Using a Real-Time Locating System to Evaluate the Impact of Telemedicine in an Emergency Department During COVID-19: Observational Study
Background: Telemedicine has been deployed by health care systems in response to the COVID-19 pandemic to enable health care workers to provide remote care for both outpatients and inpatients. Although it is reasonable to suspect telemedicine visits limit unnecessary personal contact and thus decrea...
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| Veröffentlicht in: | Journal of medical Internet research 2021-07, Vol.23 (7), p.e29240-e29240, Article 29240 |
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| creator | Patel, Birju Vilendrer, Stacie Kling, Samantha M. R. Brown, Ian Ribeira, Ryan Eisenberg, Matthew Sharp, Christopher |
| description | Background: Telemedicine has been deployed by health care systems in response to the COVID-19 pandemic to enable health care workers to provide remote care for both outpatients and inpatients. Although it is reasonable to suspect telemedicine visits limit unnecessary personal contact and thus decrease the risk of infection transmission, the impact of the use of such technology on clinician workflows in the emergency department is unknown.
Objective: This study aimed to use a real-time locating system (RTLS) to evaluate the impact of a new telemedicine platform, which permitted clinicians located outside patient rooms to interact with patients who were under isolation precautions in the emergency department, on in-person interaction between health care workers and patients.
Methods: A pre-post analysis was conducted using a badge-based RTLS platform to collect movement data including entrances and duration of stay within patient rooms of the emergency department for nursing and physician staff. Movement data was captured between March 2, 2020, the date of the first patient screened for COVID-19 in the emergency department, and April 20, 2020. A new telemedicine platform was deployed on March 29, 2020. The number of entrances and duration of in-person interactions per patient encounter, adjusted for patient length of stay, were obtained for pre- and postimplementation phases and compared with t tests to determine statistical significance.
Results: There were 15,741 RTLS events linked to 2662 encounters for patients screened for COVID-19. There was no significant change in the number of in-person interactions between the pre- and postimplementation phases for both nurses (5.7 vs 7.0 entrances per patient, P=.07) and physicians (1.3 vs 1.5 entrances per patient, P=.12). Total duration of in-person interactions did not change (56.4 vs 55.2 minutes per patient, P=.74) despite significant increases in telemedicine videoconference frequency (0.6 vs 1.3 videoconferences per patient, P |
| doi_str_mv | 10.2196/29240 |
| format | Article |
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Objective: This study aimed to use a real-time locating system (RTLS) to evaluate the impact of a new telemedicine platform, which permitted clinicians located outside patient rooms to interact with patients who were under isolation precautions in the emergency department, on in-person interaction between health care workers and patients.
Methods: A pre-post analysis was conducted using a badge-based RTLS platform to collect movement data including entrances and duration of stay within patient rooms of the emergency department for nursing and physician staff. Movement data was captured between March 2, 2020, the date of the first patient screened for COVID-19 in the emergency department, and April 20, 2020. A new telemedicine platform was deployed on March 29, 2020. The number of entrances and duration of in-person interactions per patient encounter, adjusted for patient length of stay, were obtained for pre- and postimplementation phases and compared with t tests to determine statistical significance.
Results: There were 15,741 RTLS events linked to 2662 encounters for patients screened for COVID-19. There was no significant change in the number of in-person interactions between the pre- and postimplementation phases for both nurses (5.7 vs 7.0 entrances per patient, P=.07) and physicians (1.3 vs 1.5 entrances per patient, P=.12). Total duration of in-person interactions did not change (56.4 vs 55.2 minutes per patient, P=.74) despite significant increases in telemedicine videoconference frequency (0.6 vs 1.3 videoconferences per patient, P<.001 for change in daily average) and duration (4.3 vs 12.3 minutes per patient, P<.001 for change in daily average).
