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.
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http://dx.doi.org/10.1067/j.cpradiol.2023.06.001 | DOI Listing |
Fluids Barriers CNS
January 2025
Medical Image Processing Department, CHU Amiens-Picardie University Hospital, Amiens, France.
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View Article and Find Full Text PDFAdvances in imaging techniques have evolved, allowing for early noninvasive diagnosis and improved management of high-risk patients with hepatocellular carcinoma (HCC). The hallmark imaging features of HCC on multiphasic cross-sectional imaging can be explained by the multistep process of hepatocarcinogenesis and is seen in 60% of cases. However, approximately 40% of cases do not abide by the classic imaging appearance and may pose a diagnostic challenge for radiologists.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
College of Computer, Chongqing University, No. 55 Daxuecheng South Rd, Shapingba, 401331, Chongqing, China.
Convolutional neural networks (CNNs) have become indispensable to medical image diagnosis research, enabling the automated differentiation of diseased images from extensive medical image datasets. Due to their efficacy, these methods raise significant privacy concerns regarding patient images and diagnostic models. To address these issues, some researchers have explored privacy-preserving medical image diagnosis schemes using fully homomorphic encryption (FHE).
View Article and Find Full Text PDFJ Imaging Inform Med
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Monash Imaging, Monash Health, 246 Clayton Rd, Clayton, VIC, 3168, Australia.
We extend existing techniques by using generative adversarial network (GAN) models to reduce the appearance of cast shadows in radiographs across various age groups. We retrospectively collected 11,500 adult and paediatric wrist radiographs, evenly divided between those with and without casts. The test subset consisted of 750 radiographs with cast and 750 without cast.
View Article and Find Full Text PDFUrol Oncol
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Research Department, Urovallarta Medical Center, Puerto Vallarta, Mexico.
Background: Multiparametric MRI (Mp-MRI) is a key tool to screen for Prostate Cancer (Pca) and Clinically Significant Prostate Cancer (CsPca). It primarily includes T2-Weighted imaging (T2w), diffusion-weighted imaging (DWI), and Dynamic Contrast-Enhanced imaging (DCE). Despite its improvements in CsPca screening, concerns about the cost-effectiveness of DCE persist due to its associated side effects, increased cost, longer acquisition time, and limitations in patients with poor kidney function.
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