In 2020, the largest U.S. health care payer, the Centers for Medicare & Medicaid Services (CMS), established payment for artificial intelligence (AI) through two different systems in the Medicare Physician Fee Schedule (MPFS) and the Inpatient Prospective Payment System (IPPS).
View Article and Find Full Text PDFPurpose: The aim of this study was to temporally characterize radiologist participation in Medicare Shared Savings Program (MSSP) accountable care organizations (ACOs).
Methods: Using CMS Physician and Other Supplier Public Use Files, ACO provider-level Research Identifiable Files, and Shared Savings Program ACO Public-Use Files for 2013 through 2018, characteristics of radiologist ACO participation were assessed over time.
Results: Between 2013 and 2018, the percentage of Medicare-participating radiologists affiliated with MSSP ACOs increased from 10.
Curr Probl Diagn Radiol
April 2021
Clinical Decision Support (CDS) was designed as 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. Policymakers recognized AUC as a potential solution to control inappropriate utilization of imaging and made CDS mandatory in the Protecting Access to Medicare Act of 2014. In the years since Protecting Access to Medicare Act, data on the potential impact of CDS has been mixed and much of the physician community has expressed concern about the logistics of the program.
View Article and Find Full Text PDFPurpose: 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.
For data science tools to mature and become integrated into routine clinical practice, they must add value to patient care by improving quality without increasing cost, by reducing cost without changing quality, or by both reducing cost and improving quality. Artificial intelligence (AI) algorithms have potential to augment data-driven quality improvement for radiologists. If AI tools are adopted with population health goals in mind, the structure of value-based payment models will serve as a framework for reimbursement of AI that does not exist in the fee-for-service system.
View Article and Find Full Text PDFThe purpose of this study was to assess the percentage and characteristics of radiologists who meet criteria for facility-based measurement in the Merit-Based Incentive Payment System (MIPS). The Provider Utilization and Payment Data: Physician and Other Supplier Public Use File was used to identify radiologists who bill 75% or more of their Medicare Part B claims in the facility setting. Among 31,217 included radiologists nationwide, 71.
View Article and Find Full Text PDFBreast imaging radiologists are considered by many to be leaders among diagnostic radiologists in the transition to value-based care. Many strategies for success in the changing healthcare landscape are exemplified by the day-to-day practice of breast imaging, including well-developed quality measures, standardized accepted best practices and terminology, and a prominent role in communicating with patients and coordinating care. Further development of these strategies will be important for continued success in both the Merit-Based Incentive Payment System and in alternative payment models.
View Article and Find Full Text PDFThe Medicare and CHIP Reauthorization Act of 2015 remains the payment policy law of the land. 2017 was the first year in which performance reporting will tangibly impact future physician payments. The Centers for Medicare & Medicaid Services (CMS) considers 2017 and 2018 transitional years before full implementation in 2019.
View Article and Find Full Text PDFAJR Am J Roentgenol
April 2008
Objective: Infection at time of MR contrast administration has been reported to predispose patients with renal failure to development of nephrogenic systemic fibrosis (NSF). We assessed the frequency of infection at the time of MR contrast administration in a group of NSF patients.
Materials And Methods: Eight patients developed NSF during 2002-2006, of whom seven received the MR contrast agent gadodiamide (Omniscan), with doses of 0.