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The use of a smartphone application to improve stroke code workflow metrics: A pilot study in a comprehensive stroke centre
Background Timely coordination between stroke team members is of relevance for stroke code management. We explore the feasibility and potential utility of a smartphone application for clinical and neuroimaging data sharing for improving workflow metrics of stroke code pathways, and professionals’ op...
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Published in: | Digital health 2022-01, Vol.8, p.20552076221137252 |
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creator | Gutiérrez-Zúñiga, Raquel Uclés, Jorge Sánchez-Manso, Juan Carlos Fuentes, Blanca de Celis, Elena Ruiz-Ares, Gerardo Rodríguez-Pardo, Jorge Rigual, Ricardo Casado, Laura Alonso, Elisa Fernández-Prieto, Andrés Navia, Pedro Álvarez-Muelas, Alberto Marín, Begoña Díez Tejedor, Exuperio Alonso de Leciñana, María |
description | Background
Timely coordination between stroke team members is of relevance for stroke code management. We explore the feasibility and potential utility of a smartphone application for clinical and neuroimaging data sharing for improving workflow metrics of stroke code pathways, and professionals’ opinions about its use.
Methods
We performed an observational pilot study including stroke code activations at La Paz University Hospital in Madrid, from June 2019 to March 2020. Patients were classified according to the activation or not of the JOIN app by the attending physician. Clinical data and time-to-procedures were retrieved from the app or from the hospital records and the Madrid regional stroke registry as appropriate and compared between both groups. An anonymous survey collected professionals’ opinions about the app and its use.
Results
A total of 282 stroke code activations were registered. The JOIN app was activated in 111 (39%) cases. They had a significant reduction in imaging-to-thrombolysis (31 vs 20 min, p = .026) and in door-to-thrombolysis times (51 vs 36 min, p = .004), with more patients achieving a door-to-needle time below 45 min (68.8% vs 37.8%, p = .016). About 50% of the users found the app useful for facilitating the diagnosis and decision-making; interoperability with clinical files was considered an opportunity for improvement.
Conclusions
This pilot study suggests that JOIN helps improve and document workflow metrics in acute stroke management in a comprehensive stroke centre. These results support testing JOIN in a prospective randomised study to confirm its usefulness and the general applicability of the results. |
doi_str_mv | 10.1177/20552076221137252 |
format | article |
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Timely coordination between stroke team members is of relevance for stroke code management. We explore the feasibility and potential utility of a smartphone application for clinical and neuroimaging data sharing for improving workflow metrics of stroke code pathways, and professionals’ opinions about its use.
Methods
We performed an observational pilot study including stroke code activations at La Paz University Hospital in Madrid, from June 2019 to March 2020. Patients were classified according to the activation or not of the JOIN app by the attending physician. Clinical data and time-to-procedures were retrieved from the app or from the hospital records and the Madrid regional stroke registry as appropriate and compared between both groups. An anonymous survey collected professionals’ opinions about the app and its use.
Results
A total of 282 stroke code activations were registered. The JOIN app was activated in 111 (39%) cases. They had a significant reduction in imaging-to-thrombolysis (31 vs 20 min, p = .026) and in door-to-thrombolysis times (51 vs 36 min, p = .004), with more patients achieving a door-to-needle time below 45 min (68.8% vs 37.8%, p = .016). About 50% of the users found the app useful for facilitating the diagnosis and decision-making; interoperability with clinical files was considered an opportunity for improvement.
Conclusions
This pilot study suggests that JOIN helps improve and document workflow metrics in acute stroke management in a comprehensive stroke centre. These results support testing JOIN in a prospective randomised study to confirm its usefulness and the general applicability of the results.</description><identifier>ISSN: 2055-2076</identifier><identifier>EISSN: 2055-2076</identifier><identifier>DOI: 10.1177/20552076221137252</identifier><identifier>PMID: 36406153</identifier><language>eng</language><publisher>London, England: SAGE Publications</publisher><subject>Original Research ; Smartphones ; Stroke ; Telemedicine</subject><ispartof>Digital health, 2022-01, Vol.8, p.20552076221137252</ispartof><rights>The Author(s) 2022</rights><rights>The Author(s) 2022.</rights><rights>The Author(s) 2022. This work is licensed under the Creative Commons Attribution – Non-Commercial – No Derivatives License https://creativecommons.org/licenses/by-nc-nd/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>The Author(s) 2022 2022 SAGE Publications Ltd, unless otherwise noted. Manuscript content on this site is licensed under Creative Commons Licenses</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c484t-66255d1dbfa3eda5c0d6d42ac54fa9c2c460acd19dcbeeb7ed0b6a4a5c0ee9163</cites><orcidid>0000-0002-4302-6580</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9669691/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2758348247?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,21964,25751,27851,27922,27923,37010,37011,44588,44943,45331,53789,53791</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36406153$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gutiérrez-Zúñiga, Raquel</creatorcontrib><creatorcontrib>Uclés, Jorge</creatorcontrib><creatorcontrib>Sánchez-Manso, Juan Carlos</creatorcontrib><creatorcontrib>Fuentes, Blanca</creatorcontrib><creatorcontrib>de Celis, Elena</creatorcontrib><creatorcontrib>Ruiz-Ares, Gerardo</creatorcontrib><creatorcontrib>Rodríguez-Pardo, Jorge</creatorcontrib><creatorcontrib>Rigual, Ricardo</creatorcontrib><creatorcontrib>Casado, Laura</creatorcontrib><creatorcontrib>Alonso, Elisa</creatorcontrib><creatorcontrib>Fernández-Prieto, Andrés</creatorcontrib><creatorcontrib>Navia, Pedro</creatorcontrib><creatorcontrib>Álvarez-Muelas, Alberto</creatorcontrib><creatorcontrib>Marín, Begoña</creatorcontrib><creatorcontrib>Díez Tejedor, Exuperio</creatorcontrib><creatorcontrib>Alonso de Leciñana, María</creatorcontrib><title>The use of a smartphone application to improve stroke code workflow metrics: A pilot study in a comprehensive stroke centre</title><title>Digital health</title><addtitle>Digit Health</addtitle><description>Background
Timely coordination between stroke team members is of relevance for stroke code management. We explore the feasibility and potential utility of a smartphone application for clinical and neuroimaging data sharing for improving workflow metrics of stroke code pathways, and professionals’ opinions about its use.
