Literature DB >> 29305075

A County-Level Analysis of the US Radiologist Workforce: Physician Supply and Subspecialty Characteristics.

Andrew B Rosenkrantz1, Wenyi Wang2, Danny R Hughes3, Richard Duszak4.   

Abstract

PURPOSE: To explore associations between county-level measures of radiologist supply and subspecialization and county structural and health-related characteristics.
METHODS: Medicare Physician and Other Supplier Public Use Files were used to subspecialty characterize 32,844 radiologists participating in Medicare between 2012 and 2014. Measures of radiologist supply and subspecialization were computed for 3,143 US counties. Additional county characteristics were identified using the 2014 County Health Rankings database. Mann-Whitney tests and Spearman correlations were performed.
RESULTS: Counties with at least one (versus no) Medicare-participating radiologist had significantly (P < .001) larger populations (197,050 ± 457,056 versus 20,253 ± 23,689), lower rural percentages (39.5% ± 26.5% versus 74.6% ± 25.6%), higher household incomes ($47,608 ± $12,493 versus $42,510 ± $9,893), higher mammography screening rates (62.4% ± 7.0% versus 56.6% ± 15.3%), and lower premature deaths (7,581 ± 2,085 versus 7,784 ± 3,409 years of life lost). Counties' radiologists per 100,000 population and percent of subspecialized radiologists showed moderate positive correlations with counties' population (r = +0.505-+0.599) and moderate negative correlations with counties' rural percentage (r = -0.434 to -0.523). Radiologist supply and degree of subspecialization both showed concurrent positive or negative weak associations with counties' percent age 65+ (r = -0.256 to -0.271), percent Hispanic (r = +0.209-+0.234), and income (r = +0.230-+0.316). Radiologists per 100,000 population showed weak positive correlation with mammography screening (r = +0.214); percent of radiologists subspecialized showed weak negative correlation with premature death (r = -0.226).
CONCLUSION: Geographic disparities in radiologist supply at the community level are compounded by superimposed variation in the degree of subspecialization of those radiologists. The potential impact of such access disparities on county-level health warrants further investigation.
Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Medicare; Radiologist workforce; health policy; physician supply; subspecialization

Mesh:

Year:  2018        PMID: 29305075     DOI: 10.1016/j.jacr.2017.11.007

Source DB:  PubMed          Journal:  J Am Coll Radiol        ISSN: 1546-1440            Impact factor:   5.532


  5 in total

1.  Improving Cancer Diagnosis and Care: Patient Access to Oncologic Imaging Expertise.

Authors:  Sharyl J Nass; Christopher R Cogle; James A Brink; Curtis P Langlotz; Erin P Balogh; Ada Muellner; Dana Siegal; Richard L Schilsky; Hedvig Hricak
Journal:  J Clin Oncol       Date:  2019-05-03       Impact factor: 44.544

2.  National Trends in Oncologic Diagnostic Imaging.

Authors:  Andrew B Rosenkrantz; Laura Chaves Cerdas; Danny R Hughes; Michael P Recht; Sharyl J Nass; Hedvig Hricak
Journal:  J Am Coll Radiol       Date:  2020-07-05       Impact factor: 5.532

3.  Characteristics of COVID-19 Community Practice Declines in Noninvasive Diagnostic Imaging Professional Work.

Authors:  Richard Duszak; Jeff Maze; Candice Sessa; Howard B Fleishon; Lauren P Golding; Gregory N Nicola; Danny R Hughes
Journal:  J Am Coll Radiol       Date:  2020-07-03       Impact factor: 5.532

4.  MIMIC-CXR, a de-identified publicly available database of chest radiographs with free-text reports.

Authors:  Alistair E W Johnson; Tom J Pollard; Seth J Berkowitz; Nathaniel R Greenbaum; Matthew P Lungren; Chih-Ying Deng; Roger G Mark; Steven Horng
Journal:  Sci Data       Date:  2019-12-12       Impact factor: 6.444

5.  Incorporating Medical Supply and Demand into the Index of Physician Maldistribution Improves the Sensitivity to Healthcare Outcomes.

Authors:  Atsushi Takayama; Hemant Poudyal
Journal:  J Clin Med       Date:  2021-12-28       Impact factor: 4.241

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.