I’m increasingly disturbed by a very backward tendency to implement bad science in healthcare IT systems. More and more often, I read about initiatives to mine electronic healthcare records for data and build some kind of knowledgebase from this, then use it to support clinical decision making. It sure sounds sexy from a technical standpoint, but it’s so wrong.
We used to have anecdotal medicine, or experience-based medicine if you prefer, where each doctor largely learned from his own patients, mistakes, and successes. This led to a lot of wrong conclusions, since outcomes are multifactorial. That is, there are a bunch of reasons why any particular case goes right or goes wrong, and you can’t control for those reasons if you learn from cases after the fact.
Then we decided to only advance medical science on properly designed, prospective, and controlled clinical studies, which seems to be the only way to get anywhere in the long run. So that’s what we should do.
The reason I posted this today is that I just read something horrifying in an otherwise excellent book (which you can get for free here), the “4th Paradigm”, Microsoft Press. This is an excerpt:
…current trends toward universal electronic healthcare records mean that a large proportion of the global population will soon have records of their health available in a digital form. This will constitute in aggregate a dataset of a size and complexity rivaling those of neuroscience. Here we find parallel challenges and opportunities. Buchan, Winn, and Bishop apply novel machine learning techniques to this vast body of healthcare data to automate the selection of therapies that have the most desirable outcome. Technologies such as these will be needed if we are to realize the world of the “Healthcare Singularity,” in which the collective experience of human healthcare is used to inform clinical best practice at the speed of computation.
No, please don’t destroy medical science like this…