Association between Heat Vulnerability Index and Stroke Severity.

BACKGROUND: Socioeconomically disadvantaged neighborhoods are particularly vulnerable to heat-related illnesses. We aim to investigate the association between the heat vulnerability index (HVI), an established neighborhood-level metric of heat-related mortality risk, and acute ischemic stroke (AIS) severity. METHODS: We conducted a retrospective analysis of consecutive AIS admissions to a comprehensive stroke center between 2012 and 2021. Stroke severity was defined upon admission based on the National Institutes of Health Stroke Scale (NIHSS). Demographic, socioeconomic, and clinical characteristics were extracted from electronic health records. HVI status was assigned using residential ZIP codes. Multivariable logistic regression analyses were performed. RESULTS: Of 3429 AIS admissions, 1123 (32.8%) were from high-HVI (scores 4-5) neighborhoods and 868 (25.3%) had severe stroke (NIHSS score ≥ 10). In the multivariable regression model with stepwise selection, a high HVI was independently associated with severe stroke (adjusted odds ratio: 1.40 [95% confidence interval 1.16-1.69]). CONCLUSIONS: The association between a high HVI and severe stroke underscores the importance of targeting policy interventions to mitigate heat-related illness in socioeconomically disadvantaged neighborhoods.

Differential Access to Breast Magnetic Resonance Imaging Compared with Mammography and Ultrasound.

INTRODUCTION: For high-risk women, breast magnetic resonance (MR) is the preferred supplemental imaging option, but spatial access differences may exacerbate disparities in breast care. METHODS: This was a cross-sectional study examining distance between ZIP codes and the nearest breast imaging facility (MR, mammography, ultrasound) using 2023 data from the Food and Drug Administration and the American College of Radiology. Linear regression was used to assess distance differences controlling for Area Deprivation Index (ADI), urbanicity, and population size. Analyses were conducted in 2024. RESULTS: Among the 29,629 ZIP codes with an ADI and known urbanicity, unadjusted mean distance to breast MR was 23.2±25.1 miles (SD) compared with 8.2±8.3 for mammography and 22.2±25.0 for ultrasound. Hence, the average distance to breast MR facilities was 2.8 times further than to mammography facilities. ADI and urbanicity were associated with increased distance to the nearest breast imaging facility. The additional miles associated with the least advantaged areas compared with most advantaged areas was 12.2 (95%CI: 11.3, 13.2) for MR, 11.5 miles (95%CI: 10.6, 12.3) for ultrasound, and 2.4 (95%CI: 2.1, 2.7) for mammography. Compared with metropolitan areas, the additional miles to breast MR facilities was 23.2 (95%CI: 22.5, 24.0) for small/rural areas. CONCLUSIONS: Spatial access is substantially better for mammography sites compared with breast MR or ultrasound sites. Given these findings, consideration of options to mitigate the impact of differential access should be considered. For example, mammography sites could offer contrast-enhanced mammography. Future research should examine the feasibility and effectiveness of this and other options.

Caught Between a Radiation Oncology Case Rate (ROCR) and a Hard Place: Improving Proposed Radiation Oncology Alternative Payment Models.

