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Publicação:
Semi-automated data collection from electronic health records in a stroke unit in Brazil

dc.contributor.authorZambom Valencio, Raquel Franco [UNESP]
dc.contributor.authorSouza, Juli Thomaz de [UNESP]
dc.contributor.authorWinckler, Fernanda Cristina [UNESP]
dc.contributor.authorModolo, Gabriel Pinheiro [UNESP]
dc.contributor.authorFerreira, Natalia Cristina [UNESP]
dc.contributor.authorZanati Bazan, Silmeia Garcia [UNESP]
dc.contributor.authorLange, Marcos Christiano [UNESP]
dc.contributor.authorMacedo de Freitas, Carlos Clayton [UNESP]
dc.contributor.authorRupp de Paiva, Sergio Alberto [UNESP]
dc.contributor.authorOliveira, Rogerio Carvalho de [UNESP]
dc.contributor.authorLuvizutto, Gustavo Jose
dc.contributor.authorBazan, Rodrigo [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionUniv Fed Parana
dc.contributor.institutionUniv Fed Triangulo Mineiro
dc.date.accessioned2022-04-28T17:22:47Z
dc.date.available2022-04-28T17:22:47Z
dc.date.issued2021-12-17
dc.description.abstractBackground: There is a high demand for stroke patient data in the public health systems of middle and low-income countries. Objective: To develop a stroke databank for integrating clinical or functional data and benchmarks from stroke patients. Methods: This was an observational, cross-sectional, prospective study. A tool was developed to collect all clinical data during hospitalizations due to stroke, using an electronic editor of structured forms that was integrated with electronic medical records. Validation of fields in the electronic editor was programmed using a structured query language (SQL). To store the results from SQL, a virtual table was created and programmed to update daily. To develop an interface between the data and user, the Embarcadero Delphi software and the DevExpress component were used to generate the information displayed on the screen. The data were extracted from the fields of the form and also from cross-referencing of other information from the computerized system, including patients who were admitted to the stroke unit. Results: The database was created and integrated with the hospital electronic system, thus allowing daily data collection. Quality indicators (benchmarks) were created in the database for the system to track and perform decision-making in conjunction with healthcare service managers, which resulted in improved processes and patient care after a stroke. An intelligent portal was created, in which the information referring to the patients was accessible. Conclusions: Based on semi-automated data collection, it was possible to create a dynamic and optimized Brazilian stroke databank.en
dc.description.affiliationUniv Estadual Paulista, Fac Med Botucatu, Botucatu, SP, Brazil
dc.description.affiliationUniv Estadual Paulista, Fac Med Botucatu, Dept Med Interna, Botucatu, SP, Brazil
dc.description.affiliationUniv Estadual Paulista, Fac Med Botucatu, Dept Neurol Psicol & Psiquiatria, Botucatu, SP, Brazil
dc.description.affiliationUniv Fed Parana, Complexo Hosp Clin, Curitiba, Parana, Brazil
dc.description.affiliationUniv Fed Triangulo Mineiro, Dept Fisioterapia Aplicada, Uberaba, MG, Brazil
dc.description.affiliationUnespUniv Estadual Paulista, Fac Med Botucatu, Botucatu, SP, Brazil
dc.description.affiliationUnespUniv Estadual Paulista, Fac Med Botucatu, Dept Med Interna, Botucatu, SP, Brazil
dc.description.affiliationUnespUniv Estadual Paulista, Fac Med Botucatu, Dept Neurol Psicol & Psiquiatria, Botucatu, SP, Brazil
dc.format.extent5
dc.identifierhttp://dx.doi.org/10.1590/0004-282X-ANP-2020-0558
dc.identifier.citationArquivos De Neuro-psiquiatria. Sao Paulo Sp: Assoc Arquivos Neuro- Psiquiatria, 5 p., 2021.
dc.identifier.doi10.1590/0004-282X-ANP-2020-0558
dc.identifier.issn0004-282X
dc.identifier.urihttp://hdl.handle.net/11449/218753
dc.identifier.wosWOS:000734894100001
dc.language.isoeng
dc.publisherAssoc Arquivos Neuro- Psiquiatria
dc.relation.ispartofArquivos De Neuro-psiquiatria
dc.sourceWeb of Science
dc.subjectStroke
dc.subjectBenchmarking
dc.subjectArtificial Intelligence
dc.subjectSupervised Machine Learning
dc.subjectEmergency Service
dc.subjectHospital
dc.titleSemi-automated data collection from electronic health records in a stroke unit in Brazilen
dc.typeArtigo
dcterms.rightsHolderAssoc Arquivos Neuro- Psiquiatria
dspace.entity.typePublication
unesp.author.orcid0000-0003-1057-5089[4]
unesp.author.orcid0000-0002-0607-8189[6]
unesp.author.orcid0000-0001-5210-4336[8]
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Medicina, Botucatupt
unesp.departmentNeurologia, Psicologia e Psiquiatria - FMBpt

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