Forecast UTI: application for predicting intensive care unit beds in the context of the COVID-19 pandemic
In view of the need to manage and forecast the number of Intensive Care Unit (ICU) beds for critically ill COVID-19 patients, the Forecast UTI open access application was developed to enable hospital indicator monitoring based on past health data and the temporal dynamics of the Coronavirus epidemic...
Gespeichert in:
| Veröffentlicht in: | Epidemiologia e serviços de saúde 2020, Vol.29 (4), p.e2020391-e2020391 |
|---|---|
| Hauptverfasser: | , , , , , , , , , , |
| Format: | Artikel |
| Sprache: | eng ; por |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | e2020391 |
|---|---|
| container_issue | 4 |
| container_start_page | e2020391 |
| container_title | Epidemiologia e serviços de saúde |
| container_volume | 29 |
| creator | Salles Neto, Luiz Leduíno de Martins, Camila Bertini Chaves, Antônio Augusto Konstantyner, Thais Cláudia Roma de Oliveira Yanasse, Horacio Hideki Campos, Claudia Barbosa Ladeira de Bellini, Ana Júlia de Oliveira Butkeraites, Renan Brito Correia, Leonardo Magro, Igor Luciano Soares, Fernando Dos Santos |
| description | In view of the need to manage and forecast the number of Intensive Care Unit (ICU) beds for critically ill COVID-19 patients, the Forecast UTI open access application was developed to enable hospital indicator monitoring based on past health data and the temporal dynamics of the Coronavirus epidemic. Forecast UTI also enables short-term forecasts of the number of beds occupied daily by COVID-19 patients and possible care scenarios to be established. This article presents the functions, mode of access and examples of uses of Forecast UTI, a computational tool intended to assist managers of public and private hospitals within the Brazilian National Health System by supporting quick, strategic and efficient decision-making. |
| doi_str_mv | 10.1590/S1679-49742020000400023 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_proquest_miscellaneous_2447542619</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2447542619</sourcerecordid><originalsourceid>FETCH-LOGICAL-p126t-64e74a011b36925a23d8c5353a39c209db461ceb40bdc08ecfb71cdec2b850ab3</originalsourceid><addsrcrecordid>eNo1kEtPwzAQhC0kRCvoXwAfuQTstWPH3FChUKlSD7RcI78CRnkROwj-PQHKSqPVzHzawyJ0QckVzRW5fqJCqowryYEAmYZPAnaE5gBMZkoAzNAixrefLueSAj1BMwZKSSKKOQqrbvBWx4T3u_UN1n1fB6tT6FpcdQPuB--CTaF9waFNvo3hw2OrB4_HNiRsvItTgdPrlHYT8JlwV_3a5fZ5fZdRhXvdOt8Ee4aOK11HvzjsU7Rf3e-Wj9lm-7Be3m6ynoJImeBeck0oNUwoyDUwV9ic5UwzZYEoZ7ig1htOjLOk8LYyklrnLZgiJ9qwU3T5d7cfuvfRx1Q2IVpf17r13RhL4FzmHARVE3p-QEfTeFf2Q2j08FX-v4d9AzEjZxE</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2447542619</pqid></control><display><type>article</type><title>Forecast UTI: application for predicting intensive care unit beds in the context of the COVID-19 pandemic</title><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>EZB-FREE-00999 freely available EZB journals</source><creator>Salles Neto, Luiz Leduíno de ; Martins, Camila Bertini ; Chaves, Antônio Augusto ; Konstantyner, Thais Cláudia Roma de Oliveira ; Yanasse, Horacio Hideki ; Campos, Claudia Barbosa Ladeira de ; Bellini, Ana Júlia de Oliveira ; Butkeraites, Renan Brito ; Correia, Leonardo ; Magro, Igor Luciano ; Soares, Fernando Dos Santos</creator><creatorcontrib>Salles Neto, Luiz Leduíno de ; Martins, Camila Bertini ; Chaves, Antônio Augusto ; Konstantyner, Thais Cláudia Roma de Oliveira ; Yanasse, Horacio Hideki ; Campos, Claudia Barbosa Ladeira de ; Bellini, Ana Júlia de Oliveira ; Butkeraites, Renan Brito ; Correia, Leonardo ; Magro, Igor Luciano ; Soares, Fernando Dos Santos</creatorcontrib><description>In view of the need to manage and forecast the number of Intensive Care Unit (ICU) beds for critically ill COVID-19 patients, the Forecast UTI open access application was developed to enable hospital indicator monitoring based on past health data and the temporal dynamics of the Coronavirus epidemic. Forecast UTI also enables short-term forecasts of the number of beds occupied daily by COVID-19 patients and possible care scenarios to be established. This article presents the functions, mode of access and examples of uses of Forecast UTI, a computational tool intended to assist managers of public and private hospitals within the Brazilian National Health System by supporting quick, strategic and efficient decision-making.