PURPOSE: The Radiation Oncology Case Rate (ROCR) aims to shift radiation reimbursement from fee-for-service (FFS) to bundled payments, which would decouple fractionation from reimbursement in the United States. This study compares historical reimbursement rates from 3 large centers and a national Medicare sample with proposed base rates from ROCR. It also tests the impact of methodological inclusion of treatment and disease characteristics to determine if any variables are associated with greater rate differences that may lead to inequitable reimbursement. METHODS AND MATERIALS: Using Mayo Clinic electronic medical record data from 2017 to 2020 and part B claims from the Medicare 5% research identifiable files, episodic 90-day historical reimbursement rates for 15 cancer types were calculated per the ROCR payment methodology. Mayo Clinic reimbursement rates were stratified by disease and treatment characteristics and multiple linear regression was performed to assess the association of these variables on historical episode reimbursement rates. RESULTS: From Mayo Clinic, 3498 patient episodes were included and 480,526 from the research identifiable files. From both data sets, 25% of brain metastases and 13% of bone metastases episodes included ≥2 treatment courses with an average of 51 days between courses. Accounting for all 15 cancer types, ROCR base rates resulted in an average -2.4% and -2.9% reduction in rates for Mayo Clinic and the research identifiable files respectively compared with historical reimbursement. On multivariate analysis of Mayo Clinic data, treatment intent (curative vs palliative) was associated with higher historical reimbursement (+$477 to +$7417; P ≤.05) for 12 out of 12 applicable cancer types. Stage (III-IV vs I-II) was associated with higher historical reimbursement (+$1169 to +$3917; P ≤ .05) for 8 out of 12 applicable cancer types. CONCLUSIONS: Our data suggest ROCR base rates introduce an average ≤3% reimbursement rate decrease compared with historical FFS reimbursement per cancer type, which could produce the Medicare savings required for congressional approval of ROCR. Estimating comparisons with future FFS reimbursement would require consideration of additional factors such as the increased utilization of hypofractionation, proposed FFS rate cuts, and inflationary updates. A distinct rate and shortened episode duration (≤30 days) should be considered for palliative episodes. Applying a base rate modifier per cancer stage may mitigate disproportionate reductions in reimbursement for facilities with a higher volume of curative advanced-stage patients such as freestanding centers in rural settings.

Changes in the Radiology Practice Landscape and Indicators of Practice Consolidation From 2014 to 2023.

BACKGROUND. A range of economic and health policy incentives are leading to ongoing consolidation among payers, hospitals, and physician practices. OBJECTIVE. The purpose of the present study was to evaluate consolidation among radiologists' affiliated practices through 2023, analyze the impact of consolidation on such practices' specialty mix and size, and assess radiologists' new affiliations after prior practices cease. METHODS. CMS data from 2014 to 2023 were used to identify all radiologists nationally along with their affiliated practices. Based on the specialty mix of all affiliated physicians, practices were categorized as radiology only or multispecialty; multispecialty practices were further categorized as radiology majority, other specialty majority, or no majority specialty. Practices that ceased (i.e., became absent within CMS data) were identified. Temporal shifts were assessed to infer consolidation patterns. RESULTS. From 2014 to 2023, the number of radiologists enrolled in Medicare increased 17.3% (from 30,723 to 36,024), whereas the number of affiliated practices decreased 14.7% (from 5059 to 4313). The number of radiology-only, radiology-majority, other-specialty-majority, and no-majority-specialty practices changed by -31.8% (from 3104 to 2118), 10.9% (from 402 to 446), -5.7% (from 615 to 580), and 24.6% (from 938 to 1169), respectively. The number of practices with one to two, three to nine, 10-24, 25-49, 50-99, and 100 or more radiologists changed by -18.7% (from 2233 to 1815), -34.4% (from 1406 to 923), -25.2% (from 910 to 681), 33.2% (from 352 to 469), 121.6% (from 125 to 277), and 348.5% (from 33 to 148). A total of 3494 practices ceased, including 2281 radiology-only practices. Among 3854 radiologists whose only affiliation was a ceased radiology-only practice, their subsequent-year affiliation was a radiology-only practice in 54.3% and a multispecialty practice type in the remaining instances. CONCLUSION. An overall decrease in the number of radiology practices and concurrent growth in the number of radiologists was mirrored by shifts from small toward large practices and from radiology-only toward multispecialty practices, consistent with ongoing practice consolidation. Although determining the causes of consolidation was beyond this scope of this study, the shifts may relate to economic incentives and legislative changes favoring large multispecialty practices. CLINICAL IMPACT. The continued consolidation of radiologists into large multispecialty practices may facilitate subspecialization and greater negotiating power in payer contracting. However, radiologists may prefer smaller and/or radiology-only practices for reasons of autonomy and influence on practice structure.