Methods
We performed an observational pilot study including stroke code activations at La Paz University Hospital in Madrid, from June 2019 to March 2020. Patients were classified according to the activation or not of the JOIN app by the attending physician. Clinical data and time-to-procedures were retrieved from the app or from the hospital records and the Madrid regional stroke registry as appropriate and compared between both groups. An anonymous survey collected professionals’ opinions about the app and its use.
Results
A total of 282 stroke code activations were registered. The JOIN app was activated in 111 (39%) cases. They had a significant reduction in imaging-to-thrombolysis (31 vs 20 min, p = .026) and in door-to-thrombolysis times (51 vs 36 min, p = .004), with more patients achieving a door-to-needle time below 45 min (68.8% vs 37.8%, p = .016). About 50% of the users found the app useful for facilitating the diagnosis and decision-making; interoperability with clinical files was considered an opportunity for improvement.
Conclusions
This pilot study suggests that JOIN helps improve and document workflow metrics in acute stroke management in a comprehensive stroke centre. These results support testing JOIN in a prospective randomised study to confirm its usefulness and the general applicability of the results.</description><subject>Original Research</subject><subject>Smartphones</subject><subject>Stroke</subject><subject>Telemedicine</subject><issn>2055-2076</issn><issn>2055-2076</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>AFRWT</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNp1kl9rFDEUxQdRbKn9AL5IwBdftuZ_Jj4IpWhbKPhSn0MmudnNdnYyJjMtxS9vtlvrVvEp4eZ3zr0n3KZ5S_AJIUp9pFgIipWklBCmqKAvmsNtbbEtvty7HzTHpawxxkQxpYl83RwwybEkgh02P69XgOYCKAVkUdnYPI2rNACy49hHZ6eYBjQlFDdjTreAypTTDSCXPKC7lG9Cn-7QBqYcXfmETtEY-zRVavb3KA7V0qWqhBUMJe7JYZgyvGleBdsXOH48j5rvX79cn10srr6dX56dXi0cb_m0kJIK4YnvgmXgrXDYS8-pdYIHqx11XGLrPNHedQCdAo87afkWBKh52VFzufP1ya7NmGNNeW-SjeahkPLS1NjR9WC0b1lQMvAAgYvOdQ7XGTTDLQ2thlC9Pu-8xrnbgH8IYvtnps9fhrgyy3RrtJRaalINPjwa5PRjhjKZTSwO-t4OkOZiqGK1oZStruj7v9B1mvNQv6pSomW8pVxViuwol1MpGcLTMASb7aaYfzalat7tp3hS_N6LCpzsgGKX8Kft_x1_AfvMyTI</recordid><startdate>20220101</startdate><enddate>20220101</enddate><creator>Gutiérrez-Zúñiga, Raquel</creator><creator>Uclés, Jorge</creator><creator>Sánchez-Manso, Juan Carlos</creator><creator>Fuentes, Blanca</creator><creator>de Celis, Elena</creator><creator>Ruiz-Ares, Gerardo</creator><creator>Rodríguez-Pardo, Jorge</creator><creator>Rigual, Ricardo</creator><creator>Casado, Laura</creator><creator>Alonso, Elisa</creator><creator>Fernández-Prieto, Andrés</creator><creator>Navia, Pedro</creator><creator>Álvarez-Muelas, Alberto</creator><creator>Marín, Begoña</creator><creator>Díez Tejedor, Exuperio</creator><creator>Alonso de Leciñana, María</creator><general>SAGE Publications</general><general>Sage Publications Ltd</general><general>SAGE Publishing</general><scope>AFRWT</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</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/0000-0002-4302-6580</orcidid></search><sort><creationdate>20220101</creationdate><title>The use of a smartphone application to improve stroke code workflow metrics: A pilot study in a comprehensive stroke centre</title><author>Gutiérrez-Zúñiga, Raquel ; Uclés, Jorge ; Sánchez-Manso, Juan Carlos ; Fuentes, Blanca ; de Celis, Elena ; Ruiz-Ares, Gerardo ; Rodríguez-Pardo, Jorge ; Rigual, Ricardo ; Casado, Laura ; Alonso, Elisa ; Fernández-Prieto, Andrés ; Navia, Pedro ; Álvarez-Muelas, Alberto ; Marín, Begoña ; Díez Tejedor, Exuperio ; Alonso de Leciñana, María</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c484t-66255d1dbfa3eda5c0d6d42ac54fa9c2c460acd19dcbeeb7ed0b6a4a5c0ee9163</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Original Research</topic><topic>Smartphones</topic><topic>Stroke</topic><topic>Telemedicine</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gutiérrez-Zúñiga, Raquel</creatorcontrib><creatorcontrib>Uclés, Jorge</creatorcontrib><creatorcontrib>Sánchez-Manso, Juan