Telemedicine Use in Orthopaedic Surgery Varies by Race, Ethnicity, Primary Language, and Insurance Status
Healthcare disparities are well documented across multiple subspecialties in orthopaedics. The widespread implementation of telemedicine risks worsening these disparities if not carefully executed, despite original assumptions that telemedicine improves overall access to care. Telemedicine also pose...
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Veröffentlicht in: | Clinical orthopaedics and related research 2021-07, Vol.479 (7), p.1417-1425 |
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description | Healthcare disparities are well documented across multiple subspecialties in orthopaedics. The widespread implementation of telemedicine risks worsening these disparities if not carefully executed, despite original assumptions that telemedicine improves overall access to care. Telemedicine also poses unique challenges such as potential language or technological barriers that may alter previously described patterns in orthopaedic disparities.
Are the proportions of patients who use telemedicine across orthopaedic services different among (1) racial and ethnic minorities, (2) non-English speakers, and (3) patients insured through Medicaid during a 10-week period after the implementation of telemedicine in our healthcare system compared with in-person visits during a similar time period in 2019?
This was a retrospective comparative study using electronic medical record data to compare new patients establishing orthopaedic care via outpatient telemedicine at two academic urban medical centers between March 2020 and May 2020 with new orthopaedic patients during the same 10-week period in 2019. A total of 11,056 patients were included for analysis, with 1760 in the virtual group and 9296 in the control group. Unadjusted analyses demonstrated patients in the virtual group were younger (median age 57 years versus 59 years; p < 0.001), but there were no differences with regard to gender (56% female versus 56% female; p = 0.66). We used self-reported race or ethnicity as our primary independent variable, with primary language and insurance status considered secondarily. Unadjusted and multivariable adjusted analyses were performed for our primary and secondary predictors using logistic regression. We also assessed interactions between race or ethnicity, primary language, and insurance type.
After adjusting for age, gender, subspecialty, insurance, and median household income, we found that patients who were Hispanic (odds ratio 0.59 [95% confidence interval 0.39 to 0.91]; p = 0.02) or Asian were less likely (OR 0.73 [95% CI 0.53 to 0.99]; p = 0.04) to be seen through telemedicine than were patients who were white. After controlling for confounding variables, we also found that speakers of languages other than English or Spanish were less likely to have a telemedicine visit than were people whose primary language was English (OR 0.34 [95% CI 0.18 to 0.65]; p = 0.001), and that patients insured through Medicaid were less likely to be seen via telemedicine than were pa |
doi_str_mv | 10.1097/CORR.0000000000001775 |
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Are the proportions of patients who use telemedicine across orthopaedic services different among (1) racial and ethnic minorities, (2) non-English speakers, and (3) patients insured through Medicaid during a 10-week period after the implementation of telemedicine in our healthcare system compared with in-person visits during a similar time period in 2019?
This was a retrospective comparative study using electronic medical record data to compare new patients establishing orthopaedic care via outpatient telemedicine at two academic urban medical centers between March 2020 and May 2020 with new orthopaedic patients during the same 10-week period in 2019. A total of 11,056 patients were included for analysis, with 1760 in the virtual group and 9296 in the control group. Unadjusted analyses demonstrated patients in the virtual group were younger (median age 57 years versus 59 years; p < 0.001), but there were no differences with regard to gender (56% female versus 56% female; p = 0.66). We used self-reported race or ethnicity as our primary independent variable, with primary language and insurance status considered secondarily. Unadjusted and multivariable adjusted analyses were performed for our primary and secondary predictors using logistic regression. We also assessed interactions between race or ethnicity, primary language, and insurance type.
After adjusting for age, gender, subspecialty, insurance, and median household income, we found that patients who were Hispanic (odds ratio 0.59 [95% confidence interval 0.39 to 0.91]; p = 0.02) or Asian were less likely (OR 0.73 [95% CI 0.53 to 0.99]; p = 0.04) to be seen through telemedicine than were patients who were white. After controlling for confounding variables, we also found that speakers of languages other than English or Spanish were less likely to have a telemedicine visit than were people whose primary language was English (OR 0.34 [95% CI 0.18 to 0.65]; p = 0.001), and that patients insured through Medicaid were less likely to be seen via telemedicine than were patients who were privately insured (OR 0.83 [95% CI 0.69 to 0.98]; p = 0.03).
