Temporal Trends in Telehealth Availability in Mental Health Treatment Settings: Differences in Growth by State Rurality, 2015–2020
We sought to investigate temporal trends in telehealth availability among outpatient mental health treatment facilities and differences in the pace of telehealth growth by state urbanicity and rurality. We used the National Mental Health Services Survey (2015–2020) to identify outpatient mental heal...
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| Veröffentlicht in: | Journal of urban health 2023-12, Vol.100 (6), p.1149-1158 |
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| creator | Pro, George Fairman, Brian Baloh, Jure Willis, Don Montgomery, Broome E. E. |
| description | We sought to investigate temporal trends in telehealth availability among outpatient mental health treatment facilities and differences in the pace of telehealth growth by state urbanicity and rurality. We used the National Mental Health Services Survey (2015–2020) to identify outpatient mental health treatment facilities in the US (
N
= 28,989 facilities; 2015
n
= 5,018; 2020
n
= 4,889). We used logistic regression to model telehealth, predicted by time, state rurality (1 to 10% rural, 10 to |
| doi_str_mv | 10.1007/s11524-023-00795-y |
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| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10728410</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2894724881</sourcerecordid><originalsourceid>FETCH-LOGICAL-c431t-b504cf7916d806035cf5bc4ade0a1ae307a232a7d0e90f99df515088e82c28aa3</originalsourceid><addsrcrecordid>eNp9kctu1TAQhiNERUvhBVigSGxYEBhfkthsUFXoRSpCooe15SSTc1zlcmo7Rdmx4A14wz4J06aUy4KVL_83_4z9J8kzBq8ZQPkmMJZzmQEXGR11ns0Pkj0mC5VxVeiHtAetMyEL2E0eh3ABwApZ8kfJrlDAeA58L_m-wn47etulK49DE1I3pCvscIO2i5v04Mq6zlauc3G-kT7iEIk9WVQqsbGnq_QcY3TDOrxN37u2RbKq8dbr2I9fiazm9DzaiOnniXqR2auUA8uvv_3gwOFJstPaLuDTu3U_-XL0YXV4kp19Oj49PDjLailYzKocZN2WmhWNggJEXrd5VUvbIFhmUUBpueC2bAA1tFo3bc5yUAoVr7myVuwn7xbf7VT12NQ0OU1jtt711s9mtM78rQxuY9bjlWFQciUZkMPLOwc_Xk4YouldqLHr7IDjFAxXmn5YKsUIffEPejFOfqD3Ga5BMCkoAaL4QtV-DMFjez8NA3OTsllSNpSyuU3ZzFT0_M933Jf8ipUAsQCBpGGN_nfv_9j-BPTNtHs</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2903143250</pqid></control><display><type>article</type><title>Temporal Trends in Telehealth Availability in Mental Health Treatment Settings: Differences in Growth by State Rurality, 2015–2020</title><source>MEDLINE</source><source>Alma/SFX Local Collection</source><source>SpringerLink Journals - AutoHoldings</source><creator>Pro, George ; Fairman, Brian ; Baloh, Jure ; Willis, Don ; Montgomery, Broome E. E.</creator><creatorcontrib>Pro, George ; Fairman, Brian ; Baloh, Jure ; Willis, Don ; Montgomery, Broome E. E.</creatorcontrib><description>We sought to investigate temporal trends in telehealth availability among outpatient mental health treatment facilities and differences in the pace of telehealth growth by state urbanicity and rurality. We used the National Mental Health Services Survey (2015–2020) to identify outpatient mental health treatment facilities in the US (
N
= 28,989 facilities; 2015
n
= 5,018; 2020
n
= 4,889). We used logistic regression to model telehealth, predicted by time, state rurality (1 to 10% rural, 10 to < 20%, 20 to < 30%, or
≥
30%), and their interaction, and adjusted for relevant covariates. We estimated the predicted probability of telehealth based on our model. We estimated effects with and without data from 2020 to assess whether the rapid and widespread adoption of telehealth during the COVID-19 pandemic changed the rural/urban trajectories of telehealth availability. We found that telehealth grew fastest in more urban states (year*rurality interaction
p
< 0.0001). Between 2015 and 2020, the predicted probability of telehealth in more urban states increased by 51 percentage points (from 9 to 61%), whereas telehealth in more rural states increased by 38 percentage points (from 23 to 61%). Predicted telehealth also varied widely by state, ranging from more than 75% of facilities (RI, OR) to below 20% (VT, KY). Health systems and new technological innovations must consider the unique challenges faced by urban populations and how best practices may be adapted to meet the growing urban demand. We framed our findings around the need for policies that minimize barriers to telehealth.