</description><identifier>EISSN: 2237-9622</identifier><identifier>DOI: 10.1590/S1679-49742020000400023</identifier><identifier>PMID: 32997068</identifier><language>eng ; por</language><publisher>Brazil</publisher><subject>Bed Occupancy - statistics & numerical data ; Beds - supply & distribution ; Betacoronavirus ; Brazil - epidemiology ; Coronavirus Infections - epidemiology ; COVID-19 ; Decision Making ; Forecasting ; Hospital Bed Capacity - statistics & numerical data ; Humans ; Intensive Care Units - statistics & numerical data ; Pandemics ; Pneumonia, Viral - epidemiology ; SARS-CoV-2 ; Software ; Software Design</subject><ispartof>Epidemiologia e serviços de saúde, 2020, Vol.29 (4), p.e2020391-e2020391</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0001-8938-5370 ; 0000-0002-8252-8815 ; 0000-0002-5830-0466 ; 0000-0002-2289-1866 ; 0000-0002-6946-9670 ; 0000-0002-1460-4169 ; 0000-0002-7091-0435 ; 0000-0002-1836-0915 ; 0000-0003-4671-5290 ; 0000-0002-2773-2696 ; 0000-0001-5767-6798</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,864,4024,27923,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32997068$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Salles Neto, Luiz Leduíno de</creatorcontrib><creatorcontrib>Martins, Camila Bertini</creatorcontrib><creatorcontrib>Chaves, Antônio Augusto</creatorcontrib><creatorcontrib>Konstantyner, Thais Cláudia Roma de Oliveira</creatorcontrib><creatorcontrib>Yanasse, Horacio Hideki</creatorcontrib><creatorcontrib>Campos, Claudia Barbosa Ladeira de</creatorcontrib><creatorcontrib>Bellini, Ana Júlia de Oliveira</creatorcontrib><creatorcontrib>Butkeraites, Renan Brito</creatorcontrib><creatorcontrib>Correia, Leonardo</creatorcontrib><creatorcontrib>Magro, Igor Luciano</creatorcontrib><creatorcontrib>Soares, Fernando Dos Santos</creatorcontrib><title>Forecast UTI: application for predicting intensive care unit beds in the context of the COVID-19 pandemic</title><title>Epidemiologia e serviços de saúde</title><addtitle>Epidemiol Serv Saude</addtitle><description>In view of the need to manage and forecast the number of Intensive Care Unit (ICU) beds for critically ill COVID-19 patients, the Forecast UTI open access application was developed to enable hospital indicator monitoring based on past health data and the temporal dynamics of the Coronavirus epidemic. Forecast UTI also enables short-term forecasts of the number of beds occupied daily by COVID-19 patients and possible care scenarios to be established. This article presents the functions, mode of access and examples of uses of Forecast UTI, a computational tool intended to assist managers of public and private hospitals within the Brazilian National Health System by supporting quick, strategic and efficient decision-making.