Carlos</creatorcontrib><creatorcontrib>Fuentes, Blanca</creatorcontrib><creatorcontrib>de Celis, Elena</creatorcontrib><creatorcontrib>Ruiz-Ares, Gerardo</creatorcontrib><creatorcontrib>Rodríguez-Pardo, Jorge</creatorcontrib><creatorcontrib>Rigual, Ricardo</creatorcontrib><creatorcontrib>Casado, Laura</creatorcontrib><creatorcontrib>Alonso, Elisa</creatorcontrib><creatorcontrib>Fernández-Prieto, Andrés</creatorcontrib><creatorcontrib>Navia, Pedro</creatorcontrib><creatorcontrib>Álvarez-Muelas, Alberto</creatorcontrib><creatorcontrib>Marín, Begoña</creatorcontrib><creatorcontrib>Díez Tejedor, Exuperio</creatorcontrib><creatorcontrib>Alonso de Leciñana, María</creatorcontrib><collection>SAGE Open Access</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</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)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Publicly Available Content Database</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>Digital health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gutiérrez-Zúñiga, Raquel</au><au>Uclés, Jorge</au><au>Sánchez-Manso, Juan Carlos</au><au>Fuentes, Blanca</au><au>de Celis, Elena</au><au>Ruiz-Ares, Gerardo</au><au>Rodríguez-Pardo, Jorge</au><au>Rigual, Ricardo</au><au>Casado, Laura</au><au>Alonso, Elisa</au><au>Fernández-Prieto, Andrés</au><au>Navia, Pedro</au><au>Álvarez-Muelas, Alberto</au><au>Marín, Begoña</au><au>Díez Tejedor, Exuperio</au><au>Alonso de Leciñana, María</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The use of a smartphone application to improve stroke code workflow metrics: A pilot study in a comprehensive stroke centre</atitle><jtitle>Digital health</jtitle><addtitle>Digit Health</addtitle><date>2022-01-01</date><risdate>2022</risdate><volume>8</volume><spage>20552076221137252</spage><pages>20552076221137252-</pages><issn>2055-2076</issn><eissn>2055-2076</eissn><abstract>Background
Timely coordination between stroke team members is of relevance for stroke code management. We explore the feasibility and potential utility of a smartphone application for clinical and neuroimaging data sharing for improving workflow metrics of stroke code pathways, and professionals’ opinions about its use.
Methods
We performed an observational pilot study including stroke code activations at La Paz University Hospital in Madrid, from June 2019 to March 2020. Patients were classified according to the activation or not of the JOIN app by the attending physician. Clinical data and time-to-procedures were retrieved from the app or from the hospital records and the Madrid regional stroke registry as appropriate and compared between both groups. An anonymous survey collected professionals’ opinions about the app and its use.
Results
A total of 282 stroke code activations were registered. The JOIN app was activated in 111 (39%) cases. They had a significant reduction in imaging-to-thrombolysis (31 vs 20 min, p = .026) and in door-to-thrombolysis times (51 vs 36 min, p = .004), with more patients achieving a door-to-needle time below 45 min (68.8% vs 37.8%, p = .016). About 50% of the users found the app useful for facilitating the diagnosis and decision-making; interoperability with clinical files was considered an opportunity for improvement.
Conclusions
This pilot study suggests that JOIN helps improve and document workflow metrics in acute stroke management in a comprehensive stroke centre. These results support testing JOIN in a prospective randomised study to confirm its usefulness and the general applicability of the results.</abstract><cop>London, England</cop><pub>SAGE Publications</pub><pmid>36406153</pmid><doi>10.1177/20552076221137252</doi><orcidid>https://orcid.org/0000-0002-4302-6580</orcidid><oa>free_for_read</oa></addata></record> |
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source | SAGE Open Access; Publicly Available Content Database; PubMed Central |
subjects | Original Research Smartphones Stroke Telemedicine |
title | The use of a smartphone application to improve stroke code workflow metrics: A pilot study in a comprehensive stroke centre |
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