Conclusions: Telemedicine was rapidly adopted with the intent of minimizing pathogen exposure to health care workers during the COVID-19 pandemic, yet RTLS movement data did not reveal significant changes for in-person interactions between staff and patients under investigation for COVID-19 infection. Additional research is needed to better understand how telemedicine technology may be better incorporated into emergency departments to improve workflows for frontline health care clinicians.</description><identifier>ISSN: 1438-8871</identifier><identifier>ISSN: 1439-4456</identifier><identifier>EISSN: 1438-8871</identifier><identifier>DOI: 10.2196/29240</identifier><identifier>PMID: 34236993</identifier><language>eng</language><publisher>TORONTO: Jmir Publications, Inc</publisher><subject><![CDATA[Averages ; Changes ; Coronaviruses ; COVID-19 ; COVID-19 - diagnosis ; COVID-19 - epidemiology ; COVID-19 - prevention & control ; COVID-19 diagnostic tests ; Cross Infection - prevention & control ; Disease transmission ; Electronic health records ; Emergency medical care ; Emergency Service, Hospital - organization & administration ; Emergency services ; Health Care Sciences & Services ; Health Personnel - organization & administration ; Humans ; Infections ; Length of stay ; Life Sciences & Biomedicine ; Medical Informatics ; Medical personnel ; Nurses ; Observational studies ; Original Paper ; Outpatients ; Pandemics ; Patient communication ; Patients ; Personal protective equipment ; Physicians ; Precautions ; SARS-CoV-2 ; Science & Technology ; Sensors ; Severe acute respiratory syndrome coronavirus 2 ; Statistical significance ; Technology ; Telemedicine ; Time Factors ; Video conferencing ; Workers ; Workflow]]></subject><ispartof>Journal of medical Internet research, 2021-07, Vol.23 (7), p.e29240-e29240, Article 29240</ispartof><rights>Birju Patel, Stacie Vilendrer, Samantha M R Kling, Ian Brown, Ryan Ribeira, Matthew Eisenberg, Christopher Sharp. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 26.07.2021.</rights><rights>2021. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Birju Patel, Stacie Vilendrer, Samantha M R Kling, Ian Brown, Ryan Ribeira, Matthew Eisenberg, Christopher Sharp. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 26.07.2021. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>true</woscitedreferencessubscribed><woscitedreferencescount>5</woscitedreferencescount><woscitedreferencesoriginalsourcerecordid>wos000678771200009</woscitedreferencesoriginalsourcerecordid><citedby>FETCH-LOGICAL-c457t-2e648d69a41ec60ed0c2af31c0517556e2656dcec1a77b8e2690e39d7f9ca9473</citedby><cites>FETCH-LOGICAL-c457t-2e648d69a41ec60ed0c2af31c0517556e2656dcec1a77b8e2690e39d7f9ca9473</cites><orcidid>0000-0001-9169-763X ; 0000-0001-7169-6904 ; 0000-0003-3970-1886 ; 0000-0001-7673-6143 ; 0000-0002-4782-2410 ; 0000-0003-2317-5973 ; 0000-0003-0656-2621</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,315,729,782,786,866,887,2104,2116,12853,27931,27932,31006,39265</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34236993$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Patel, Birju</creatorcontrib><creatorcontrib>Vilendrer, Stacie</creatorcontrib><creatorcontrib>Kling, Samantha M. R.</creatorcontrib><creatorcontrib>Brown, Ian</creatorcontrib><creatorcontrib>Ribeira, Ryan</creatorcontrib><creatorcontrib>Eisenberg, Matthew</creatorcontrib><creatorcontrib>Sharp, Christopher</creatorcontrib><title>Using a Real-Time Locating System to Evaluate the Impact of Telemedicine in an Emergency Department During COVID-19: Observational Study</title><title>Journal of medical Internet research</title><addtitle>J MED INTERNET RES</addtitle><addtitle>J Med Internet Res</addtitle><description>Background: Telemedicine has been deployed by health care systems in response to the COVID-19 pandemic to enable health care workers to provide remote care for both outpatients and inpatients. Although it is reasonable to suspect telemedicine visits limit unnecessary personal contact and thus decrease the risk of infection transmission, the impact of the use of such technology on clinician workflows in the emergency department is unknown.
Objective: This study aimed to use a real-time locating system (RTLS) to evaluate the impact of a new telemedicine platform, which permitted clinicians located outside patient rooms to interact with patients who were under isolation precautions in the emergency department, on in-person interaction between health care workers and patients.
Methods: A pre-post analysis was conducted using a badge-based RTLS platform to collect movement data including entrances and duration of stay within patient rooms of the emergency department for nursing and physician staff. Movement data was captured between March 2, 2020, the date of the first patient screened for COVID-19 in the emergency department, and April 20, 2020. A new telemedicine platform was deployed on March 29, 2020. The number of entrances and duration of in-person interactions per patient encounter, adjusted for patient length of stay, were obtained for pre- and postimplementation phases and compared with t tests to determine statistical significance.
Results: There were 15,741 RTLS events linked to 2662 encounters for patients screened for COVID-19. There was no significant change in the number of in-person interactions between the pre- and postimplementation phases for both nurses (5.7 vs 7.0 entrances per patient, P=.07) and physicians (1.3 vs 1.5 entrances per patient, P=.12). Total duration of in-person interactions did not change (56.4 vs 55.2 minutes per patient, P=.74) despite significant increases in telemedicine videoconference frequency (0.6 vs 1.3 videoconferences per patient, P<.001 for change in daily average) and duration (4.3 vs 12.3 minutes per patient, P<.001 for change in daily average).