</description><identifier>ISSN: 1099-3460</identifier><identifier>ISSN: 1468-2869</identifier><identifier>EISSN: 1468-2869</identifier><identifier>DOI: 10.1007/s11524-023-00795-y</identifier><identifier>PMID: 38012502</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Availability ; Best practice ; COVID-19 ; COVID-19 - epidemiology ; Epidemiology ; Health Informatics ; Health services ; Humans ; Medicine ; Medicine & Public Health ; Mental Health ; Mental health care ; Original ; Original Article ; Pandemics ; Public Health ; Regression models ; Rural Population ; Statistical analysis ; Technological change ; Telemedicine ; Trends ; United States ; Urban populations</subject><ispartof>Journal of urban health, 2023-12, Vol.100 (6), p.1149-1158</ispartof><rights>The New York Academy of Medicine 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2023. The New York Academy of Medicine.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c431t-b504cf7916d806035cf5bc4ade0a1ae307a232a7d0e90f99df515088e82c28aa3</citedby><cites>FETCH-LOGICAL-c431t-b504cf7916d806035cf5bc4ade0a1ae307a232a7d0e90f99df515088e82c28aa3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11524-023-00795-y$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11524-023-00795-y$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>230,314,780,784,885,27922,27923,41486,42555,51317</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38012502$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Pro, George</creatorcontrib><creatorcontrib>Fairman, Brian</creatorcontrib><creatorcontrib>Baloh, Jure</creatorcontrib><creatorcontrib>Willis, Don</creatorcontrib><creatorcontrib>Montgomery, Broome E. E.</creatorcontrib><title>Temporal Trends in Telehealth Availability in Mental Health Treatment Settings: Differences in Growth by State Rurality, 2015–2020</title><title>Journal of urban health</title><addtitle>J Urban Health</addtitle><addtitle>J Urban Health</addtitle><description>We sought to investigate temporal trends in telehealth availability among outpatient mental health treatment facilities and differences in the pace of telehealth growth by state urbanicity and rurality. We used the National Mental Health Services Survey (2015–2020) to identify outpatient mental health treatment facilities in the US (
N
= 28,989 facilities; 2015
n
= 5,018; 2020
n
= 4,889). We used logistic regression to model telehealth, predicted by time, state rurality (1 to 10% rural, 10 to < 20%, 20 to < 30%, or
≥
30%), and their interaction, and adjusted for relevant covariates. We estimated the predicted probability of telehealth based on our model. We estimated effects with and without data from 2020 to assess whether the rapid and widespread adoption of telehealth during the COVID-19 pandemic changed the rural/urban trajectories of telehealth availability. We found that telehealth grew fastest in more urban states (year*rurality interaction
p
< 0.0001). Between 2015 and 2020, the predicted probability of telehealth in more urban states increased by 51 percentage points (from 9 to 61%), whereas telehealth in more rural states increased by 38 percentage points (from 23 to 61%). Predicted telehealth also varied widely by state, ranging from more than 75% of facilities (RI, OR) to below 20% (VT, KY). Health systems and new technological innovations must consider the unique challenges faced by urban populations and how best practices may be adapted to meet the growing urban demand. We framed our findings around the need for policies that minimize barriers to telehealth.</description><subject>Availability</subject><subject>Best practice</subject><subject>COVID-19</subject><subject>COVID-19 - epidemiology</subject><subject>Epidemiology</subject><subject>Health Informatics</subject><subject>Health services</subject><subject>Humans</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Mental Health</subject><subject>Mental health care</subject><subject>Original</subject><subject>Original Article</subject><subject>Pandemics</subject><subject>Public Health</subject><subject>Regression models</subject><subject>Rural Population</subject><subject>Statistical analysis</subject><subject>Technological change</subject><subject>Telemedicine</subject><subject>Trends</subject><subject>United States</subject><subject>Urban populations</subject><issn>1099-3460</issn><issn>1468-2869</issn><issn>1468-2869</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kctu1TAQhiNERUvhBVigSGxYEBhfkthsUFXoRSpCooe15SSTc1zlcmo7Rdmx4A14wz4J06aUy4KVL_83_4z9J8kzBq8ZQPkmMJZzmQEXGR11ns0Pkj0mC5VxVeiHtAetMyEL2E0eh3ABwApZ8kfJrlDAeA58L_m-wn47etulK49DE1I3pCvscIO2i5v04Mq6zlauc3G-kT7iEIk9WVQqsbGnq_QcY3TDOrxN37u2RbKq8dbr2I9fiazm9DzaiOnniXqR2auUA8uvv_3gwOFJstPaLuDTu3U_-XL0YXV4kp19Oj49PDjLailYzKocZN2WmhWNggJEXrd5VUvbIFhmUUBpueC2bAA1tFo3bc5yUAoVr7myVuwn7xbf7VT12NQ0OU1jtt711s9mtM78rQxuY9bjlWFQciUZkMPLOwc_Xk4YouldqLHr7IDjFAxXmn5YKsUIffEPejFOfqD3Ga5BMCkoAaL4QtV-DMFjez8NA3OTsllSNpSyuU3ZzFT0_M933Jf8ipUAsQCBpGGN_nfv_9j-BPTNtHs</recordid><startdate>20231201</startdate><enddate>20231201</enddate><creator>Pro, George</creator><creator>Fairman, Brian</creator><creator>Baloh, Jure</creator><creator>Willis, Don</creator><creator>Montgomery, Broome E. E.