The Heritage Health Prize

There's been an interesting trend in recent years: the comeback of public competitions to solve problems of various types. From the X-Prizes to the now-finished Netflix prize, competing for the kudos (and cash prizes) of solving a given problem is very much of the moment.

Of particular interest to me personally is the Heritage Health Prize. Run by the website Kaggle, on behalf of the Heritage Provider Network (a Californian healthcare provider), the aim of the competition is to predict the likely number of days of hospitalisation for a range of clients, based on their historical (anonymised) medical claims data. Being someone who researches statistical machine learning and is interested in applying ML methods to medical data sets, this is a pretty cool challenge.

There are some complications to using such a competition data set to research new machine learning methods. HPN and Kaggle are rightly very cautious about the data, and there are various ethical considerations about mining medical data in this way. My understanding is that they're willing to consider case-by-case whether research arising from these data can be published. We'll see how that pans out in practice.

I'm hopeful that I can do reasonably well in the HHP, but it's also an interesting area in which to research (provided publishing papers proves possible) and I'm finding that I'm getting some useful experience with new approaches and methods that I'd not used before.

And perhaps this is the strength of these competitions. The cash prize is nice, but there are also a lot of other things the competitors can get out of it.