Conclusions: Telemedicine was rapidly adopted with the intent of minimizing pathogen exposure to health care workers during the COVID-19 pandemic, yet RTLS movement data did not reveal significant changes for in-person interactions between staff and patients under investigation for COVID-19 infection. Additional research is needed to better understand how telemedicine technology may be better incorporated into emergency departments to improve workflows for frontline health care clinicians.</description><subject>Averages</subject><subject>Changes</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>COVID-19 - diagnosis</subject><subject>COVID-19 - epidemiology</subject><subject>COVID-19 - prevention & control</subject><subject>COVID-19 diagnostic tests</subject><subject>Cross Infection - prevention & control</subject><subject>Disease transmission</subject><subject>Electronic health records</subject><subject>Emergency medical care</subject><subject>Emergency Service, Hospital - organization & administration</subject><subject>Emergency services</subject><subject>Health Care Sciences & Services</subject><subject>Health Personnel - organization & administration</subject><subject>Humans</subject><subject>Infections</subject><subject>Length of stay</subject><subject>Life Sciences & Biomedicine</subject><subject>Medical Informatics</subject><subject>Medical personnel</subject><subject>Nurses</subject><subject>Observational studies</subject><subject>Original Paper</subject><subject>Outpatients</subject><subject>Pandemics</subject><subject>Patient communication</subject><subject>Patients</subject><subject>Personal protective equipment</subject><subject>Physicians</subject><subject>Precautions</subject><subject>SARS-CoV-2</subject><subject>Science & Technology</subject><subject>Sensors</subject><subject>Severe acute respiratory syndrome coronavirus 2</subject><subject>Statistical significance</subject><subject>Technology</subject><subject>Telemedicine</subject><subject>Time Factors</subject><subject>Video conferencing</subject><subject>Workers</subject><subject>Workflow</subject><issn>1438-8871</issn><issn>1439-4456</issn><issn>1438-8871</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>HGBXW</sourceid><sourceid>EIF</sourceid><sourceid>7QJ</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>DOA</sourceid><recordid>eNqNkt-K1DAUxoso7rruK0hABEGqSdqmiReCdEYdGBhwZ70NaXo6m6FtxiQdmTfwsU1n1mHXK69ycvLjy3f-JMk1we8pEewDFTTHT5JLkmc85bwkTx_EF8kL77cYU5wL8jy5yHKaMSGyy-T3rTfDBin0HVSXrk0PaGm1ClPy5uAD9ChYNN-rblQBULgDtOh3SgdkW7SGDnpojDYDIDMgNaB5D24Dgz6gGeyUCz0MAc1GN-lVqx-LWUrER7SqPbh9_MUOqkM3YWwOL5Nnreo8XN-fV8ntl_m6-pYuV18X1edlqvOiDCkFlvOGCZUT0AxDgzVVbUY0LkhZFAwoK1ijQRNVljWPV4EhE03ZCq1EXmZXyeKk21i1lTtneuUO0iojjwnrNjLaNroDCZgTDqJRom7yVtc8y_KGFpywlnNMeNT6dNLajXXsg461OtU9En38Mpg7ubF7yTNSkEJEgbf3As7-HMEH2RuvoevUAHb0khYFpowwnkf09T_o1o4utm-iOC4pLsRU3ZsTpZ313kF7NkOwnPZEHvckcq8eOj9TfxcjAu9OwC-obeu1iTOFM4YxZiUvS0JjhKc6-P_TlQnHyVd2HEL2B4A615E</recordid><startdate>20210726</startdate><enddate>20210726</enddate><creator>Patel, Birju</creator><creator>Vilendrer, Stacie</creator><creator>Kling, Samantha M. R.</creator><creator>Brown, Ian</creator><creator>Ribeira, Ryan</creator><creator>Eisenberg, Matthew</creator><creator>Sharp, Christopher</creator><general>Jmir Publications, Inc</general><general>Gunther Eysenbach MD MPH, Associate Professor</general><general>JMIR Publications</general><scope>BLEPL</scope><scope>DTL</scope><scope>HGBXW</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>3V.</scope><scope>7QJ</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>CNYFK</scope><scope>COVID</scope><scope>DWQXO</scope><scope>E3H</scope><scope>F2A</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1O</scope><scope>NAPCQ</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-9169-763X</orcidid><orcidid>https://orcid.org/0000-0001-7169-6904</orcidid><orcidid>https://orcid.org/0000-0003-3970-1886</orcidid><orcidid>https://orcid.org/0000-0001-7673-6143</orcidid><orcidid>https://orcid.org/0000-0002-4782-2410</orcidid><orcidid>https://orcid.org/0000-0003-2317-5973</orcidid><orcidid>https://orcid.org/0000-0003-0656-2621</orcidid></search><sort><creationdate>20210726</creationdate><title>Using a Real-Time Locating System to Evaluate