Lauren Parks Golding1, Gregory N Nicola2, Richard Duszak3, Andrew B Rosenkrantz4. 1. Triad Radiology Associates, Winston Salem, North Carolina. Electronic address: laurengoldingmd@gmail.com. 2. Hackensack Radiology Group, PA, River Edge, New Jersey. 3. Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia. 4. Department of Radiology, NYU Langone Medical Center, New York, New York.
Abstract
PURPOSE: CMS implemented Merit-Based Incentive Payment System (MIPS) policies to cap points and remove "topped out" quality measures having extremely high national performance. We assess such policies' impact on quality measure reporting, focusing on diagnostic radiology. METHODS: Data regarding MIPS 2019 quality measures were extracted from the CMS Quality Benchmarks File and the Quality Payment Program Explore Measures search tool and summarized by collection type and specialty. RESULTS: Among 348 MIPS measure-and-collection-type combinations, 40.5% were topped out (56.6% of those with a benchmark) and 23.3% were capped. Among measures with a benchmark, the percent topped out varied (P < .001) by collection type: claims 82.7%, qualified registry 60.4%, electronic health record 11.6%. The percent capped was also greatest for claims measures (52.3%). Among 699 Qualified Clinical Data Registry (QCDR) measures, 63 had a benchmark, of which 44.4% were topped out. The percent of measures topped out also varied significantly (P < .001) by specialty, ranging from 0.0% (electrophysiology) to 95.0% (diagnostic radiology). Among 20 unique measure-and-collection-type combinations for diagnostic radiology, only one was not topped out, and 30.0% were capped. Among 20 radiology QCDR measures, 5 had a benchmark, of which 3 were topped out. CONCLUSION: CMS topped out measure scoring and removal policies disproportionately impact radiology, which has the highest topped out percentage among all specialties and only a single non-topped out measure. This asymmetry disproportionately impairs radiologists' MIPS flexibility and is anticipated to progress in ensuing years. Current CMS policies create a looming crisis for radiologists in MIPS. The high risk of an insufficient number of available quality measures creates an urgent need for new radiology measure development.
PURPOSE: CMS implemented Merit-Based Incentive Payment System (MIPS) policies to cap points and remove "topped out" quality measures having extremely high national performance. We assess such policies' impact on quality measure reporting, focusing on diagnostic radiology. METHODS: Data regarding MIPS 2019 quality measures were extracted from the CMS Quality Benchmarks File and the Quality Payment Program Explore Measures search tool and summarized by collection type and specialty. RESULTS: Among 348 MIPS measure-and-collection-type combinations, 40.5% were topped out (56.6% of those with a benchmark) and 23.3% were capped. Among measures with a benchmark, the percent topped out varied (P < .001) by collection type: claims 82.7%, qualified registry 60.4%, electronic health record 11.6%. The percent capped was also greatest for claims measures (52.3%). Among 699 Qualified Clinical Data Registry (QCDR) measures, 63 had a benchmark, of which 44.4% were topped out. The percent of measures topped out also varied significantly (P < .001) by specialty, ranging from 0.0% (electrophysiology) to 95.0% (diagnostic radiology). Among 20 unique measure-and-collection-type combinations for diagnostic radiology, only one was not topped out, and 30.0% were capped. Among 20 radiology QCDR measures, 5 had a benchmark, of which 3 were topped out. CONCLUSION: CMS topped out measure scoring and removal policies disproportionately impact radiology, which has the highest topped out percentage among all specialties and only a single non-topped out measure. This asymmetry disproportionately impairs radiologists' MIPS flexibility and is anticipated to progress in ensuing years. Current CMS policies create a looming crisis for radiologists in MIPS. The high risk of an insufficient number of available quality measures creates an urgent need for new radiology measure development.
Authors: Cameron J Gettel; Christopher R Han; Michael A Granovsky; Carl T Berdahl; Keith E Kocher; Abhishek Mehrotra; Jeremiah D Schuur; Amer Z Aldeen; Richard T Griffey; Arjun K Venkatesh Journal: Acad Emerg Med Date: 2021-09-07 Impact factor: 3.451
Authors: Cameron J Gettel; Christopher R Han; Maureen E Canavan; Susannah M Bernheim; Elizabeth E Drye; Reena Duseja; Arjun K Venkatesh Journal: Med Care Date: 2022-02-01 Impact factor: 2.983