An Overview of the Radiation Oncology Alternative Payment Model and Impact on Practices Serving Vulnerable Populations.

Radiation oncology reimbursement methodology has been largely unchanged over the past 30 years, and new approaches are of great interest to practicing radiation oncologists and other health care stakeholders. Traditional radiation oncology reimbursement is based on a series of individual codes for evaluation and management (professional) and technical services, yielding a complex reimbursement system. In an attempt to move toward a simpler, episodic payment model, bundling all of the codes into a single payment, an alternative payment model for radiation oncology was developed. The radiation oncology alternative payment model is a revolutionary change in how radiation oncologic services will be reimbursed and has potential to affect all aspects of radiation oncologic care. Here, the authors review the origin of the currently proposed radiation oncology model and discuss potential implications of this model on the provision of care, especially as it relates to rural practices and other underserved and vulnerable patient populations.

The Economic Impact of AI on Breast Imaging.

This article explores the development of computer-aided detection (CAD) and artificial or augmented intelligence (AI) for breast radiology examinations and describes the current applications of AI in breast imaging. Although radiologists in other subspecialties may be less familiar with the use of these technologies in their practices, CAD has been used in breast imaging for more than two decades, as mammography CAD programs have been commercially available in the United States since the late 1990s. Likewise, breast radiologists have seen payment for CAD in mammography and breast MRI evolve over time. With the rapid expansion of AI products in radiology in recent years, many new applications for these technologies in breast imaging have emerged. This article outlines the current state of reimbursement for breast radiology AI algorithms within the traditional fee-for-service model used by Medicare and commercial insurers as well as potential future payment pathways. In addition, the inherent challenges of employing the existing payment framework in the United States to AI programs in radiology are detailed for the reader. This article aims to give breast radiologists a better understanding of how AI will be reimbursed as they seek to further incorporate these emerging technologies into their practices to advance patient care and improve workflow efficiency.

Who Will Pay for AI?

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). Within the MPFS, a new Current Procedural Terminology code was valued for an AI tool for diagnosis of diabetic retinopathy, IDx-RX. In the IPPS, Medicare established a New Technology Add-on Payment for Viz.ai software, an AI algorithm that facilitates diagnosis and treatment of large-vessel occlusion strokes. This article describes reimbursement in these two payment systems and proposes future payment pathways for AI. Keywords: Computer Applications-General (Informatics), Technology Assessment © RSNA, 2021.

Evolving Radiologist Participation in Medicare Shared Savings Program Accountable Care Organizations.

PURPOSE: 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 10.4% to 34.9%. During that time, the share of large ACOs (>20,000 beneficiaries) with participating radiologists averaged 87.0%, and the shares of medium ACOs (10,000-20,000) and small ACOs (<10,000) with participating radiologists rose from 62.5% to 66.0% and from 26.3% to 51.6%, respectively. The number of physicians in MSSP ACOs with radiologists was substantially larger than those without radiologists (mean range across years, 573-945 versus 107-179). Primary care physicians constituted a larger percentage of the physician population for ACOs without radiologists (average across years, 66.3% versus 38.5%), and ACOs with radiologists had a higher rate of specialist representation (56.0% versus 33.7%). Beneficiary age, race, and sex demographics were similar among radiologist-participating versus nonparticipating ACOs. CONCLUSIONS: In recent years, radiologist participation in MSSP ACOs has increased substantially. ACOs with radiologist participation are large and more diverse in their physician specialty composition. Nonparticipating radiologists should prepare accordingly.

Mapping the Ultrasound Landscape to Define Point-of-Care Ultrasound and Diagnostic Ultrasound: A Proposal From the Society of Radiologists in Ultrasound and ACR Commission on Ultrasound.

Current descriptions of ultrasound evaluations, including use of the term "point-of-care ultrasound" (POCUS), are imprecise because they are predicated on distinctions based on the device used to obtain images, the location where the images were obtained, the provider who obtained the images, or the focus of the examination. This is confusing because it does not account for more meaningful distinctions based on the setting, comprehensiveness, and completeness of the evaluation. In this article, the Society of Radiologists in Ultrasound and the members of the American College of Radiology Ultrasound Commission articulate a map of the ultrasound landscape that divides sonographic evaluations into four distinct categories on the basis of setting, comprehensiveness, and completeness. Details of this classification scheme are elaborated, including important clarifications regarding what ensures comprehensiveness and completeness. Practical implications of this framework for future research and reimbursement paradigms are highlighted.