Despite initial promises that telemedicine would help to bridge gaps in healthcare, our results demonstrate disparities in orthopaedic telemedicine use based on race or ethnicity, language, and insurance type. The telemedicine group was slightly younger, which we do not believe undermines the findings. As healthcare moves toward increased telemedicine use, we suggest several approaches to ensure that patients of certain racial, ethnic, or language groups do not experience disparate barriers to care. These might include individual patient- or provider-level approaches like expanded telemedicine schedules to accommodate weekends and evenings, institutional investment in culturally conscious outreach materials such as advertisements on community transport systems, or government-level provisions such as reimbursement for telephone-only encounters.
Level III, therapeutic study.</description><identifier>ISSN: 0009-921X</identifier><identifier>EISSN: 1528-1132</identifier><identifier>DOI: 10.1097/CORR.0000000000001775</identifier><identifier>PMID: 33982979</identifier><language>eng</language><publisher>United States: Wolters Kluwer</publisher><subject><![CDATA[Adult ; Electronic medical records ; Ethnicity ; Ethnicity - statistics & numerical data ; Female ; Gender ; Health care ; Health care access ; Health Plan Implementation ; Health Services Accessibility ; Healthcare Disparities - ethnology ; Healthcare Disparities - statistics & numerical data ; Humans ; Insurance Coverage - statistics & numerical data ; Language ; Male ; Medicaid ; Middle Aged ; Minority & ethnic groups ; Minority Groups - statistics & numerical data ; Odds Ratio ; Orthopedic Procedures - statistics & numerical data ; Orthopedics ; Patients ; Race ; Racial Groups - statistics & numerical data ; Retrospective Studies ; Telemedicine ; Telemedicine - methods ; Telemedicine - statistics & numerical data ; United States]]></subject><ispartof>Clinical orthopaedics and related research, 2021-07, Vol.479 (7), p.1417-1425</ispartof><rights>Wolters Kluwer</rights><rights>Copyright © 2021 by the Association of Bone and Joint Surgeons.</rights><rights>2021 by the Association of Bone and Joint Surgeons</rights><rights>2021 by the Association of Bone and Joint Surgeons 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5363-a49adf0695ec41a96fa72a9041dac9d087d190f7ccf83e5ae24e01f28bd47f693</citedby><cites>FETCH-LOGICAL-c5363-a49adf0695ec41a96fa72a9041dac9d087d190f7ccf83e5ae24e01f28bd47f693</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8208394/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8208394/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,724,777,781,882,27906,27907,53773,53775</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33982979$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Xiong, Grace</creatorcontrib><creatorcontrib>Greene, Nattaly E.</creatorcontrib><creatorcontrib>Lightsey, Harry M.</creatorcontrib><creatorcontrib>Crawford, Alexander M.</creatorcontrib><creatorcontrib>Striano, Brendan M.</creatorcontrib><creatorcontrib>Simpson, Andrew K.</creatorcontrib><creatorcontrib>Schoenfeld, Andrew J.</creatorcontrib><title>Telemedicine Use in Orthopaedic Surgery Varies by Race, Ethnicity, Primary Language, and Insurance Status</title><title>Clinical orthopaedics and related research</title><addtitle>Clin Orthop Relat Res</addtitle><description>Healthcare disparities are well documented across multiple subspecialties in orthopaedics. The widespread implementation of telemedicine risks worsening these disparities if not carefully executed, despite original assumptions that telemedicine improves overall access to care. Telemedicine also poses unique challenges such as potential language or technological barriers that may alter previously described patterns in orthopaedic disparities.
Are the proportions of patients who use telemedicine across orthopaedic services different among (1) racial and ethnic minorities, (2) non-English speakers, and (3) patients insured through Medicaid during a 10-week period after the implementation of telemedicine in our healthcare system compared with in-person visits during a similar time period in 2019?
This was a retrospective comparative study using electronic medical record data to compare new patients establishing orthopaedic care via outpatient telemedicine at two academic urban medical centers between March 2020 and May 2020 with new orthopaedic patients during the same 10-week period in 2019. A total of 11,056 patients were included for analysis, with 1760 in the virtual group and 9296 in the control group. Unadjusted analyses demonstrated patients in the virtual group were younger (median age 57 years versus 59 years; p < 0.001), but there were no differences with regard to gender (56% female versus 56% female; p = 0.66). We used self-reported race or ethnicity as our primary independent variable, with primary language and insurance status considered secondarily. Unadjusted and multivariable adjusted analyses were performed for our primary and secondary predictors using logistic regression. We also assessed interactions between race or ethnicity, primary language, and insurance type.
