Vishal Khetpal & Nishant Shah in an opinion piece for Undark:
In the midst of the uncertainty, Epic, a private electronic health record giant and a key purveyor of American health data, accelerated the deployment of a clinical prediction tool called the Deterioration Index. Built with a type of artificial intelligence called machine learning and in use at some hospitals prior to the pandemic, the index is designed to help physicians decide when to move a patient into or out of intensive care, and is influenced by factors like breathing rate and blood potassium level. Epic had been tinkering with the index for years but expanded its use during the pandemic. At hundreds of hospitals, including those in which we both work, a Deterioration Index score is prominently displayed on the chart of every patient admitted to the hospital
The use of algorithms to support clinical decision making isn’t new. But historically, these tools have been put into use only after a rigorous peer review of the raw data and statistical analyses used to develop them. Epic’s Deterioration Index, on the other hand, remains proprietary despite its widespread deployment. Although physicians are provided with a list of the variables used to calculate the index and a rough estimate of each variable’s impact on the score, we aren’t allowed under the hood to evaluate the raw data and calculations.
Blind trust in an algorithm that is create and maintained by a for profit institution without transparency of the data or calculations performed is insane. How do we know what assumptions are made? What the actual characteristics of the calculations are? How are they validated?
We don’t just trust the word of researchers findings without peer review - why should we treat an algorithm any different?