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https://www.acr.org/Clinical-Resources/Clinical-Decision-Support
Clinical Decision Support Educate Referring Providers with the PAMA-AUC Toolkit For radiology professionals regarding PAMA and the genesis of the AUC requirement: NEW CDS for Appropriate Ordering of Imaging PPT (to present to radiology audiences)
https://www.adrad.com/for-physicians/clinical-decision-support/
Beginning January 1, 2020, the Centers for Medicare and Medicaid Services (CMS) will begin a year-long educational and operations testing phase prior to requiring all Medicare Part B advanced diagnostic imaging requests to carry a code signifying that the ordering medical professional consulted a qualified Clinical Decision Support mechanism (CDSM).
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Appropriate-Use-Criteria-Program/CDSM
A Clinical Decision Support Mechanism (CDSM) is an interactive, electronic tool for use by clinicians that communicates appropriate use criteria (AUC) information to the user and assists them in making the most appropriate treatment decision for a patient’s specific clinical condition.
https://radadvocate.com/clinical-decision-support/
The rule requires that AUC be consulted, via a qualified Clinical Decision Support Mechanism (CDSM), by the ordering physician or his/her clinical staff (see definition below), prior to ordering advanced imaging services(CT, MRI, PET, nuclear medicine). AUC specify when it is appropriate to order advanced imaging services.
https://www.itnonline.com/article/intro-clinical-decision-support-radiology
Mar 19, 2013 · In radiology, the main use of clinical decision support is to quickly determine what type of imaging exam or diagnostic testing is needed for a patient with specific symptoms. The software is based on AUC set by various medical societies, including the American College of Radiology (ACR).
https://www.aidoc.com/blog/radiology-decision-support/
Oct 29, 2019 · Clinical decision support software offers the radiologist ample opportunity to enhance workflows, reduce system complexity, improve processes, support in diagnoses, and utilize legacy and existing data to inform decision making.
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