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Fail: Computerized Clinical Decision Support Systems for Medical Imaging

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Computerized systems that help physicians make clinical decisions fail two-thirds of the time, according to a study published today in the Journal of the American Medical Association (JAMA). With the use of such systems expanding—and becoming mandatory in some settings—developers must work quickly to fix the programs and their algorithms, the authors said. The two-year study, which is the largest of its kind, involved over 3,300 physicians. 

Computerized clinical decision support (CDS) systems make recommendations to physicians about next steps in treatment or diagnostics for patients. The physician enters information about the patient and the ailment, and based on a database of criteria, algorithms come up with a score for how appropriate certain next clinical steps would be. These databases of “appropriateness criteria” have been developed by national medical specialty societies and are used across various CDS systems. They aim to reduce overuse of care that can be costly and harmful to patients

But according to the JAMA study, the leading CDS systems don’t work most of the time. The study tracked more than 117,000 orders input by physicians for advanced diagnostic imaging procedures such as magnetic resonance imaging (MRI) and computed tomography (CT). For two-thirds of those orders, the computer program could not come up with any feedback. “Basically it says, ‘I don’t have a guideline for you. I can’t help you,’” says Peter Hussey, a senior policy researcher at RAND Corporation and the lead author of the study. “When that happens two-thirds of the time…the physicians start to get more negative about it.”

That’s a problem, because these computerized decision makers will soon be mandated by the U.S. federal government. The Protecting Access to Medicare Act of 2014 says that, starting in 2017, CDS systems must be allowed to weigh in on whether advanced diagnostic imaging should be ordered for Medicare patients. CDS systems are already used in the private sector as well, but not widely, Hussey says.   

The systems’ problems are likely caused by lackluster databases and algorithms that fall short, says Hussey. “There are lots of different kinds of patients with different problems, and the criteria just haven’t been created for some of those. In other cases, it’s likely that the criteria were out there but the CDS tools couldn’t find them,” he explains. “These seem like solvable problems, but we need to get working on this pretty quickly becaue this is going to be mandatory in a couple of years.”

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