Artificial intelligence will significantly alter how we humans make decisions. It will also impact the way that we organise ourselves to do work itself. Organisations are a particular structure to bring together ‘brains’ to work together for common purposes and goals. Adding a ‘cognological’ dimension from artificial intelligence increases the mix of insights and analysis possible, but this will also change the way we need to organise ourselves.
In many cases we routinise work to enable easy communication, and in healthcare construct protocols and guidelines on how to treat patients, and various other criteria to manage the inherent complexity that is healthcare itself.
I include pharma and medical device companies here as they are significant actors, as well as patient support groups: all this will come under the influence of AI.
All decisions are predictions: we make a decision that reflects our understanding on the assumption that our decision will enable the change we anticipate in the future.
Medical reasoning is all about prediction. We think of clinical judgement but what we really mean is that the doctor is making a prediction about whether the diagnosis is correct, whether the treatment will be effective and whether the patient’s care trajectory will get them to recovery. These decisions by doctors of course drive costs into healthcare systems and one hopes they are good decisions but we know that many of them lead to medical errors.
By harnassing AI into clinical decision making we can lift clinical prediction performance from perhaps 75% right to 95% or more being right. That is a 30% reduction in possible errors and a quantifiable reduction in risk.
This also signals potential productivity gains in healthcare just by improving the quality of medical decision making and these productivity gains include reduction in costs for avoided treatment options. We call this precision healthcare.