One of the perennially-lacking tools to support development of EHRs and other health technology is the lack of good quality dummy data for testing. I’m involved in the INTEROPen Hackathon next week, and I thought it would be nice prep to make a very quick sketch API to randomly generate plausible blood glucose measurements and HbA1c values for the famous INTEROPen subject ‘Michael’, who has Type II Diabetes.
I’ve been Googling around this a bit and not found much of use already out there. Academic papers tend not to publish their actual algorithms, which is a shame.
I already have a Clinical Calculation API which I’ve been reviving as a project after a few years’ hiatus, so I’ve simply added a dummy-data endpoint to this existing API, which is a fairly rudimentary work in progress here:
What I’m asking from the community is:
does anyone have access to or could suggest a ‘plausible’ mean and standard deviation for blood glucose and HbA1c in Type II DM? Looking at you diabetologists or laboratory peeps @jonathan_kay In my testing I’m getting reasonable numbers from a mean of 10 mmol/l and a SD of 2.5, but this is just a clinical ballpark figure I came up with. There will be data out there, I just can’t find it.
does anyone know of any better way to model this than a Normal distribution?
Anyone want to help out or join in? (Minimal Ruby programming required, 1 hour tutorial should be enough to get you going) The idea is Plausible Dummy Data for various conditions served via API according to SNOMED-CT code.