Share of Diagnostic Imaging Interpretation: Radiology and Other Specialties.

PURPOSE: The aim of this study was to examine radiology's and other specialties' market shares for diagnostic imaging interpretation for Medicare fee-for-service claims by modality, body region, and place of service. METHODS: In this cross-sectional study of Physician/Supplier Procedure Summary data for 2022, the authors examined the proportion of diagnostic imaging interpretation by specialty. All claims for CT, MR, nuclear medicine (NM), ultrasound, and radiography and fluoroscopy (XR) were included. Claims were aggregated into 52 specialty groups using Medicare specialty codes. The market share for each specialty group was computed by modality, body region, and place of service. RESULTS: For Medicare fee-for-service beneficiaries, there were 122,851,716 imaging studies, of which 88,559,272 (72.1%) were interpreted by radiologists. This percentage varied by modality: 97.3% for CT, 91.0% for MR, 76.6% for XR, 50.9% for NM, and 33.9% for ultrasound. Radiologists interpreted a lower percentage of cardiac (67.6% for CT, 42.2% for MR, 11.8% for NM, and 0.4% for ultrasound) than noncardiac studies (97.6% for CT, 91.4% for MR, 95.6% for NM, and 53.0% for ultrasound). Among noncardiac studies, radiologists interpreted nearly all in the outpatient hospital, inpatient, and emergency department (99.5% for CT, 99.4% for MR, 98.9% for NM, 79.3% for ultrasound, and 97.9% for XR) compared with the office setting (84.4% for CT, 78.7% for MR, 85.4% for NM, 29.2% for ultrasound, and 43.1% for XR). CONCLUSIONS: Radiologists perform the dominant share of CT and MR interpretation and more so for noncardiac imaging and imaging performed in outpatient hospital, inpatient, and emergency department places of service.

Decomposition of medical imaging spending growth between 2010 and 2021 in the US employer-insured population.

Medical imaging, identified as a potential driver of unsustainable US health care spending growth, was subject to policies to reduce prices and use in low-value settings. Meanwhile, the Affordable Care Act increased access to preventive services-many involving imaging-for employer-sponsored insurance (ESI) beneficiaries. We used a large insurance claims database to examine imaging spending trends in the ESI population between 2010 and 2021-a period of considerable policy and benefits changes. Nominal spending on imaging increased 35.9% between 2010 and 2021, but as a share of total health care spending fell from 10.5% to 8.9%. The 22.5% growth of nominal imaging prices was below inflation, 24.3%, as measured by the Consumer Price Index. Other key contributors to imaging spending growth were increased use (7.4 percentage points [pp]), shifts toward advanced modalities (4.0 pp), and demographic changes (3.5 pp). Shifts in care settings and provider network participation resulted in 2.5-pp and 0.3-pp imaging spending decreases, respectively. In sum, imaging spending decreased as a share of all health care spending and relative to inflation, as intended by concurrent cost-containment policies.

Radiologists' 2021 Quality Reporting and Performance in Medicare's Merit-Based Incentive Payment System: Analysis by Practice Type.

This study of national CMS data shows differences in quality reporting and performance of Merit-Based Incentive Payment System (MIPS)-participating radiologists by practice specialty mix. For certain practice types, radiologist-reported quality measures were commonly not radiology measures. The results support a need to expand radiology measures and to better align measure reporting with clinician specialty.

A Claims-Based Method for Identification and Characterization of Practicing Interventional Radiologists.