</description><subject>Bed Occupancy - statistics & numerical data</subject><subject>Beds - supply & distribution</subject><subject>Betacoronavirus</subject><subject>Brazil - epidemiology</subject><subject>Coronavirus Infections - epidemiology</subject><subject>COVID-19</subject><subject>Decision Making</subject><subject>Forecasting</subject><subject>Hospital Bed Capacity - statistics & numerical data</subject><subject>Humans</subject><subject>Intensive Care Units - statistics & numerical data</subject><subject>Pandemics</subject><subject>Pneumonia, Viral - epidemiology</subject><subject>SARS-CoV-2</subject><subject>Software</subject><subject>Software Design</subject><issn>2237-9622</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNo1kEtPwzAQhC0kRCvoXwAfuQTstWPH3FChUKlSD7RcI78CRnkROwj-PQHKSqPVzHzawyJ0QckVzRW5fqJCqowryYEAmYZPAnaE5gBMZkoAzNAixrefLueSAj1BMwZKSSKKOQqrbvBWx4T3u_UN1n1fB6tT6FpcdQPuB--CTaF9waFNvo3hw2OrB4_HNiRsvItTgdPrlHYT8JlwV_3a5fZ5fZdRhXvdOt8Ee4aOK11HvzjsU7Rf3e-Wj9lm-7Be3m6ynoJImeBeck0oNUwoyDUwV9ic5UwzZYEoZ7ig1htOjLOk8LYyklrnLZgiJ9qwU3T5d7cfuvfRx1Q2IVpf17r13RhL4FzmHARVE3p-QEfTeFf2Q2j08FX-v4d9AzEjZxE</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Salles Neto, Luiz Leduíno de</creator><creator>Martins, Camila Bertini</creator><creator>Chaves, Antônio Augusto</creator><creator>Konstantyner, Thais Cláudia Roma de Oliveira</creator><creator>Yanasse, Horacio Hideki</creator><creator>Campos, Claudia Barbosa Ladeira de</creator><creator>Bellini, Ana Júlia de Oliveira</creator><creator>Butkeraites, Renan Brito</creator><creator>Correia, Leonardo</creator><creator>Magro, Igor Luciano</creator><creator>Soares, Fernando Dos Santos</creator><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-8938-5370</orcidid><orcidid>https://orcid.org/0000-0002-8252-8815</orcidid><orcidid>https://orcid.org/0000-0002-5830-0466</orcidid><orcidid>https://orcid.org/0000-0002-2289-1866</orcidid><orcidid>https://orcid.org/0000-0002-6946-9670</orcidid><orcidid>https://orcid.org/0000-0002-1460-4169</orcidid><orcidid>https://orcid.org/0000-0002-7091-0435</orcidid><orcidid>https://orcid.org/0000-0002-1836-0915</orcidid><orcidid>https://orcid.org/0000-0003-4671-5290</orcidid><orcidid>https://orcid.org/0000-0002-2773-2696</orcidid><orcidid>https://orcid.org/0000-0001-5767-6798</orcidid></search><sort><creationdate>2020</creationdate><title>Forecast UTI: application for predicting intensive care unit beds in the context of the COVID-19 pandemic</title><author>Salles Neto, Luiz Leduíno de ; Martins, Camila Bertini ; Chaves, Antônio Augusto ; Konstantyner, Thais Cláudia Roma de Oliveira ; Yanasse, Horacio Hideki ; Campos, Claudia Barbosa Ladeira de ; Bellini, Ana Júlia de Oliveira ; Butkeraites, Renan Brito ; Correia, Leonardo ; Magro, Igor Luciano ; Soares, Fernando Dos Santos</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p126t-64e74a011b36925a23d8c5353a39c209db461ceb40bdc08ecfb71cdec2b850ab3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng ; por</language><creationdate>2020</creationdate><topic>Bed Occupancy - statistics & numerical data</topic><topic>Beds - supply & distribution</topic><topic>Betacoronavirus</topic><topic>Brazil - epidemiology</topic><topic>Coronavirus Infections - epidemiology</topic><topic>COVID-19</topic><topic>Decision Making</topic><topic>Forecasting</topic><topic>Hospital Bed Capacity - statistics & numerical data</topic><topic>Humans</topic><topic>Intensive Care Units - statistics & numerical data</topic><topic>Pandemics</topic><topic>Pneumonia, Viral - epidemiology</topic><topic>SARS-CoV-2</topic><topic>Software</topic><topic>Software Design</topic><toplevel>online_resources</toplevel><creatorcontrib>Salles Neto, Luiz Leduíno de</creatorcontrib><creatorcontrib>Martins, Camila Bertini</creatorcontrib><creatorcontrib>Chaves, Antônio Augusto</creatorcontrib><creatorcontrib>Konstantyner, Thais Cláudia Roma de Oliveira</creatorcontrib><creatorcontrib>Yanasse, Horacio Hideki</creatorcontrib><creatorcontrib>Campos, Claudia Barbosa Ladeira de</creatorcontrib><creatorcontrib>Bellini, Ana Júlia de Oliveira</creatorcontrib><creatorcontrib>Butkeraites, Renan Brito</creatorcontrib><creatorcontrib>Correia, Leonardo</creatorcontrib><creatorcontrib>Magro, Igor Luciano</creatorcontrib><creatorcontrib>Soares, Fernando Dos Santos</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>MEDLINE - Academic</collection><jtitle>Epidemiologia