the Impact of Telemedicine in an Emergency Department During COVID-19: Observational Study</title><author>Patel, Birju ; Vilendrer, Stacie ; Kling, Samantha M. R. ; Brown, Ian ; Ribeira, Ryan ; Eisenberg, Matthew ; Sharp, Christopher</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c457t-2e648d69a41ec60ed0c2af31c0517556e2656dcec1a77b8e2690e39d7f9ca9473</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Averages</topic><topic>Changes</topic><topic>Coronaviruses</topic><topic>COVID-19</topic><topic>COVID-19 - diagnosis</topic><topic>COVID-19 - epidemiology</topic><topic>COVID-19 - prevention & control</topic><topic>COVID-19 diagnostic tests</topic><topic>Cross Infection - prevention & control</topic><topic>Disease transmission</topic><topic>Electronic health records</topic><topic>Emergency medical care</topic><topic>Emergency Service, Hospital - organization & administration</topic><topic>Emergency services</topic><topic>Health Care Sciences & Services</topic><topic>Health Personnel - organization & administration</topic><topic>Humans</topic><topic>Infections</topic><topic>Length of stay</topic><topic>Life Sciences & Biomedicine</topic><topic>Medical Informatics</topic><topic>Medical personnel</topic><topic>Nurses</topic><topic>Observational studies</topic><topic>Original Paper</topic><topic>Outpatients</topic><topic>Pandemics</topic><topic>Patient communication</topic><topic>Patients</topic><topic>Personal protective equipment</topic><topic>Physicians</topic><topic>Precautions</topic><topic>SARS-CoV-2</topic><topic>Science & Technology</topic><topic>Sensors</topic><topic>Severe acute respiratory syndrome coronavirus 2</topic><topic>Statistical significance</topic><topic>Technology</topic><topic>Telemedicine</topic><topic>Time Factors</topic><topic>Video conferencing</topic><topic>Workers</topic><topic>Workflow</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Patel, Birju</creatorcontrib><creatorcontrib>Vilendrer, Stacie</creatorcontrib><creatorcontrib>Kling, Samantha M. R.</creatorcontrib><creatorcontrib>Brown, Ian</creatorcontrib><creatorcontrib>Ribeira, Ryan</creatorcontrib><creatorcontrib>Eisenberg, Matthew</creatorcontrib><creatorcontrib>Sharp, Christopher</creatorcontrib><collection>Web of Science Core Collection</collection><collection>Science Citation Index Expanded</collection><collection>Web of Science - Science Citation Index Expanded - 2021</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Applied Social Sciences Index & Abstracts (ASSIA)</collection><collection>Nursing & Allied Health Database</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Library & Information Science Collection</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central Korea</collection><collection>Library & Information Sciences Abstracts (LISA)</collection><collection>Library & Information Science Abstracts (LISA)</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Library Science Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Journal of medical Internet research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Patel, Birju</au><au>Vilendrer, Stacie</au><au>Kling, Samantha M. R.</au><au>Brown, Ian</au><au>Ribeira, Ryan</au><au>Eisenberg, Matthew</au><au>Sharp, Christopher</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Using a Real-Time Locating System to Evaluate the Impact of Telemedicine in an Emergency Department During COVID-19: Observational Study</atitle><jtitle>Journal of medical Internet research</jtitle><stitle>J MED INTERNET RES</stitle><addtitle>J Med Internet Res</addtitle><date>2021-07-26</date><risdate>2021</risdate><volume>23</volume><issue>7</issue><spage>e29240</spage><epage>e29240</epage><pages>e29240-e29240</pages><artnum>29240</artnum><issn>1438-8871</issn><issn>1439-4456</issn><eissn>1438-8871</eissn><abstract>Background: Telemedicine has been deployed by health care systems in response to the COVID-19 pandemic to enable health care workers to provide remote care for both outpatients and inpatients. Although it is reasonable to suspect telemedicine visits limit unnecessary personal contact and thus decrease the risk of infection transmission, the impact of the use of such technology on clinician workflows in the emergency department is unknown.