PURPOSE: To propose a research method for identifying "practicing interventional radiologists" using 2 national claims data sets. MATERIALS AND METHODS: The 2015-2019 100% Medicare Part B data and 2015-2019 private insurance claims from Optum's Clinformatics Data Mart (CDM) database were used to rank-order radiologists' interventional radiology (IR)-related work as a percentage of total billed work relative value units (RVUs). Characteristics were analyzed at various threshold percentages. External validation used Medicare self-designated specialty with Society of Interventional Radiology (SIR) membership records; Youden index evaluated sensitivity and specificity. Multivariate logistic regression assessed practicing IR characteristics. RESULTS: In the Medicare data, above a 10% IR-related work threshold, only 23.8% of selected practicing interventional radiologists were designated as interventional radiologists; above 50% and 90% thresholds, this percentage increased to 42.0% and 47.5%, respectively. The mean percentage of IR-related work among practicing interventional radiologists was 45%, 84%, and 96% of total work RVUs for the 10%, 50%, and 90% thresholds, respectively. At these thresholds, the CDM practicing interventional radiologists included 21.2%, 35.2%, and 38.4% designated interventional radiologists, and evaluation and management services comprised relatively more total work RVUs. Practicing interventional radiologists were more likely to be males, metropolitan, and earlier in their careers than other radiologists at all thresholds. CONCLUSIONS: Most radiologists performing IR-related work are designated in claims data as diagnostic radiologists, indicating insufficiency of specialty designation for IR identification. The proposed method to identify practicing interventional radiologists by percent IR-related work effort could improve generalizability and comparability across claims-based IR studies.

Financial Viability of the No Surprises Act Independent Dispute Resolution Process: Radiology and Other Hospital-Based Specialties.

BACKGROUND. The federal No Surprises Act (NSA), designed to eliminate surprise medical billing for out-of-network (OON) care for circumstances beyond patients' control, established the independent dispute resolution (IDR) process to settle clinician-payer payment disputes for OON care. OBJECTIVE. The purpose of our study was to assess the fraction of OON claims for which radiologists and other hospital-based specialists can expect to at least break even when challenging payer-determined payments through the NSA IDR process, as a measure of the process's financial viability. METHODS. This retrospective study extracted claims from a national commercial database (Optum's deidentified Clinformatics Data Mart) for hospital-based specialties occurring on the same day as in-network emergency department (ED) visits or inpatient stays from January 2017 to December 2021. OON claims were identified. OON claims batching was simulated using IDR rules. Maximum potential recovered payments from the IDR process were estimated as the difference between the charges and the allowed amount. The percentages of claims for which the maximum potential payment and one-quarter of this amount (a more realistic payment recovery estimate) would exceed IDR fees were determined, using US$150 and US$450 fee thresholds to approximate the range of final 2024 IDR fees. These values represented the percentage of OON claims that would be financially viable candidates for IDR submission. RESULTS. Among 76,221,264 claims for hospital-based specialties associated with in-network ED visits or inpatient stays, 1,482,973 (1.9%) were OON. The maximum potential payment exceeded fee thresholds of US$150 and US$450 for 55.0% and 32.1%, respectively, of batched OON claims for radiologists and 76.8% and 61.3% of batched OON claims for all other hospital-based specialties combined. At payment of one-quarter of that amount, these values were 26.9% and 10.6%, respectively, for radiologists and 56.6% and 38.4% for all other hospital-based specialties combined. CONCLUSION. The IDR process would be financially unviable for a substantial fraction of OON claims for hospital-based specialists (more so for radiology than for other such specialties). CLINICAL IMPACT. Although the NSA enacted important patient protections, IDR fees limit clinicians' opportunities to dispute payer-determined payments and potentially undermine their bargaining power in contract negotiations. Therefore, IDR rulemaking may negatively impact patient access to in-network care.

Radiologists' Out-of-Network Billing Trends, 2007 to 2021.

