It isn’t often that I come across an article that truly resonates with me, but Next-Generation Phenotyping of Electronic Health Records, by Hripcsak and Albers, did just that. While the authors’ main focus is EHR data quality, they make this intriguing observation/suggestion:
It will require study of the EHR as if it were a natural object worthy of study in itself (emphasis mine), and it may be helpful to employ the general paradigm of physics, which involves modeling and aggregation. It will be helpful to pull in expertise and algorithms from many fields, including non-linear time series analysis from physics, new directions in causality from philosophy, psychology, economics, of course our usual collaborators in computer science and statistics, and even new models of research that engage the public.
I absolutely agree–it is time to start treating EHR systems as more than front ends to data stores. Considering the role that EHR systems are expected to play in improving healthcare quality and safety while lowering or stabilizing costs, the design of clinical systems is rarely discussed in the literature. As I have mentioned in previous posts, most EHR-related standards address the content and features EHR systems should have, but specifically disclaim any concern about how systems should be built. It’s almost as if the prevailing attitude is that EHR design and architecture are straightforward and require little real intellectual input. This raises another issue that I think deserves discussion—the intellectual work of software development.