» Articles » PMID: 32640248

National Trends in Oncologic Diagnostic Imaging

Overview
Publisher Elsevier
Specialty Radiology
Date 2020 Jul 9
PMID 32640248
Citations 2
Authors
Affiliations
Soon will be listed here.
Abstract

Objective: To characterize national trends in oncologic imaging (OI) utilization.

Methods: This retrospective cross-sectional study used 2004 and 2016 CMS 5% Carrier Claims Research Identifiable Files. Radiologist-performed, primary noninvasive diagnostic imaging examinations were identified from billed Current Procedural Terminology codes; CT, MRI, and PET/CT examinations were categorized as "advanced" imaging. OI examinations were identified from imaging claims' primary International Classification of Diseases-9 and International Classification of Diseases-10 codes. Imaging services were stratified by academic practice status and place of service. State-level correlations of oncologic advanced imaging utilization (examinations per 1,000 beneficiaries) with cancer prevalence and radiologist supply were assessed by Spearman correlation coefficient.

Results: The national Medicare sample included 5,051,095 diagnostic imaging examinations (1,220,224 of them advanced) in 2004 and 5,023,115 diagnostic imaging examinations (1,504,608 of them advanced) in 2016. In 2004 and 2016, OI represented 4.3% and 3.9%, respectively, of all imaging versus 10.8% and 9.5%, respectively, of advanced imaging. The percentage of advanced OI done in academic practices rose from 18.8% in 2004 to 34.1% in 2016, leaving 65.9% outside academia. In 2016, 58.0% of advanced OI was performed in the hospital outpatient setting and 23.9% in the physician office setting. In 2016, state-level oncologic advanced imaging utilization correlated with state-level radiologist supply (r = +0.489, P < .001) but not with state-level cancer prevalence (r = -0.139, P = .329).

Discussion: OI usage varied between practice settings. Although the percentage of advanced OI done in academic settings nearly doubled from 2004 to 2016, the majority remained in nonacademic practices. State-level oncologic advanced imaging utilization correlated with radiologist supply but not cancer prevalence.

Citing Articles

Oncologic Errors in Diagnostic Radiology: A 10-Year Analysis Based on Medical Malpractice Claims.

Rosenkrantz A, Siegal D, Skillings J, Muellner A, Nass S, Hricak H J Am Coll Radiol. 2021; 18(9):1310-1316.

PMID: 34058137 PMC: 11175171. DOI: 10.1016/j.jacr.2021.05.001.


Medical imaging and nuclear medicine: a Lancet Oncology Commission.

Hricak H, Abdel-Wahab M, Atun R, Mikhail Lette M, Paez D, Brink J Lancet Oncol. 2021; 22(4):e136-e172.

PMID: 33676609 PMC: 8444235. DOI: 10.1016/S1470-2045(20)30751-8.

References
1.
Chodick G, Levin M, Kleinerman R, Shwarz M, Shalev V, Ashkenazi S . Differences in characteristics of pediatric patients undergoing computed tomography between hospitals and primary care settings: implications for assessing cancer follow-up studies. Isr J Health Policy Res. 2015; 4:33. PMC: 4644629. DOI: 10.1186/s13584-015-0031-x. View

2.
Herold C, Lewin J, Wibmer A, Thrall J, Krestin G, Dixon A . Imaging in the Age of Precision Medicine: Summary of the Proceedings of the 10th Biannual Symposium of the International Society for Strategic Studies in Radiology. Radiology. 2015; 279(1):226-38. DOI: 10.1148/radiol.2015150709. View

3.
Abouassaly R, Finelli A, Tomlinson G, Urbach D, Alibhai S . Volume-outcome relationships in the treatment of renal tumors. J Urol. 2012; 187(6):1984-8. DOI: 10.1016/j.juro.2012.01.076. View

4.
Rosenkrantz A, Wang W, Hughes D, Duszak Jr R . A County-Level Analysis of the US Radiologist Workforce: Physician Supply and Subspecialty Characteristics. J Am Coll Radiol. 2018; 15(4):601-606. DOI: 10.1016/j.jacr.2017.11.007. View

5.
Pfister D, Rubin D, Elkin E, Neill U, Duck E, Radzyner M . Risk Adjusting Survival Outcomes in Hospitals That Treat Patients With Cancer Without Information on Cancer Stage. JAMA Oncol. 2015; 1(9):1303-10. PMC: 5038982. DOI: 10.1001/jamaoncol.2015.3151. View