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Analysis of Rural Disparities in Ultrasound Access
Purpose This work aims to conduct a geospatial analysis of recent ultrasound access and usage within the United States, with a particular focus on disparities between rural and urban areas. Methods/Materials Multiple public datasets were merged on a county level, including US Department of Agricultu...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cureus
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9236672/ https://www.ncbi.nlm.nih.gov/pubmed/35774712 http://dx.doi.org/10.7759/cureus.25425 |
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author | Peterman, Nicholas J Yeo, Eunhae Kaptur, Brad Smith, Emily J Christensen, Anton Huang, Edward Rasheed, Mehmoodur |
author_facet | Peterman, Nicholas J Yeo, Eunhae Kaptur, Brad Smith, Emily J Christensen, Anton Huang, Edward Rasheed, Mehmoodur |
author_sort | Peterman, Nicholas J |
collection | PubMed |
description | Purpose This work aims to conduct a geospatial analysis of recent ultrasound access and usage within the United States, with a particular focus on disparities between rural and urban areas. Methods/Materials Multiple public datasets were merged on a county level, including US Department of Agriculture economic metrics and Centers for Medicare Services data using the most recent years available (2015-2019). From these databases, 39 total variables encompassing the socioeconomic, health, and ultrasound characteristics of each county were obtained. Current Procedural Terminology (CPT) codes incorporated included ultrasound-guided procedures and diagnostic exams. Three thousand eleven counties were included. The combined dataset was then exported to GeoDa for network-based analysis and to produce map visualizations. To identify statistically significant (p < 0.05) hotspots and coldspots in point-of-care ultrasound (POCUS) prevalence, Moran’s I was used. Choropleth maps were created for visualization. ANOVA was run across the four Moran’s I groups for each of 39 variables of interest. Results A total of 30,135,085 ultrasound-related CPT codes were billed to Medicare over 2015-2019, with 26.55% of codes being ultrasound-guided procedures and 73.45% being diagnostic exams. 38.84% of rural counties had access to POC ultrasound compared to 88.56% of metropolitan counties and 74.19% of counties overall. Hotspots of POCUS were in Southern California and the Eastern US (average of 1,441 per 10,000 Medicare members per year). Coldspot areas were seen in the Great Plains and Midwest (average of 7.43 per 10k Medicare members per year). Hotspot clusters, when compared to coldspot clusters, were significantly (p < 0.001) more dense (703.6 to 14.9 people per square mile), more urbanized (3.5 to 7.1 Rural-Urban Continuum (RUC)), more college-educated (25.1% to 20.0%), more likely to have an Emergency Department (ED) visit (725.8 to 616.9 visits per 1,000 Medicare members), more likely to be obese (19.0% to 12.9%), less likely to be uninsured (10.1% to 13.0%), had more Black representation (8.5% to 3.4%), and less Hispanic representation (2.6% to 5.5%). Conclusions Ultrasound access and usage demonstrate significant geospatial trends across the United States. Hotspot and coldspot counties differ on several key sociodemographic and economic variables. |
format | Online Article Text |
id | pubmed-9236672 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cureus |
record_format | MEDLINE/PubMed |
spelling | pubmed-92366722022-06-29 Analysis of Rural Disparities in Ultrasound Access Peterman, Nicholas J Yeo, Eunhae Kaptur, Brad Smith, Emily J Christensen, Anton Huang, Edward Rasheed, Mehmoodur Cureus Public Health Purpose This work aims to conduct a geospatial analysis of recent ultrasound access and usage within the United States, with a particular focus on disparities between rural and urban areas. Methods/Materials Multiple public datasets were merged on a county level, including US Department of Agriculture economic metrics and Centers for Medicare Services data using the most recent years available (2015-2019). From these databases, 39 total variables encompassing the socioeconomic, health, and ultrasound characteristics of each county were obtained. Current Procedural Terminology (CPT) codes incorporated included ultrasound-guided procedures and diagnostic exams. Three thousand eleven counties were included. The combined dataset was then exported to GeoDa for network-based analysis and to produce map visualizations. To identify statistically significant (p < 0.05) hotspots and coldspots in point-of-care ultrasound (POCUS) prevalence, Moran’s I was used. Choropleth maps were created for visualization. ANOVA was run across the four Moran’s I groups for each of 39 variables of interest. Results A total of 30,135,085 ultrasound-related CPT codes were billed to Medicare over 2015-2019, with 26.55% of codes being ultrasound-guided procedures and 73.45% being diagnostic exams. 38.84% of rural counties had access to POC ultrasound compared to 88.56% of metropolitan counties and 74.19% of counties overall. Hotspots of POCUS were in Southern California and the Eastern US (average of 1,441 per 10,000 Medicare members per year). Coldspot areas were seen in the Great Plains and Midwest (average of 7.43 per 10k Medicare members per year). Hotspot clusters, when compared to coldspot clusters, were significantly (p < 0.001) more dense (703.6 to 14.9 people per square mile), more urbanized (3.5 to 7.1 Rural-Urban Continuum (RUC)), more college-educated (25.1% to 20.0%), more likely to have an Emergency Department (ED) visit (725.8 to 616.9 visits per 1,000 Medicare members), more likely to be obese (19.0% to 12.9%), less likely to be uninsured (10.1% to 13.0%), had more Black representation (8.5% to 3.4%), and less Hispanic representation (2.6% to 5.5%). Conclusions Ultrasound access and usage demonstrate significant geospatial trends across the United States. Hotspot and coldspot counties differ on several key sociodemographic and economic variables. Cureus 2022-05-28 /pmc/articles/PMC9236672/ /pubmed/35774712 http://dx.doi.org/10.7759/cureus.25425 Text en Copyright © 2022, Peterman et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Public Health Peterman, Nicholas J Yeo, Eunhae Kaptur, Brad Smith, Emily J Christensen, Anton Huang, Edward Rasheed, Mehmoodur Analysis of Rural Disparities in Ultrasound Access |
title | Analysis of Rural Disparities in Ultrasound Access |
title_full | Analysis of Rural Disparities in Ultrasound Access |
title_fullStr | Analysis of Rural Disparities in Ultrasound Access |
title_full_unstemmed | Analysis of Rural Disparities in Ultrasound Access |
title_short | Analysis of Rural Disparities in Ultrasound Access |
title_sort | analysis of rural disparities in ultrasound access |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9236672/ https://www.ncbi.nlm.nih.gov/pubmed/35774712 http://dx.doi.org/10.7759/cureus.25425 |
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