Accessible medical diagnostic equipment in primary care: Assessing its geographic distribution for disability equity
Height adjustable examination tables, accessible weight scales, and lifts for transferring individuals on/off examination equipment enable delivery of equitable health care to persons with mobility impairment. Because most Medicaid-covered patients must utilize a managed care network, network provid...
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Veröffentlicht in: | Disability and health journal 2023-04, Vol.16 (2), p.101425-101425, Article 101425 |
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creator | Mudrick, Nancy R. Breslin, Mary Lou Blackwell, Julia Wang, Xiafei Nielsen, Kyrian A. |
description | Height adjustable examination tables, accessible weight scales, and lifts for transferring individuals on/off examination equipment enable delivery of equitable health care to persons with mobility impairment. Because most Medicaid-covered patients must utilize a managed care network, network providers with accessible medical diagnostic equipment (MDE) at proximate locations for travel time and distance are necessary. Network density and distribution of accessible MDE has not been studied.
This descriptive research examined geographic network adequacy by comparing the density of persons with mobility impairments and location of Medicaid managed care practices with accessible MDE in Los Angeles County.
Medicaid managed care practices with MDE were mapped by ZIP Codes shaded to indicate the number of persons with mobility impairment. Zero-inflated negative binomial regression examined ZIP Code population characteristics as potential predictors of accessible MDE presence. Data sources were: (1) 2013–2016 primary care facility audit of Medicaid managed care network providers in LA County, aggregated by ZIP Code, and (2) LA County ZIP Code characteristics from the 2016 American Community Survey. ArcGIS was used for mapping and MPlus for the regression analysis.
No consistent association between the size of the mobility limited population, demographic characteristics, and presence of accessible MDE was observed or measured by regression. The observed low MDE density suggests network adequacy likely is not achieved in LA County.
Actions by state and federal agencies are necessary to increase accessible MDE and network adequacy by enforcing existing non-discrimination law and Medicaid regulations. |
doi_str_mv | 10.1016/j.dhjo.2022.101425 |
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This descriptive research examined geographic network adequacy by comparing the density of persons with mobility impairments and location of Medicaid managed care practices with accessible MDE in Los Angeles County.
Medicaid managed care practices with MDE were mapped by ZIP Codes shaded to indicate the number of persons with mobility impairment. Zero-inflated negative binomial regression examined ZIP Code population characteristics as potential predictors of accessible MDE presence. Data sources were: (1) 2013–2016 primary care facility audit of Medicaid managed care network providers in LA County, aggregated by ZIP Code, and (2) LA County ZIP Code characteristics from the 2016 American Community Survey. ArcGIS was used for mapping and MPlus for the regression analysis.
No consistent association between the size of the mobility limited population, demographic characteristics, and presence of accessible MDE was observed or measured by regression. The observed low MDE density suggests network adequacy likely is not achieved in LA County.
Actions by state and federal agencies are necessary to increase accessible MDE and network adequacy by enforcing existing non-discrimination law and Medicaid regulations.</description><identifier>ISSN: 1936-6574</identifier><identifier>EISSN: 1876-7583</identifier><identifier>DOI: 10.1016/j.dhjo.2022.101425</identifier><identifier>PMID: 36631363</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Accessible medical diagnostic equipment ; Accessible weight scale ; Diagnostic Equipment ; Disability ; Disabled Persons ; Health Facilities ; Height adjustable examination table ; Humans ; Medicaid ; Medicaid network adequacy ; Primary Health Care ; United States</subject><ispartof>Disability and health journal, 2023-04, Vol.16 (2), p.101425-101425, Article 101425</ispartof><rights>2022 The Authors</rights><rights>Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c400t-b011592eca63a6bbada1639571cf94482a203c9346cc64c5d87596b910099d0c3</citedby><cites>FETCH-LOGICAL-c400t-b011592eca63a6bbada1639571cf94482a203c9346cc64c5d87596b910099d0c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S193665742200187X$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36631363$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Mudrick, Nancy R.</creatorcontrib><creatorcontrib>Breslin, Mary Lou</creatorcontrib><creatorcontrib>Blackwell, Julia</creatorcontrib><creatorcontrib>Wang, Xiafei</creatorcontrib><creatorcontrib>Nielsen, Kyrian A.</creatorcontrib><title>Accessible medical diagnostic equipment in primary care: Assessing its geographic distribution for disability equity</title><title>Disability and health journal</title><addtitle>Disabil Health J</addtitle><description>Height adjustable examination tables, accessible weight scales, and lifts for transferring individuals on/off examination equipment enable delivery of equitable health care to persons with mobility impairment. Because most Medicaid-covered patients must utilize a managed care network, network providers with accessible medical diagnostic equipment (MDE) at proximate locations for travel time and distance are necessary. Network density and distribution of accessible MDE has not been studied.
This descriptive research examined geographic network adequacy by comparing the density of persons with mobility impairments and location of Medicaid managed care practices with accessible MDE in Los Angeles County.
Medicaid managed care practices with MDE were mapped by ZIP Codes shaded to indicate the number of persons with mobility impairment. Zero-inflated negative binomial regression examined ZIP Code population characteristics as potential predictors of accessible MDE presence. Data sources were: (1) 2013–2016 primary care facility audit of Medicaid managed care network providers in LA County, aggregated by ZIP Code, and (2) LA County ZIP Code characteristics from the 2016 American Community Survey. ArcGIS was used for mapping and MPlus for the regression analysis.
No consistent association between the size of the mobility limited population, demographic characteristics, and presence of accessible MDE was observed or measured by regression. The observed low MDE density suggests network adequacy likely is not achieved in LA County.