PURPOSE: Given the financial hardships of surprise billing for patients, the aim of this study was to assess the degree to which radiologists effectively participate in commercial insurance networks by examining the trend in the share of radiologists' imaging claims that are out of network (OON). METHODS: A retrospective study over a 15-year period (2007-2021) was conducted using claims from Optum's deidentified Clinformatics Data Mart Database to assess the share of radiologists' imaging claims that are OON. Radiologists' annual OON rate was assessed overall as well as for claims associated with inpatient stays and emergency department (ED) visits. Rates were assessed for all imaging studies as well as by modality. Linear regression was conducted to assess OON rate time trends. RESULTS: From 2007 to 2021, 5,039,142 of radiologists' imaging claims (6.3%) were OON. This rate declined from 12.6% in 2007 to 1.1% in 2021. Over the study period, the OON rate was 5.0% during an inpatient stay and 2.1% on the same day as an ED visit that did not lead to an inpatient admission. The linear trend in the overall OON rate declined 0.74 percentage points annually (95% confidence interval [CI], -0.90 to -0.58 percentage points) over the study period. Likewise, the annual declines were 0.54 percentage points (95% CI, -0.71 to -0.36) and 0.26 percentage points (95% CI, -0.33 to -0.20 percentage points) for imaging claims associated with inpatient stays and ED visits, respectively. CONCLUSIONS: Radiologists' imaging claims that are OON has significantly declined from 2007 to a minimal level in 2021. This may indicate effective negotiations between radiologists and commercial payers and new state-level surprise billing laws.

The Neiman Imaging Comorbidity Index: Development and Validation in a National Commercial Claims Database.

OBJECTIVE: To build the Neiman Imaging Comorbidity Index (NICI), based on variables available in claims datasets, which provides good discrimination of an individual's chance of receiving advanced imaging (CT, MR, PET), and thus, utility as a control variable in research. METHODS: This retrospective study used national commercial claims data from Optum's deidentified Clinformatics Data Mart database from the period January 1, 2018 to December 31, 2019. Individuals with continuous enrollment during this 2-year study period were included. Lasso (least absolute shrinkage and selection operator) regression was used to predict the chance of receiving advanced imaging in 2019 based on the presence of comorbidities in 2018. A numerical index was created in a development cohort (70% of the total dataset) using weights assigned to each comorbidity, based on regression ß coefficients. Internal validation of assigned scores was performed in the remaining 30% of claims, with comparison to the commonly used Charlson Comorbidity Index. RESULTS: The final sample (development and validation cohorts) included 10,532,734 beneficiaries, of whom 2,116,348 (20.1%) received advanced imaging. After model development, the NICI included nine comorbidities. In the internal validation set, the NICI achieved good discrimination of receipt of advanced imaging with a C statistic of 0.709 (95% confidence interval [CI] 0.708-0.709), which predicted advanced imaging better than the CCI (C 0.692, 95% CI 0.691-0.692). Controlling for age and sex yielded better discrimination (C 0.748, 95% CI 0.748-0.749). DISCUSSION: The NICI is an easily calculated measure of comorbidity burden that can be used to adjust for patients' chances of receiving advanced imaging. Future work should explore external validation of the NICI.

Sociodemographic Factors and Screening CT Colonography Use Among Medicare Beneficiaries.