e serviços de saúde</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Salles Neto, Luiz Leduíno de</au><au>Martins, Camila Bertini</au><au>Chaves, Antônio Augusto</au><au>Konstantyner, Thais Cláudia Roma de Oliveira</au><au>Yanasse, Horacio Hideki</au><au>Campos, Claudia Barbosa Ladeira de</au><au>Bellini, Ana Júlia de Oliveira</au><au>Butkeraites, Renan Brito</au><au>Correia, Leonardo</au><au>Magro, Igor Luciano</au><au>Soares, Fernando Dos Santos</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Forecast UTI: application for predicting intensive care unit beds in the context of the COVID-19 pandemic</atitle><jtitle>Epidemiologia e serviços de saúde</jtitle><addtitle>Epidemiol Serv Saude</addtitle><date>2020</date><risdate>2020</risdate><volume>29</volume><issue>4</issue><spage>e2020391</spage><epage>e2020391</epage><pages>e2020391-e2020391</pages><eissn>2237-9622</eissn><abstract>In view of the need to manage and forecast the number of Intensive Care Unit (ICU) beds for critically ill COVID-19 patients, the Forecast UTI open access application was developed to enable hospital indicator monitoring based on past health data and the temporal dynamics of the Coronavirus epidemic. Forecast UTI also enables short-term forecasts of the number of beds occupied daily by COVID-19 patients and possible care scenarios to be established. This article presents the functions, mode of access and examples of uses of Forecast UTI, a computational tool intended to assist managers of public and private hospitals within the Brazilian National Health System by supporting quick, strategic and efficient decision-making.</abstract><cop>Brazil</cop><pmid>32997068</pmid><doi>10.1590/S1679-49742020000400023</doi><orcidid>https://orcid.org/0000-0001-8938-5370</orcidid><orcidid>https://orcid.org/0000-0002-8252-8815</orcidid><orcidid>https://orcid.org/0000-0002-5830-0466</orcidid><orcidid>https://orcid.org/0000-0002-2289-1866</orcidid><orcidid>https://orcid.org/0000-0002-6946-9670</orcidid><orcidid>https://orcid.org/0000-0002-1460-4169</orcidid><orcidid>https://orcid.org/0000-0002-7091-0435</orcidid><orcidid>https://orcid.org/0000-0002-1836-0915</orcidid><orcidid>https://orcid.org/0000-0003-4671-5290</orcidid><orcidid>https://orcid.org/0000-0002-2773-2696</orcidid><orcidid>https://orcid.org/0000-0001-5767-6798</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | EISSN: 2237-9622 |
| ispartof | Epidemiologia e serviços de saúde, 2020, Vol.29 (4), p.e2020391-e2020391 |
| issn | 2237-9622 |
| language | eng ; por |
| recordid | cdi_proquest_miscellaneous_2447542619 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals |
| subjects | Bed Occupancy - statistics & numerical data Beds - supply & distribution Betacoronavirus Brazil - epidemiology Coronavirus Infections - epidemiology COVID-19 Decision Making Forecasting Hospital Bed Capacity - statistics & numerical data Humans Intensive Care Units - statistics & numerical data Pandemics Pneumonia, Viral - epidemiology SARS-CoV-2 Software Software Design |
| title | Forecast UTI: application for predicting intensive care unit beds in the context of the COVID-19 pandemic |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-07T20%3A26%3A49IST&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=Forecast%20UTI:%20application%20for%20predicting%20intensive%20care%20unit%20beds%20in%20the%20context%20of%20the%20COVID-19%20pandemic&rft.jtitle=Epidemiologia%20e%20servi%C3%A7os%20de%20sa%C3%BAde&rft.au=Salles%20Neto,%20Luiz%20Ledu%C3%ADno%20de&rft.date=2020&rft.volume=29&rft.issue=4&rft.spage=e2020391&rft.epage=e2020391&rft.pages=e2020391-e2020391&rft.eissn=2237-9622&rft_id=info:doi/10.1590/S1679-49742020000400023&rft_dat=%3Cproquest_pubme%3E2447542619%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=2447542619&rft_id=info:pmid/32997068&rfr_iscdi=true |