Actions by state and federal agencies are necessary to increase accessible MDE and network adequacy by enforcing existing non-discrimination law and Medicaid regulations.</description><subject>Accessible medical diagnostic equipment</subject><subject>Accessible weight scale</subject><subject>Diagnostic Equipment</subject><subject>Disability</subject><subject>Disabled Persons</subject><subject>Health Facilities</subject><subject>Height adjustable examination table</subject><subject>Humans</subject><subject>Medicaid</subject><subject>Medicaid network adequacy</subject><subject>Primary Health Care</subject><subject>United States</subject><issn>1936-6574</issn><issn>1876-7583</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kEtv2zAQhImiRfNo_0APBY-9yOVDpMSiFyNImgIBeknOBLVaO2vIokNSBfzvI9Vujz3tYjAzwHyMfZJiJYW0X3er_nkXV0ootQi1Mm_YpWwbWzWm1W_n32lbWdPUF-wq550QVrhWvmcX2lottdWXrKwBMGfqBuR77AnCwHsK2zHmQsDxZaLDHsfCaeSHRPuQjhxCwm98nfMSHLecSuZbjNsUDs9zpqdcEnVToTjyTUyLEDoaqBz_9JXjB_ZuE4aMH8_3mj3d3T7e3FcPv378vFk_VFALUapOSGmcQghWB9t1oQ_SamcaCRtX160KSmhwurYAtgbTt41xtnNSCOd6AfqafTn1HlJ8mTAXv6cMOAxhxDhlrxprRCNN085WdbJCijkn3PjzWi-FX2j7nV9o-4W2P9GeQ5_P_VM3w_sX-Yt3Nnw_GXBe-Zsw-QyEI8ygE0LxfaT_9b8CS8-SQQ</recordid><startdate>202304</startdate><enddate>202304</enddate><creator>Mudrick, Nancy R.</creator><creator>Breslin, Mary Lou</creator><creator>Blackwell, Julia</creator><creator>Wang, Xiafei</creator><creator>Nielsen, Kyrian A.</creator><general>Elsevier Inc</general><scope>6I.</scope><scope>AAFTH</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>202304</creationdate><title>Accessible medical diagnostic equipment in primary care: Assessing its geographic distribution for disability equity</title><author>Mudrick, Nancy R. ; Breslin, Mary Lou ; Blackwell, Julia ; Wang, Xiafei ; Nielsen, Kyrian A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c400t-b011592eca63a6bbada1639571cf94482a203c9346cc64c5d87596b910099d0c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Accessible medical diagnostic equipment</topic><topic>Accessible weight scale</topic><topic>Diagnostic Equipment</topic><topic>Disability</topic><topic>Disabled Persons</topic><topic>Health Facilities</topic><topic>Height adjustable examination table</topic><topic>Humans</topic><topic>Medicaid</topic><topic>Medicaid network adequacy</topic><topic>Primary Health Care</topic><topic>United States</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mudrick, Nancy R.</creatorcontrib><creatorcontrib>Breslin, Mary Lou</creatorcontrib><creatorcontrib>Blackwell, Julia</creatorcontrib><creatorcontrib>Wang, Xiafei</creatorcontrib><creatorcontrib>Nielsen, Kyrian A.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Disability and health journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mudrick, Nancy R.</au><au>Breslin, Mary Lou</au><au>Blackwell, Julia</au><au>Wang, Xiafei</au><au>Nielsen, Kyrian A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Accessible medical diagnostic equipment in primary care: Assessing its geographic distribution for disability equity</atitle><jtitle>Disability and health journal</jtitle><addtitle>Disabil Health J</addtitle><date>2023-04</date><risdate>2023</risdate><volume>16</volume><issue>2</issue><spage>101425</spage><epage>101425</epage><pages>101425-101425</pages><artnum>101425</artnum><issn>1936-6574</issn><eissn>1876-7583</eissn><abstract>Height adjustable examination tables, accessible weight scales, and lifts for transferring individuals on/off examination equipment enable delivery of equitable health care to persons with mobility impairment. Because most Medicaid-covered patients must utilize a managed care network, network providers with accessible medical diagnostic equipment (MDE) at proximate locations for travel time and distance are necessary. Network density and distribution of accessible MDE has not been studied.
This descriptive research examined geographic network adequacy by comparing the density of persons with mobility impairments and location of Medicaid managed care practices with accessible MDE in Los Angeles County.
Medicaid managed care practices with MDE were mapped by ZIP Codes shaded to indicate the number of persons with mobility impairment. Zero-inflated negative binomial regression examined ZIP Code population characteristics as potential predictors of accessible MDE presence. Data sources were: (1) 2013–2016 primary care facility audit of Medicaid managed care network providers in LA County, aggregated by ZIP Code, and (2) LA County ZIP Code characteristics from the 2016 American Community Survey. ArcGIS was used for mapping and MPlus for the regression analysis.
No consistent association between the size of the mobility limited population, demographic characteristics, and presence of accessible MDE was observed or measured by regression. The observed low MDE density suggests network adequacy likely is not achieved in LA County.
Actions by state and federal agencies are necessary to increase accessible MDE and network adequacy by enforcing existing non-discrimination law and Medicaid regulations.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>36631363</pmid><doi>10.1016/j.dhjo.2022.101425</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Accessible medical diagnostic equipment Accessible weight scale Diagnostic Equipment Disability Disabled Persons Health Facilities Height adjustable examination table Humans Medicaid Medicaid network adequacy Primary Health Care United States |
title | Accessible medical diagnostic equipment in primary care: Assessing its geographic distribution for disability equity |
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