Prevalence of "One-Off Events" in Radiology: Implications for Radiology in Episode-Based Alternative Payment Models.

OBJECTIVE: As reimbursement mechanisms become more value-based, there are questions about the applicability of these mechanisms for nonepisodic care, particularly care provided by nonpatient-facing specialists, for example, radiologists. Accordingly, this study examined the prevalence of nonepisodic care-one-off events-in diagnostic radiology. METHODS: We conducted a multiyear (2015-2019) retrospective study of diagnostic imaging using a large commercial payer database including commercial insurance and Medicare Advantage. Using a 12-month evaluation period starting with the day of the initial imaging study/studies, we categorized imaging studies as one-off events if there were no additional studies (beyond the first day of the evaluation period) for the next 12 months in the same body region. We also evaluated an alternative, more stringent definition of a one-off event: the only imaging study during the 12-month evaluation period. We computed the percentage of one-off events overall and by body region. RESULTS: We found that one-off events comprised 33.2%-45.8% of imaging studies depending on whether one-off events are defined as the only study in the evaluation period or imaging only on the first day of the evaluation period, respectively. This share varied widely by body region: highest for cardiac (80.9%-87.7%) and lower for chest (26.8%-35.2%). By place-of-service, the proportion was lowest for the inpatient (12.9%-29.1%) and long-term care settings (18.6%-30%). DISCUSSION: Given the sizeable share of imaging studies categorized as one-off events, much of radiologists' workload falls outside of the framework of episodic measurement tools and value-based payment models.

Budget Neutrality and Medicare Physician Fee Schedule Reimbursement Trends for Radiologists, 2005 to 2021.

PURPOSE: The Medicare program, by law, must remain budget neutral. Increases in volume or relative value units (RVUs) for individual services necessitate declines in either the conversion factor or assigned RVUs for other services for budget neutrality. This study aimed to assess the contribution of budget neutrality on reimbursement trends per Medicare fee-for-service beneficiary for services provided by radiologists. METHODS: The study used aggregated 100% of Medicare Part B claims from 2005 to 2021. We computed the percentage change in reimbursement per beneficiary, actual and inflation adjusted, to radiologists. These trends were then adjusted by separately holding constant RVUs per beneficiary and the conversion factor to demonstrate the impact of budget neutrality. RESULTS: Unadjusted reimbursement to radiologists per beneficiary increased 4.2% between 2005 and 2021, but when adjusted for inflation, it declined 24.9%. Over this period, the conversion factor declined 7.9%. Without this decline, the reimbursement per beneficiary would have been 9 percentage points higher in 2021 compared with actual. RVUs per beneficiary performed by radiologists increased 13.1%. Keeping RVUs per beneficiary at 2005 levels, reimbursement per beneficiary would have been 12.1 percentage points lower than observed in 2021. CONCLUSIONS: Given budget neutrality, a substantial decline has occurred in inflation-adjusted reimbursement to radiologists per Medicare beneficiary. Decreases due to both inflation and the decline in conversion factor are only partially offset by increased RVUs per beneficiary, meaning more services per patient with less overall pay, an equation likely to heighten access challenges for Medicare beneficiaries and shortages of radiologists.

Opportunistic Screening: Radiology Scientific Expert Panel.

Radiologic tests often contain rich imaging data not relevant to the clinical indication. Opportunistic screening refers to the practice of systematically leveraging these incidental imaging findings. Although opportunistic screening can apply to imaging modalities such as conventional radiography, US, and MRI, most attention to date has focused on body CT by using artificial intelligence (AI)-assisted methods. Body CT represents an ideal high-volume modality whereby a quantitative assessment of tissue composition (eg, bone, muscle, fat, and vascular calcium) can provide valuable risk stratification and help detect unsuspected presymptomatic disease. The emergence of "explainable" AI algorithms that fully automate these measurements could eventually lead to their routine clinical use. Potential barriers to widespread implementation of opportunistic CT screening include the need for buy-in from radiologists, referring providers, and patients. Standardization of acquiring and reporting measures is needed, in addition to expanded normative data according to age, sex, and race and ethnicity. Regulatory and reimbursement hurdles are not insurmountable but pose substantial challenges to commercialization and clinical use. Through demonstration of improved population health outcomes and cost-effectiveness, these opportunistic CT-based measures should be attractive to both payers and health care systems as value-based reimbursement models mature. If highly successful, opportunistic screening could eventually justify a practice of standalone "intended" CT screening.

White Paper: Best Practices in the Communication and Management of Actionable Incidental Findings in Emergency Department Imaging.