Breast Imaging Radiologists' Role in Value Pathways.

The Merit-Based Incentive Payment System (MIPS) has fallen short of its intended goal to substantially transform the delivery of healthcare by tying clinician payments to quality and cost reduction. Policy makers made changes to the program over its first five years in efforts to address concerns about complexity and lack of meaningful impact on outcomes for our patients. One of these changes, the creation of MIPS Value Pathways (MVPs), aims to streamline reporting of increasingly aligned measures and serve as a stepping-stone for the transition to alternative payment models. As MIPS continues to evolve, these value pathways will provide new opportunities for breast imaging radiologists to participate in value-based care.

Characteristics of COVID-19 Community Practice Declines in Noninvasive Diagnostic Imaging Professional Work.

PURPOSE: The operational and financial impact of the widespread coronavirus disease 2019 (COVID-19) curtailment of imaging services on radiology practices is unknown. We aimed to characterize recent COVID-19-related community practice noninvasive diagnostic imaging professional work declines. METHODS: Using imaging metadata from nine community radiology practices across the United States between January 2019 and May 2020, we mapped work relative value unit (wRVU)-weighted stand-alone noninvasive diagnostic imaging service codes to both modality and body region. Weekly 2020 versus 2019 wRVU changes were analyzed by modality, body region, and site of service. Practice share χ2 testing was performed. RESULTS: Aggregate weekly wRVUs ranged from a high of 120,450 (February 2020) to a low of 55,188 (April 2020). During that -52% wRVU nadir, outpatient declines were greatest (-66%). All practices followed similar aggregate trends in the distribution of wRVUs between each 2020 versus 2019 week (P = .96-.98). As a percentage of total all-practice wRVUs, declines in CT (20,046 of 63,992; 31%) and radiography and fluoroscopy (19,196; 30%) were greatest. By body region, declines in abdomen and pelvis (16,203; 25%) and breast (12,032; 19%) imaging were greatest. Mammography (-17%) and abdominal and pelvic CT (-14%) accounted for the largest shares of total all-practice wRVU reductions. Across modality-region groups, declines were far greatest for mammography (-92%). CONCLUSIONS: Substantial COVID-19-related diagnostic imaging work declines were similar across community practices and disproportionately impacted mammography. Decline patterns could facilitate pandemic second wave planning. Overall implications for practice workflows, practice finances, patient access, and payment policy are manifold.

Clinical Decision Support: The Law, the Future, and the Role for Radiologists.

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. This article aims to review the legislation behind the AUC program, the events that have transpired since, and some of the challenges and opportunities facing radiologists in the current environment.

The Quality Measure Crunch: How CMS Topped Out Scoring and Removal Policies Disproportionately Disadvantage Radiologists.

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.

The Alternative Payment Model Pathway to Radiologists' Success in the Merit-Based Incentive Payment System.

PURPOSE: To assess radiologists' performance in the Merit-Based Incentive Payment System (MIPS), with attention to the impact of the novel MIPS-Alternative Payment Models (APMs) participation option created under the Medicare Access and CHIP Reauthorization Act. METHODS: Data regarding radiologists' 2017 MIPS performance was extracted from the Physician Compare 2017 Individual EC Public Reporting-overall MIPS Performance data set, and additional physician characteristics were extracted from multiple CMS data sets. RESULTS: Among 20,956 MIPS-participating radiologists, 16.6% participated using individual reporting, 68.9% group reporting, and 13.4% APM reporting. Average Quality scores were 59.7 84.0, and 92.5, respectively. The fractions of radiologists scored in Advancing Care Information were 4.1%, 27.0%, and 100.0%. When scored, average scores in this category were 61.9, 94.6, and 80.9. A total of 27.7% and 42.7% of interventional radiologists were scored in this category using individual and group reporting, respectively. However, general radiologists and subspecialists other than interventional radiologists were rarely (<5%) scored. Average scores in Improvement Activities were 37.5, 92.5, and 100.0 for individual reporting, group reporting, and APM reporting, respectively. Average Final Scores were 56.5, 85.6, and 90.6. The better performance of APM versus group reporting was most apparent for smaller practices (ie, for practice sizes ≤15, average Final Score of 84.1 for APM versus 75.0 for group reporting). CONCLUSION: Although radiologists perform much better in MIPS using group versus individual reporting, performance improves even further through APM reporting, particularly for smaller practices. Radiologists seeking better performance under MIPS should carefully explore APM opportunities.

