The Actual Consequences of Decision-Support
AI edition!
This is an AI-centric look at the problem, but it generalizes nicely to any sort of clinical decision-support: what are the practical manifestations of a predictive or prescriptive technology?
I might be in the minority regarding appreciation of the unintended consequences of clinical IT, so I appreciate this call for a framework of formal documentation of the downstream impact of workflows changing as a result of CDS interventions. It’s quite easy to report sensitivity, specificity, AUROCs, NPVs, etc., but even clinically advantageous CDS can fail if the change in demand for services shifts the burden from traditional care pathways to new bottlenecks.
Their examples:
A good lens for technology developers to use when attempting to translate their innovation into the existing conditions and constraints of a health system.