title: Academic Radiologist Subspecialty Identification Using a Novel Claims-Based Classification System.
abstract: OBJECTIVE
  The objective of the present study is to assess the feasibility of a novel claims-based classification system for payer identification of academic radiologist subspecialties.
  
  
  METHODS
  Using a categorization scheme based on the Neiman Imaging Types of Service (NITOS) system, we mapped the Medicare Part B services billed by all radiologists from 2012 to 2014, assigning them to the following subspecialty categories: abdominal imaging, breast imaging, cardiothoracic imaging, musculoskeletal imaging, nuclear medicine, interventional radiology, and neuroradiology. The percentage of subspecialty work relative value units (RVUs) to total billed work RVUs was calculated for each radiologist nationwide. For radiologists at the top 20 academic departments funded by the National Institutes of Health, those percentages were compared with subspecialties designated on faculty websites. NITOS-based subspecialty assignments were also compared with the only radiologist subspecialty classifications currently recognized by Medicare (i.e., nuclear medicine and interventional radiology).
  
  
  RESULTS
  Of 1012 academic radiologists studied, the median percentage of Medicare-billed NITOS-based subspecialty work RVUs matching the subspecialty designated on radiologists' own websites ranged from 71.3% (for nuclear medicine) to 98.9% (for neuroradiology). A NITOS-based work RVU threshold of 50% correctly classified 89.8% of radiologists (5.9% were not mapped to any subspecialty; subspecialty error rate, 4.2%). In contrast, existing Medicare provider codes identified only 46.7% of nuclear medicine physicians and 39.4% of interventional radiologists.
  
  
  CONCLUSIONS
  Using a framework based on a recently established imaging health services research tool that maps service codes based on imaging modality and body region, Medicare claims data can be used to consistently identify academic radiologists by subspecialty in a manner not possible with the use of existing Medicare physician specialty identifiers. This method may facilitate more appropriate performance metrics for subspecialty academic physicians under emerging value-based payment models.
authors.affiliation: 1 Department of Radiology, Center for Biomedical Imaging, NYU School of Medicine, NYU Langone Medical Center, 660 First Ave, 3rd Fl, New York, NY 10016.
authors.forename: Andrew B
authors.initials: AB
authors.lastname: Rosenkrantz
authors.affiliation: 2 Harvey L. Neiman Health Policy Institute, Reston, VA.
authors.forename: Wenyi
authors.initials: W
authors.lastname: Wang
authors.affiliation: 2 Harvey L. Neiman Health Policy Institute, Reston, VA.|3 Department of Health Administration and Policy, George Mason University, Fairfax, VA.
authors.forename: Danny R
authors.initials: DR
authors.lastname: Hughes
authors.affiliation: 1 Department of Radiology, Center for Biomedical Imaging, NYU School of Medicine, NYU Langone Medical Center, 660 First Ave, 3rd Fl, New York, NY 10016.
authors.forename: Luke A
authors.initials: LA
authors.lastname: Ginocchio
authors.affiliation: 4 Department of Radiology, Massachusetts General Hospital, Boston, MA.
authors.forename: David A
authors.initials: DA
authors.lastname: Rosman
authors.affiliation: 5 Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA.
authors.forename: Richard
authors.initials: R
authors.lastname: Duszak
mesh_terms: D000046:Academic Medical Centers / Q000706:statistics & numerical data*; D003952:Diagnostic Imaging / Q000706:statistics & numerical data*; D007345:Insurance Claim Review / Q000706:statistics & numerical data*; D006278:Medicare / Q000706:statistics & numerical data*; D000072177:Radiologists / Q000706:statistics & numerical data; D011871:Radiology / Q000706:statistics & numerical data*; D015895:Relative Value Scales; D014481:United States; D000078329:Workforce; D016526:Workload / Q000706:statistics & numerical data*
keywords: academic practice; radiologists; subspecialties