2] https://datatracker.ietf.org/doc/rfc9180/
[3] https://github.com/DouglasNeuroInformatics/OpenDataCapture