</creator><general>Springer US</general><general>Springer Nature B.V</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>0-V</scope><scope>3V.</scope><scope>7T2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88J</scope><scope>8AO</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M2R</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20231201</creationdate><title>Temporal Trends in Telehealth Availability in Mental Health Treatment Settings: Differences in Growth by State Rurality, 2015–2020</title><author>Pro, George ; Fairman, Brian ; Baloh, Jure ; Willis, Don ; Montgomery, Broome E. E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c431t-b504cf7916d806035cf5bc4ade0a1ae307a232a7d0e90f99df515088e82c28aa3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Availability</topic><topic>Best practice</topic><topic>COVID-19</topic><topic>COVID-19 - epidemiology</topic><topic>Epidemiology</topic><topic>Health Informatics</topic><topic>Health services</topic><topic>Humans</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Mental Health</topic><topic>Mental health care</topic><topic>Original</topic><topic>Original Article</topic><topic>Pandemics</topic><topic>Public Health</topic><topic>Regression models</topic><topic>Rural Population</topic><topic>Statistical analysis</topic><topic>Technological change</topic><topic>Telemedicine</topic><topic>Trends</topic><topic>United States</topic><topic>Urban populations</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pro, George</creatorcontrib><creatorcontrib>Fairman, Brian</creatorcontrib><creatorcontrib>Baloh, Jure</creatorcontrib><creatorcontrib>Willis, Don</creatorcontrib><creatorcontrib>Montgomery, Broome E. 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E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Temporal Trends in Telehealth Availability in Mental Health Treatment Settings: Differences in Growth by State Rurality, 2015–2020</atitle><jtitle>Journal of urban health</jtitle><stitle>J Urban Health</stitle><addtitle>J Urban Health</addtitle><date>2023-12-01</date><risdate>2023</risdate><volume>100</volume><issue>6</issue><spage>1149</spage><epage>1158</epage><pages>1149-1158</pages><issn>1099-3460</issn><issn>1468-2869</issn><eissn>1468-2869</eissn><abstract>We sought to investigate temporal trends in telehealth availability among outpatient mental health treatment facilities and differences in the pace of telehealth growth by state urbanicity and rurality. We used the National Mental Health Services Survey (2015–2020) to identify outpatient mental health treatment facilities in the US (
N
= 28,989 facilities; 2015
n
= 5,018; 2020
n
= 4,889). We used logistic regression to model telehealth, predicted by time, state rurality (1 to 10% rural, 10 to < 20%, 20 to < 30%, or
≥
30%), and their interaction, and adjusted for relevant covariates. We estimated the predicted probability of telehealth based on our model. We estimated effects with and without data from 2020 to assess whether the rapid and widespread adoption of telehealth during the COVID-19 pandemic changed the rural/urban trajectories of telehealth availability. We found that telehealth grew fastest in more urban states (year*rurality interaction
p
< 0.0001). Between 2015 and 2020, the predicted probability of telehealth in more urban states increased by 51 percentage points (from 9 to 61%), whereas telehealth in more rural states increased by 38 percentage points (from 23 to 61%). Predicted telehealth also varied widely by state, ranging from more than 75% of facilities (RI, OR) to below 20% (VT, KY). Health systems and new technological innovations must consider the unique challenges faced by urban populations and how best practices may be adapted to meet the growing urban demand. We framed our findings around the need for policies that minimize barriers to telehealth.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>38012502</pmid><doi>10.1007/s11524-023-00795-y</doi><tpages>10</tpages></addata></record> |
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| ispartof | Journal of urban health, 2023-12, Vol.100 (6), p.1149-1158 |
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| subjects | Availability Best practice COVID-19 COVID-19 - epidemiology Epidemiology Health Informatics Health services Humans Medicine Medicine & Public Health Mental Health Mental health care Original Original Article Pandemics Public Health Regression models Rural Population Statistical analysis Technological change Telemedicine Trends United States Urban populations |
| title | Temporal Trends in Telehealth Availability in Mental Health Treatment Settings: Differences in Growth by State Rurality, 2015–2020 |
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