PURPOSE: Actionable incidental findings (AIFs) are common in radiologic imaging. Imaging is commonly performed in emergency department (ED) visits, and AIFs are frequently encountered, but the ED presents unique challenges for communication and follow-up of these findings. The authors formed a multidisciplinary panel to seek consensus regarding best practices in the reporting, communication, and follow-up of AIFs on ED imaging tests. METHODS: A 15-member panel was formed, nominated by the ACR and American College of Emergency Physicians, to represent radiologists, emergency physicians, patients, and those involved in health care systems and quality. A modified Delphi process was used to identify areas of best practice and seek consensus. The panel identified four areas: (1) report elements and structure, (2) communication of findings with patients, (3) communication of findings with clinicians, and (4) follow-up and tracking systems. A survey was constructed to seek consensus and was anonymously administered in two rounds, with a priori agreement requiring at least 80% consensus. Discussion occurred after the first round, with readministration of questions where consensus was not initially achieved. RESULTS: Consensus was reached in the four areas identified. There was particularly strong consensus that AIFs represent a system-level issue, with need for approaches that do not depend on individual clinicians or patients to ensure communication and completion of recommended follow-up. CONCLUSIONS: This multidisciplinary collaboration represents consensus results on best practices regarding the reporting and communication of AIFs in the ED setting.

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.

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.

ACR Statement on Safe Resumption of Routine Radiology Care During the Coronavirus Disease 2019 (COVID-19) Pandemic.

The ACR recognizes that radiology practices are grappling with when and how to safely resume routine radiology care during the coronavirus disease 2019 (COVID-19) pandemic. Although it is unclear how long the pandemic will last, it may persist for many months. Throughout this time, it will be important to perform safe, comprehensive, and effective care for patients with and patients without COVID-19, recognizing that asymptomatic transmission is common with this disease. Local idiosyncrasies prevent a single prescriptive strategy. However, general considerations can be applied to most practice environments. A comprehensive strategy will include consideration of local COVID-19 statistics; availability of personal protective equipment; local, state, and federal government mandates; institutional regulatory guidance; local safety measures; health care worker availability; patient and health care worker risk factors; factors specific to the indication(s) for radiology care; and examination or procedure acuity. An accurate risk-benefit analysis of postponing versus performing a given routine radiology examination or procedure often is not possible because of many unknown and complex factors. However, this is the overriding principle: If the risk of illness or death to a health care worker or patient from health care-acquired COVID-19 is greater than the risk of illness or death from delaying radiology care, the care should be delayed; however, if the opposite is true, the radiology care should proceed in a timely fashion.

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.

Determining the Patient Complexity of Head CT Examinations: Implications for Proper Valuation of a Critical Imaging Service.

PURPOSE: The head-computed tomography (CT) exam code was recently identified by policy makers as having a potentially overvalued resource value units (RVU). A critical aspect in determining RVUs is the complexity of patients undergoing the service. This study evaluated the complexity of patients undergoing head-CT. METHODS: The 2017 Medicare PSPS Master File was used to identify the most common site for performing head-CT examinations. Given the most common location, the 5% Research Identifiable File, was then used to evaluate complexity of patients undergoing head CT on the same day as an emergency department (ED) visit based on the Evaluation & Management (E&M) "level" of these visits (1-least complex to 5-most complex patient) and the ICD-10 diagnosis coding associated with the billed head CT claims. RESULTS: 56.1% of head CT examinations were performed in the ED. Seventy percent of noncontrast exams performed in the ED were ordered in the most complex patient encounters (level 5 E&M visits). The most common ICD-10 code for head-CT without intravenous contrast billed with a level 5 E&M visit was "dizziness and giddiness," and for head-CT without and with intravenous contrast was "headache." CONCLUSION: Head-CT is not only most frequently ordered in the ED, but also during the most complex ED visits, suggesting that the ICD-10 codes associated with such exams do not appropriately reflects patient complexity. The valuation process should also consider the complexity of associated billed patient encounters, as indicated by E&M visit levels.

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.

Radiologist Group Performance Reporting: Power in Numbers.

PURPOSE: Radiologists have historically participated as individuals in CMS pay-for-performance programs, but little is known about how radiologists perform under increasingly available group participation. We aimed to assess radiologists' relative national performance on CMS quality metrics using group versus individual participation. METHODS: Radiologists' group- and individual-level 2016 performance on Physician Quality Reporting System (PQRS) and non-PQRS Qualified Clinical Data Registry (QCDR) measures were obtained from the CMS national Physician Compare database and compared. RESULTS: Radiology groups reported an average 4.6 ± 2.0 quality measures; individual radiologists reported 2.3 ± 1.2 (P < .001). At least six measures were reported by 31.5% of groups versus 1.0% of individuals. Only one measure was reported by 5.4% of groups versus 33.0% of individuals. Groups reported 21 unique measures (20 via registries and one via QCDR). For 8 of the 11 measures reported by 20 or more groups, the average group performance rate was 3% or better than the average performance rate among radiologists participating as individuals (maximum 14% improvement with group participation versus individual participation for any individual measure). Group and individual performance were similar for the remaining three such measures. For measures reported by 20 or more groups in which a higher score indicates better performance, average group performance rates ranged from 86.2% to 98.9%. CONCLUSION: Compared with individual participation in CMS quality performance programs, radiologists participating as a group reported larger numbers of quality measures and achieved higher performance rates on those measures. Radiology practices seeking success under Medicare's new Quality Payment Program should carefully explore group participation.