Yesterday's original posting was interrupted by the Query Health call. Another of the favorite phrases at ONC is "Ultra-Large Scale Systems". It is often used to describe the extremely interdependent, hugely complicated, collection of systems across payers, providers and the federal government that is used to manage healthcare today in this country.
A number of Federal initiatives are driving for change in this complex patchwork quilt of enterprise applications. Many of these initiatives are planning on changing the system by introducing large perturbations, in the hopes that it achieves a new norm.
One of the things that constantly interests me though, is how difficult it is to create a large change in a ULS. These systems seem to have antibodies that reject any large change. Change in and of itself is scary, which may be one reason for that.
What I like to think about are small, seemingly insignificant changes that can eventually result in a large scale effect. One of the design principles of the IHE Reconciliation profile is a sort of self-correcting effect that eventually perturbs a collection of health records into something that contains fully reconciled data. They don't immediately get that way and stay that way. But as soon as a significant volume (the tipping point) of providers begin using it, the accuracy of patient medications, problems, and allergies data recorded in systems should improve dramatically.
The profile creates a set of small nudges, over and over again, to the data, improving the accuracy on each iteration. The end result is appears to the uninformed as something like the butterfly effect. In fact, what it is really doing is exerting a lot of small changes over time. Those small changes add up, and the system floats up as it were, to a new norm.
Finding big things to change is easy. Finding those little things to change, that's something worth thinking about.