After adjusting for age, gender, subspecialty, insurance, and median household income, we found that patients who were Hispanic (odds ratio 0.59 [95% confidence interval 0.39 to 0.91]; p = 0.02) or Asian were less likely (OR 0.73 [95% CI 0.53 to 0.99]; p = 0.04) to be seen through telemedicine than were patients who were white. After controlling for confounding variables, we also found that speakers of languages other than English or Spanish were less likely to have a telemedicine visit than were people whose primary language was English (OR 0.34 [95% CI 0.18 to 0.65]; p = 0.001), and that patients insured through Medicaid were less likely to be seen via telemedicine than were patients who were privately insured (OR 0.83 [95% CI 0.69 to 0.98]; p = 0.03).
Despite initial promises that telemedicine would help to bridge gaps in healthcare, our results demonstrate disparities in orthopaedic telemedicine use based on race or ethnicity, language, and insurance type. The telemedicine group was slightly younger, which we do not believe undermines the findings. As healthcare moves toward increased telemedicine use, we suggest several approaches to ensure that patients of certain racial, ethnic, or language groups do not experience disparate barriers to care. These might include individual patient- or provider-level approaches like expanded telemedicine schedules to accommodate weekends and evenings, institutional investment in culturally conscious outreach materials such as advertisements on community transport systems, or government-level provisions such as reimbursement for telephone-only encounters.
Level III, therapeutic study.</description><subject>Adult</subject><subject>Electronic medical records</subject><subject>Ethnicity</subject><subject>Ethnicity - statistics & numerical data</subject><subject>Female</subject><subject>Gender</subject><subject>Health care</subject><subject>Health care access</subject><subject>Health Plan Implementation</subject><subject>Health Services Accessibility</subject><subject>Healthcare Disparities - ethnology</subject><subject>Healthcare Disparities - statistics & numerical data</subject><subject>Humans</subject><subject>Insurance Coverage - statistics & numerical data</subject><subject>Language</subject><subject>Male</subject><subject>Medicaid</subject><subject>Middle Aged</subject><subject>Minority & ethnic groups</subject><subject>Minority Groups - statistics & numerical data</subject><subject>Odds Ratio</subject><subject>Orthopedic Procedures - statistics & numerical data</subject><subject>Orthopedics</subject><subject>Patients</subject><subject>Race</subject><subject>Racial Groups - statistics & numerical data</subject><subject>Retrospective Studies</subject><subject>Telemedicine</subject><subject>Telemedicine - methods</subject><subject>Telemedicine - statistics & numerical data</subject><subject>United States</subject><issn>0009-921X</issn><issn>1528-1132</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpdUV1vEzEQtBAVDYGfALLESx96xR935_MLEooKVIqUKm0Rb9bGt5dzufiCfdcq_x6nKVWpX6ydnR3t7BDygbMzzrT6PFssl2fs2eNKFa_IhBeiyjiX4jWZJFRnWvBfx-RtjLeplHkh3pBjKXUltNIT4q6xww3WzjqP9CYidZ4uwtD2W9ij9GoMaww7-hOCw0hXO7oEi6f0fGh9Ghp2p_QyuA0kyhz8eoR1aoKv6YWPYwBvkV4NMIzxHTlqoIv4_vGfkptv59ezH9l88f1i9nWe2UKWMoNcQ92wUhdocw66bEAJ0CznNVhds0rVXLNGWdtUEgtAkSPjjahWda6aUssp-XLQ3Y6rZMyiHwJ0ZntY0vTgzP8d71qz7u9MJVgldZ4ETh4FQv9nxDiYjYsWuw489mM0ohClZIqna07JpxfU234MPtkzouRCiYLLPas4sGzoYwzYPC3DmdmHafZhmpdhprmPz508Tf1LLxHyA-G-7wYM8Xc33mMwLUI3tA96klVlJpjgTKUqe4DkX0itquo</recordid><startdate>20210701</startdate><enddate>20210701</enddate><creator>Xiong, Grace</creator><creator>Greene, Nattaly E.</creator><creator>Lightsey, Harry M.</creator><creator>Crawford, Alexander M.</creator><creator>Striano, Brendan M.</creator><creator>Simpson, Andrew K.</creator><creator>Schoenfeld, Andrew J.</creator><general>Wolters Kluwer</general><general>Lippincott Williams & Wilkins Ovid Technologies</general><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>7QP</scope><scope>7T5</scope><scope>H94</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20210701</creationdate><title>Telemedicine Use in Orthopaedic Surgery Varies by Race, Ethnicity, Primary Language, and Insurance Status</title><author>Xiong, Grace ; 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The widespread implementation of telemedicine risks worsening these disparities if not carefully executed, despite original assumptions that telemedicine improves overall access to care. Telemedicine also poses unique challenges such as potential language or technological barriers that may alter previously described patterns in orthopaedic disparities.
