
REGULAR CONTENT
Final ID
445
Type
Original Scientific Research-Oral or Pos
Authors
M Toliyat1, A Patel1, D Lamus1, H Park1, P Sutphin1
Institutions
1University of Texas Southwestern Medical Center, Dallas, TX
Purpose
To develop a tool, from publicly-available data, to assist interventional radiology fellowship applicants and medical students applying for IR/DR residency in choosing a suitable training program. The tool will consider geographic location, procedural case mix, volume, and program alumni.
Materials & Methods
The Medicare Provider Utilization and Payment data from 2014 was downloaded as a tab-delimited file from the Centers for Medicare and Medicaid Services (CMS) website, http://www.cms.gov. The data was filtered using R statistical software for both Interventional Radiologists and Diagnostic Radiologists. Billed procedure codes relevant to interventional radiology were identified and classified into 21 categories such as venous access, dialysis, interventional oncology, peripheral arterial disease, and vascular imaging. A database of IR fellowship positions was then created using data available from the National Resident Matching Program (NRMP), http://www.nrmp.org for 2016. The CMS data and NRMP data were merged to identify IR procedures billed to CMS by the respective fellowship programs.
Results
Fellowship positions are mainly distributed in metropolitan areas, with New York, Chicago, and Boston offering the most IR fellowship positions with 20, 17, and 15 spots respectively. The Northeastern part of the United States has the most fellowship positions with 71 (30%). Evaluation of procedural mix demonstrates heterogeneity between IR fellowship programs. The most consistent procedural categories include vascular access, venous intervention and body drainage/biopsy. Less consistent procedural categories include dialysis, advanced bone interventions, and peripheral arterial disease. The CMS data can also be used to evaluate the practice location and billed procedures of recent program alumni.
Conclusions
Publicly available data can be used to characterize IR fellowship programs with respect to geography, procedural case mix, volume (billed to CMS), and the post-graduate path of recent alumni. The aggregation of the available data may then be used to help guide medical students and residents in selecting IR programs for application.
Final ID
445
Type
Original Scientific Research-Oral or Pos
Authors
M Toliyat1, A Patel1, D Lamus1, H Park1, P Sutphin1
Institutions
1University of Texas Southwestern Medical Center, Dallas, TX
Purpose
To develop a tool, from publicly-available data, to assist interventional radiology fellowship applicants and medical students applying for IR/DR residency in choosing a suitable training program. The tool will consider geographic location, procedural case mix, volume, and program alumni.
Materials & Methods
The Medicare Provider Utilization and Payment data from 2014 was downloaded as a tab-delimited file from the Centers for Medicare and Medicaid Services (CMS) website, http://www.cms.gov. The data was filtered using R statistical software for both Interventional Radiologists and Diagnostic Radiologists. Billed procedure codes relevant to interventional radiology were identified and classified into 21 categories such as venous access, dialysis, interventional oncology, peripheral arterial disease, and vascular imaging. A database of IR fellowship positions was then created using data available from the National Resident Matching Program (NRMP), http://www.nrmp.org for 2016. The CMS data and NRMP data were merged to identify IR procedures billed to CMS by the respective fellowship programs.
Results
Fellowship positions are mainly distributed in metropolitan areas, with New York, Chicago, and Boston offering the most IR fellowship positions with 20, 17, and 15 spots respectively. The Northeastern part of the United States has the most fellowship positions with 71 (30%). Evaluation of procedural mix demonstrates heterogeneity between IR fellowship programs. The most consistent procedural categories include vascular access, venous intervention and body drainage/biopsy. Less consistent procedural categories include dialysis, advanced bone interventions, and peripheral arterial disease. The CMS data can also be used to evaluate the practice location and billed procedures of recent program alumni.
Conclusions
Publicly available data can be used to characterize IR fellowship programs with respect to geography, procedural case mix, volume (billed to CMS), and the post-graduate path of recent alumni. The aggregation of the available data may then be used to help guide medical students and residents in selecting IR programs for application.