BACKGROUND. Approximately one-third of the eligible U.S. population have not undergone guideline-compliant colorectal cancer (CRC) screening. Guidelines recognize various screening strategies to increase adherence. CMS provides coverage for all recommended screening tests except CT colonography (CTC). OBJECTIVE. The purpose of this study was to compare CTC and other CRC screening tests in terms of associations of utilization with income, race and ethnicity, and urbanicity in Medicare fee-for-service beneficiaries. METHODS. This retrospective study used CMS Research Identifiable Files from January 1, 2011, through December 31, 2020. These files contain claims information for 5% of Medicare fee-for-service beneficiaries. Data were extracted for individuals 45-85 years old, and individuals with high CRC risk were excluded. Multivariable logistic regression models were constructed to determine the likelihood of undergoing CRC screening tests (as well as of undergoing diagnostic CTC, a CMS-covered test with similar physical access as screening CTC) as a function of income, race and ethnicity, and urbanicity while controlling for sex, age, Charlson comorbidity index, U.S. census region, screening year, and related conditions and procedures. RESULTS. For 12,273,363 beneficiary years (mean age, 70.5 ± 8.2 [SD] years; 2,436,849 unique beneficiaries: 6,774,837 female beneficiaries, 5,498,526 male beneficiaries), there were 785,103 CRC screenings events, including 645 for screening CTC. Compared with individuals living in communities with per capita income of less than US$25,000, individuals in communities with income of US$100,000 or more had OR for undergoing screening CTC of 5.73, optical colonoscopy (OC) of 1.36, sigmoidoscopy of 1.03, guaiac fecal occult blood test or fecal immunochemical test of 1.50, stool DNA of 1.43, and diagnostic CTC of 2.00. The OR for undergoing screening CTC was 1.00 for Hispanic individuals and 1.08 for non-Hispanic Black individuals compared with non-Hispanic White individuals. Compared with the OR for undergoing screening CTC for residents of metropolitan areas, the OR was 0.51 for residents of micropolitan areas and 0.65 for residents of small or rural areas. CONCLUSION. The association with income was substantially larger for screening CTC than for other CRC screening tests or for diagnostic CTC. CLINICAL IMPACT. Medicare's noncoverage for screening CTC may contribute to lower adherence with CRC screening guidelines for lower-income beneficiaries. Medicare coverage of CTC could reduce income-based disparities for individuals avoiding OC owing to invasiveness, need for anesthesia, or complication risk.

Projected Growth in FDA-Approved Artificial Intelligence Products Given Venture Capital Funding.

PURPOSE: Medical imaging accounts for 85% of digital health's venture capital funding. As funding grows, it is expected that artificial intelligence (AI) products will increase commensurately. The study's objective is to project the number of new AI products given the statistical association between historical funding and FDA-approved AI products. METHODS: The study used data from the ACR Data Science Institute and for the number of FDA-approved AI products (2008-2022) and data from Rock Health for AI funding (2013-2022). Employing a 6-year lag between funding and product approved, we used linear regression to estimate the association between new products approved in a certain year, based on the lagged funding (ie, product-year funding). Using this statistical relationship, we forecasted the number of new FDA-approved products. RESULTS: The results show that there are 11.33 (95% confidence interval: 7.03-15.64) new AI products for every $1 billion in funding assuming a 6-year lag between funding and product approval. In 2022 there were 69 new FDA-approved products associated with $4.8 billion in funding. In 2035, product-year funding is projected to reach $30.8 billion, resulting in 350 new products that year. CONCLUSIONS: FDA-approved AI products are expected to grow from 69 in 2022 to 350 in 2035 given the expected funding growth in the coming years. AI is likely to change the practice of diagnostic radiology as new products are developed and integrated into practice. As more AI products are integrated, it may incentivize increased investment for future AI products.

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.

Trends in Diagnostic Imaging by Nonphysician Practitioners and Associations With Urbanicity and Scope-of-Practice Authority.

OBJECTIVE: We aimed to assess the changing share of diagnostic imaging billed by NPPs and how such changes differ by urbanicity within the context of scope-of-practice (SOP) regulations and legislation. METHODS: This retrospective cohort study used patient claims for diagnostic imaging studies spanning 2016-2020 from Optum Clinformatics Datamart datasets. Multivariable modeling determined the odds of patients receiving NPP-interpreted vs physician-interpreted imaging. Imaging rates and trends in proportions of NPP-billed claims were assessed by urbanicity and relative to other factors including SOP, imaging modality, and place of service. RESULTS: Of all identified imaging claims, 3,348,881 (3.0%) were attributed to NPPs, with the highest rates of NPP interpretations per 10,000 images occurring in rural and small-town areas. From 2016 to 2020, the rate of NPP-billed imaging increased from 257 to 331 claims per 10,000 beneficiaries (P = 0.004), observed across both metropolitan (240 to 315, P = 0.001) and micropolitan (367 to 436, P = 0.020) settings. Although rates in rural and small-town areas rose, the increase was not significant (330 to 392, P = 0.363). Rises in NPP imaging in metropolitan settings occurred in states with moderately restrictive (307 to 358, P = 0.008) and least restrictive (289 to 419, P = 0.004) SOP legislation. DISCUSSION: Rates of diagnostic imaging interpretation by NPPs are rising. Growth in recent years appears driven by metropolitan areas in states with less restrictive SOP regulations. Future work is necessary to assess the quality of and downstream costs related to increasing NPP-interpreted imaging.

