OpenDatabetes

I’ve started a Github project called Opendatabetes in an attempt to get some of my goals into reality. OpenDatabetes will be an open source data model for storing and exchanging diabetes treatment information, as originally dreamed about here.

The Current Model

Do you log your sugars in a personal logbook you made yourself or you write? That’s the only way to really keep it as your data. But you can’t do a lot with the info if you do that.

A more and more popular choice for diabetics is to use some kind of management software, often one that comes bundled with an insulin pump or glucometer. These allow some awesome things like: creation of reports, automated data collection from your devices, sharing information with healthcare professionals, etc. Part of that model is definitely the way forward.

But, caveat time!!: A lot of these systems aren’t great for one reason or another, and many of them are also locked into disappointingly slow release cycles (either because it’s not a key to a large pharma company’s overall income strategy, or because it’s a lot of work for an independent software developer who already has a full-time job). And once all your data is in one of these proprietary systems, changing to a different one isn’t easy because you can’t normally bring your data with you. (changing meters, pumps, or just trying out new management software)

There’s little or no standardization between these proprietary systems. It’s almost like if every website you went to required you to install a new plugin to view it.

How We Ought to Do It

To continue the website analogy: The internet is based on standards set out by the W3C (World Wide Web Standards Consortium). The browser makers defer to the W3C on how the underlying website code (HTML and CSS) works, but they can also contribute to it to help keep the platform evolving.

That’s what we we need for diabetes. Well, not exactly that, but something where there are at least connecting lines between the silos.

Having a central, open standard for diabetes data exchange would empower anyone interested to work with different ways of interpreting or displaying the data and it would free diabetics to experiment with different services without being locked into one. It would allow diabetes tools to be modular and work with one another.

Chart illustrating that with homebrew system you have ownership of data but little ability to use it. With proprietary system you have no flexibility but can get many insights. With Opendatabetes you get best of both worlds.

Are you getting the most out of your diabetes data?

What Does it Look Like?

So just what is OpenDatabetes, practical-deliverable-style?

It is an open data format for recording diabetes treatment information. Basically a file-type, so that if you have a *.dbts file it can be read by any program that supports the format.

It has to be flexible enough to cover various types of treatment: injection, pump, CGMS, etc. It must accommodate for metric and imperial measurements. It must be designed for maximum usefulness and efficiency when integrating with other systems.

Once I have a satisfactory data format, the goal of the project will be to create scripts to convert from proprietary formats to opendatabetes.

The idea is to provide a standard for anyone to use, encourage them to use it, but also make conversion tools so that companies when don’t use them, you can still own your data.

So that’s the genesis of my idea for Open Databetes, and I’ve put some things (mostly my attempts at data-modelling from the Sanguine prototype) on Github. Would love to hear any thoughts on how useful is this project, things to look out for, etc

3 thoughts on “OpenDatabetes

    • Hi Scott, I made the link a bit more obvious.

      I’ve been trying to find if anyone else has worked on something similar and saw this so it may be that some of the work is already being done by others 🙂 Seeing what else I can dig up.

  1. That should read more like “You: Low”, “Device/Software Company: Very Low”. Personally, I’ve never gotten useful analysis out of proprietary diabetes systems, since I use Linux, and none of them (purposefully/easily) work with it.

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