Are the proportions of patients who use telemedicine across orthopaedic services different among (1) racial and ethnic minorities, (2) non-English speakers, and (3) patients insured through Medicaid during a 10-week period after the implementation of telemedicine in our healthcare system compared with in-person visits during a similar time period in 2019?
This was a retrospective comparative study using electronic medical record data to compare new patients establishing orthopaedic care via outpatient telemedicine at two academic urban medical centers between March 2020 and May 2020 with new orthopaedic patients during the same 10-week period in 2019. A total of 11,056 patients were included for analysis, with 1760 in the virtual group and 9296 in the control group. Unadjusted analyses demonstrated patients in the virtual group were younger (median age 57 years versus 59 years; p < 0.001), but there were no differences with regard to gender (56% female versus 56% female; p = 0.66). We used self-reported race or ethnicity as our primary independent variable, with primary language and insurance status considered secondarily. Unadjusted and multivariable adjusted analyses were performed for our primary and secondary predictors using logistic regression. We also assessed interactions between race or ethnicity, primary language, and insurance type.
After adjusting for age, gender, subspecialty, insurance, and median household income, we found that patients who were Hispanic (odds ratio 0.59 [95% confidence interval 0.39 to 0.91]; p = 0.02) or Asian were less likely (OR 0.73 [95% CI 0.53 to 0.99]; p = 0.04) to be seen through telemedicine than were patients who were white. After controlling for confounding variables, we also found that speakers of languages other than English or Spanish were less likely to have a telemedicine visit than were people whose primary language was English (OR 0.34 [95% CI 0.18 to 0.65]; p = 0.001), and that patients insured through Medicaid were less likely to be seen via telemedicine than were patients who were privately insured (OR 0.83 [95% CI 0.69 to 0.98]; p = 0.03).
Despite initial promises that telemedicine would help to bridge gaps in healthcare, our results demonstrate disparities in orthopaedic telemedicine use based on race or ethnicity, language, and insurance type. The telemedicine group was slightly younger, which we do not believe undermines the findings. As healthcare moves toward increased telemedicine use, we suggest several approaches to ensure that patients of certain racial, ethnic, or language groups do not experience disparate barriers to care. These might include individual patient- or provider-level approaches like expanded telemedicine schedules to accommodate weekends and evenings, institutional investment in culturally conscious outreach materials such as advertisements on community transport systems, or government-level provisions such as reimbursement for telephone-only encounters.
Level III, therapeutic study.</abstract><cop>United States</cop><pub>Wolters Kluwer</pub><pmid>33982979</pmid><doi>10.1097/CORR.0000000000001775</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adult Electronic medical records Ethnicity Ethnicity - statistics & numerical data Female Gender Health care Health care access Health Plan Implementation Health Services Accessibility Healthcare Disparities - ethnology Healthcare Disparities - statistics & numerical data Humans Insurance Coverage - statistics & numerical data Language Male Medicaid Middle Aged Minority & ethnic groups Minority Groups - statistics & numerical data Odds Ratio Orthopedic Procedures - statistics & numerical data Orthopedics Patients Race Racial Groups - statistics & numerical data Retrospective Studies Telemedicine Telemedicine - methods Telemedicine - statistics & numerical data United States |
title | Telemedicine Use in Orthopaedic Surgery Varies by Race, Ethnicity, Primary Language, and Insurance Status |
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