Imaging Utilization Patterns in the Follow-Up of Extremity Soft Tissue Sarcomas in the United States.

This study aimed to describe patterns of imaging utilization after resection of extremity soft tissue sarcoma in the United States, assess for potential disparities, and evaluate temporal trends. A retrospective cohort study using a national database of private payer claims data was performed to determine the utilization rate of extremity and chest imaging in a 5-year postoperative follow-up period for patients with extremity soft tissue sarcoma treated between 2007 and 2019. Imaging utilization was assessed according to patient demographics (age, sex, race and ethnicity, and region of residency), calendar year of surgery, and postoperative year. Associations of demographic variables with imaging use were assessed using chi-square tests, trends in imaging use were analyzed using the Cochran-Armitage trend test or linear regression, and associations of postoperative year with imaging use were evaluated with the Pearson Correlation coefficient. A total of 3707 patients were included. Most patients received at least 1 chest (74%) and extremity (53%) imaging examination during their follow-up period. The presence of surveillance imaging was significantly associated with age (P < 0.0001) and region (P = 0.0029). Over the study period, there was an increase in use of extremity MRI (P < 0.05) and ultrasound (P < 0.01) and chest CT (P < 0.0001) and a decrease in use of chest radiographs (P < 0.0001). Imaging use declined over postoperative years (decrease by 85%-92% from year 1-5). In conclusion, the use of surveillance imaging varied according to patient demographics and has increased for extremity MRI and ultrasound and chest CT over the study period.

Urbanicity, Income, and Mammography-Use Disparities Among American Indian Women.

INTRODUCTION: Reported breast cancer screening among American Indian women is consistently below that of White women. The last claims-based trends were from 1991 to 2001. This study updates mammography trends for American Indian women and examines the impact of race, urbanicity, and income on long-term mammography use. METHODS: This was a multi-year (2005-2019), retrospective study of women aged 40-89 years using a 5% sample of Medicare fee-for-service beneficiaries residing in Arizona, California, New Mexico, Oklahoma, and Washington. This study used multivariable logistic regression to examine the impact of urbanicity and income on receiving mammography for American Indian women compared with that for White women. Analyses were conducted in 2022. RESULTS: Overall, annual age-adjusted mammography use declined from 205 per 1,000 in 2005 to 165 per 1,000 in 2019. The slope of these declines was significantly steeper (difference = -2.41, p<0.001) for White women (-3.06) than for American Indian women (-0.65). Mammography-use odds across all urbanicity categories were less for American Indian women than for White women compared with those of their respective metropolitan counterparts (e.g., rural: 0.96, 95% CI=0.77, 1.20 for American Indian women and 1.47, 99% CI=1.39, 1.57 for White women). Although residing in higher-income communities was not associated with mammography use for American Indian women, it was 31% higher for White women (OR=1.31, 99% CI=1.28, 1.34). CONCLUSIONS: The disparity in annual age-adjusted mammography use between American Indian and White women narrowed between 2005 and 2019. However, the association of urbanicity and community income on mammography use differs substantially between American Indian and White women. Policies to reduce disparities need to consider these differences.

Comparison of Lung Cancer Screening Eligibility and Use between Commercial, Medicare, and Medicare Advantage Enrollees.