A Business Case for Artificial Intelligence Tools: The Currency of Improved Quality and Reduced Cost.

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.

Facility-Based Measurement in the Merit-Based Incentive Payment System: A Potential Safety Net for Which Most Radiologists Will Be Eligible.

OBJECTIVE. The 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). MATERIALS AND METHODS. 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. RESULTS. Among 31,217 included radiologists nationwide, 71.0% met the eligibility criteria for facility-based measurement as individuals in MIPS. The percentage of predicted eligibility was slightly higher for male than female radiologists (72.9% vs 64.5%). The percentage decreased slightly with increasing years in practice (from 78.8% for radiologists with < 10 years in practice to 67.3% for radiologists with ≥ 25 years in practice). The eligibility percentage was also higher for radiologists in rural as opposed to urban practices (81.6% vs 71.3%) and in academic as opposed to nonacademic practices (77.2% vs 70.3%). However, the percentages were similar across practices of varying sizes. There was also a greater degree of heterogeneity by state, ranging from 50.9% in Minnesota to 94.0% in West Virginia. By overall geographic region, the percentage of predicted eligibility was lowest in the Northeast (64.7%) and highest in the Midwest (78.3%). A higher percentage of generalists met the 75% facility-based threshold than did subspecialists (77.3% vs 65.4%). When stratified by subspecialty, however, facility-based eligibility was lowest for musculoskeletal radiologists (38.1%) and breast imagers (45.1%) and highest for cardiothoracic radiologists (85.1%). For other subspecialties, predicted eligibility ranged from 66.0% to 77.8%. CONCLUSION. Most radiologists will be eligible for facility-based reporting for MIPS in 2019, with some variation by demographic and specialty characteristics. The facility-based option provides a safety net for radiologists who face challenges accessing hospital data for reporting quality measures. In general, radiologists should not alter their current MIPS strategy but should instead consider facility-based measurement as a contingency plan that could result in a higher final score.

Digital Breast Tomosynthesis Implementation: Considerations for Emerging Breast Cancer Screening Bundled Payment Models.

PURPOSE: Bundled payments have been touted as mechanisms to optimize quality and costs. A recent feasibility study evaluating bundled payments for screening mammography episodes predated widespread adoption of digital breast tomosynthesis (DBT). We explore a similar model reflecting emerging acceptance of DBT in breast cancer screening. METHODS: Using 4-year data for 59,094 screening episodes from two large facilities within a large academic health system, we utilized published methodology to calibrate Medicare national allowable reference prices for women undergoing screening mammography before and after practice-wide implementation of DBT. RESULTS: Excluding DBT, Medicare-normalized bundled prices for traditional breast imaging 364 days downstream to screening mammography are extremely similar pre- and post-DBT implementation ($182.86 in 2013; $182.68 in 2015). The addition of DBT increased a DBT-inclusive bundled price by $53.16 (an amount lower than the $56.13 Medicare allowable fee for screening DBT) but was associated with significantly reduced recall rates (13.0% versus 9.4%; P < .0001). Without or with DBT, screening episode bundled prices remained sensitive to bundle-included services and varied little by patient age, race, or insurance status. CONCLUSIONS: Prior non-DBT approaches to bundled payment models for breast cancer screening remain viable as DBT becomes the standard of care, with bundle prices varying little by patient age, race, or insurance status. Higher DBT-inclusive bundled prices, however, highlight the need to explore societal costs more broadly (eg, reduced time away from work from fewer recalls) as bundled payment models evolve.

Medicare Access and Children's Health Insurance Program Reauthorization Act: The Basics for the Breast Imaging Radiologist.

Breast 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.

MACRA 2.5: the legislation moves forward.

The 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. As such, 2018 increases the reporting requirements over 2017 in the form of a gradual phase-in while introducing several key changes and new elements. Indeed, it is the nature of the transition itself that led to the somewhat unique title of this manuscript, i.e., MACRA 2.5. Stakeholder feedback to the CMS regarding the program has ranged widely from the elimination of core components to expanding reporting to non-government payers. This article explores the potential impact on neurointerventional physicians.