Objective: This study aimed to use a real-time locating system (RTLS) to evaluate the impact of a new telemedicine platform, which permitted clinicians located outside patient rooms to interact with patients who were under isolation precautions in the emergency department, on in-person interaction between health care workers and patients.
Methods: A pre-post analysis was conducted using a badge-based RTLS platform to collect movement data including entrances and duration of stay within patient rooms of the emergency department for nursing and physician staff. Movement data was captured between March 2, 2020, the date of the first patient screened for COVID-19 in the emergency department, and April 20, 2020. A new telemedicine platform was deployed on March 29, 2020. The number of entrances and duration of in-person interactions per patient encounter, adjusted for patient length of stay, were obtained for pre- and postimplementation phases and compared with t tests to determine statistical significance.
Results: There were 15,741 RTLS events linked to 2662 encounters for patients screened for COVID-19. There was no significant change in the number of in-person interactions between the pre- and postimplementation phases for both nurses (5.7 vs 7.0 entrances per patient, P=.07) and physicians (1.3 vs 1.5 entrances per patient, P=.12). Total duration of in-person interactions did not change (56.4 vs 55.2 minutes per patient, P=.74) despite significant increases in telemedicine videoconference frequency (0.6 vs 1.3 videoconferences per patient, P<.001 for change in daily average) and duration (4.3 vs 12.3 minutes per patient, P<.001 for change in daily average).
Conclusions: Telemedicine was rapidly adopted with the intent of minimizing pathogen exposure to health care workers during the COVID-19 pandemic, yet RTLS movement data did not reveal significant changes for in-person interactions between staff and patients under investigation for COVID-19 infection. Additional research is needed to better understand how telemedicine technology may be better incorporated into emergency departments to improve workflows for frontline health care clinicians.</abstract><cop>TORONTO</cop><pub>Jmir Publications, Inc</pub><pmid>34236993</pmid><doi>10.2196/29240</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0001-9169-763X</orcidid><orcidid>https://orcid.org/0000-0001-7169-6904</orcidid><orcidid>https://orcid.org/0000-0003-3970-1886</orcidid><orcidid>https://orcid.org/0000-0001-7673-6143</orcidid><orcidid>https://orcid.org/0000-0002-4782-2410</orcidid><orcidid>https://orcid.org/0000-0003-2317-5973</orcidid><orcidid>https://orcid.org/0000-0003-0656-2621</orcidid><oa>free_for_read</oa></addata></record> |
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| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8315159 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central Open Access; Applied Social Sciences Index & Abstracts (ASSIA); Web of Science - Science Citation Index Expanded - 2021<img src="https://exlibris-pub.s3.amazonaws.com/fromwos-v2.jpg" />; PubMed Central |
| subjects | Averages Changes Coronaviruses COVID-19 COVID-19 - diagnosis COVID-19 - epidemiology COVID-19 - prevention & control COVID-19 diagnostic tests Cross Infection - prevention & control Disease transmission Electronic health records Emergency medical care Emergency Service, Hospital - organization & administration Emergency services Health Care Sciences & Services Health Personnel - organization & administration Humans Infections Length of stay Life Sciences & Biomedicine Medical Informatics Medical personnel Nurses Observational studies Original Paper Outpatients Pandemics Patient communication Patients Personal protective equipment Physicians Precautions SARS-CoV-2 Science & Technology Sensors Severe acute respiratory syndrome coronavirus 2 Statistical significance Technology Telemedicine Time Factors Video conferencing Workers Workflow |
| title | Using a Real-Time Locating System to Evaluate the Impact of Telemedicine in an Emergency Department During COVID-19: Observational Study |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-05T05%3A49%3A22IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Using%20a%20Real-Time%20Locating%20System%20to%20Evaluate%20the%20Impact%20of%20Telemedicine%20in%20an%20Emergency%20Department%20During%20COVID-19:%20Observational%20Study&rft.jtitle=Journal%20of%20medical%20Internet%20research&rft.au=Patel,%20Birju&rft.date=2021-07-26&rft.volume=23&rft.issue=7&rft.spage=e29240&rft.epage=e29240&rft.pages=e29240-e29240&rft.artnum=29240&rft.issn=1438-8871&rft.eissn=1438-8871&rft_id=info:doi/10.2196/29240&rft_dat=%3Cproquest_pubme%3E2580720597%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2580720597&rft_id=info:pmid/34236993&rft_doaj_id=oai_doaj_org_article_e0818e9da9bd4fcb8334d25816f88018&rfr_iscdi=true |