OBJECTIVE: Lung cancer screening does not require patient cost-sharing for insured people in the U.S. Little is known about whether other factors associated with patient selection into different insurance plans affect screening rates. We examined screening rates for enrollees in commercial, Medicare Fee-for-Service (FFS), and Medicare Advantage plans. METHODS: County-level smoking rates from the 2017 County Health Rankings were used to estimate the number of enrollees eligible for lung cancer screening in two large retrospective claims databases covering: a 5% national sample of Medicare FFS enrollees; and 100% sample of enrollees associated with large commercial and Medicare Advantage carriers. Screening rates were estimated using observed claims, stratified by payer, before aggregation into national estimates by payer and demographics. Chi-square tests were used to examine differences in screening rates between payers. RESULTS: There were 1,077,142 enrollees estimated to be eligible for screening. The overall estimated screening rate for enrollees by payer was 1.75% for commercial plans, 3.37% for Medicare FFS, and 4.56% for Medicare Advantage plans. Screening rates were estimated to be lowest among females (1.55%-4.02%), those aged 75-77 years (0.63%-2.87%), those residing in rural areas (1.88%-3.56%), and those in the West (1.16%-3.65%). Among Medicare FFS enrollees, screening rates by race/ethnicity were non-Hispanic White (3.71%), non-Hispanic Black (2.17%) and Other (1.68%). CONCLUSIONS: Considerable variation exists in lung cancer screening between different payers and across patient characteristics. Efforts targeting historically vulnerable populations could present opportunities to increase screening.

Patient Cost-Sharing and Utilization of Breast Cancer Diagnostic Imaging by Patients Undergoing Subsequent Testing After a Screening Mammogram.

Importance: Out-of-pocket costs (OOPCs) have been largely eliminated for screening mammography. However, patients still face OOPCs when undergoing subsequent diagnostic tests after the initial screening, which represents a potential barrier to those who require follow-up testing after initial testing. Objective: To examine the association between the degree of patient cost-sharing and the use of diagnostic breast cancer imaging after undergoing a screening mammogram. Design, Setting, and Participants: This retrospective cohort study used medical claims from Optum's deidentified Clinformatics Data Mart Database, a commercial claims database derived from a database of administrative health claims for members of large commercial and Medicare Advantage health plans. The large commercially insured cohort included female patients aged 40 years or older with no prior history of breast cancer undergoing a screening mammogram examination. Data were collected from January 1, 2015, to December 31, 2017, and analysis was conducted from January 2021 to September 2022. Exposures: A k-means clustering machine learning algorithm was used to classify patient insurance plans by dominant cost-sharing mechanism. Plan types were then ranked by OOPCs. Main Outcomes and Measures: A multivariable 2-part hurdle regression model was used to examine the association between patient OOPCs and the number and type of diagnostic breast services undergone by patients observed to undergo subsequent testing. Results: In our sample, 230 845 women (220 023 [95.3%] aged 40 to 64 years; 16 810 [7.3%] Black, 16 398 [7.1%] Hispanic, and 164 702 [71.3%] White) underwent a screening mammogram in 2016. These patients were covered by 22 828 distinct insurance plans associated with 6 025 741 enrollees and 44 911 473 distinct medical claims. Plans dominated by coinsurance were found to have the lowest mean (SD) OOPCs ($945 [$1456]), followed by balanced plans ($1017 [$1386]), plans dominated by copays ($1020 [$1408]), and plans dominated by deductibles ($1186 [$1522]). Women underwent significantly fewer subsequent breast imaging procedures in dominantly copay (24 [95% CI, 11-37] procedures per 1000 women) and dominantly deductible (16 [95% CI, 5-28] procedures per 1000 women) plans compared with coinsurance plans. Patients from all plan types underwent fewer breast magnetic resonance imaging (MRI) scans than patients in the lowest OOPC plan (balanced, 5 [95% CI, 2-12] MRIs per 1000 women; copay, 6 [95% CI, 3-6] MRI per 100 women; deductible, 6 [95% CI, 3-9] MRIs per 1000 women. Conclusions and Relevance: Despite policies designed to remove financial barriers to access for breast cancer screening, significant financial barriers remain for women at risk of breast cancer.