Forecasting daily volume and acuity of patients in the emergency department
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/150410 |
Resumo: | This study aimed at analyzing the performance of four forecasting models in predicting the demand for medical care in terms of daily visits in an emergency department (ED) that handles high complexity cases, testing the influence of climatic and calendrical factors on demand behavior. We tested different mathematical models to forecast ED daily visits at Hospital de Cl´ınicas de Porto Alegre (HCPA), which is a tertiary care teaching hospital located in Southern Brazil. Model accuracy was evaluated using mean absolute percentage error (MAPE), considering forecasting horizons of 1, 7, 14, 21, and 30 days.The demand time serieswas stratified according to patient classification using the Manchester Triage System’s (MTS) criteria. Models tested were the simple seasonal exponential smoothing (SS), seasonal multiplicative Holt-Winters (SMHW), seasonal autoregressive integrated moving average (SARIMA), and multivariate autoregressive integrated moving average (MSARIMA). Performance of models varied according to patient classification, such that SS was the best choice when all types of patients were jointly considered, and SARIMA was the most accurate for modeling demands of very urgent (VU) and urgent (U) patients. The MSARIMA models taking into account climatic factors did not improve the performance of the SARIMA models, independent of patient classification. |
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Calegari, RafaelFogliatto, Flavio SansonLucini, Filipe RissieriNeyeloff, Jeruza LavanholiKuchenbecker, Ricardo de SouzaSchaan, Beatriz D'Agord2017-01-04T02:26:51Z20161748-6718http://hdl.handle.net/10183/150410001008496This study aimed at analyzing the performance of four forecasting models in predicting the demand for medical care in terms of daily visits in an emergency department (ED) that handles high complexity cases, testing the influence of climatic and calendrical factors on demand behavior. We tested different mathematical models to forecast ED daily visits at Hospital de Cl´ınicas de Porto Alegre (HCPA), which is a tertiary care teaching hospital located in Southern Brazil. Model accuracy was evaluated using mean absolute percentage error (MAPE), considering forecasting horizons of 1, 7, 14, 21, and 30 days.The demand time serieswas stratified according to patient classification using the Manchester Triage System’s (MTS) criteria. Models tested were the simple seasonal exponential smoothing (SS), seasonal multiplicative Holt-Winters (SMHW), seasonal autoregressive integrated moving average (SARIMA), and multivariate autoregressive integrated moving average (MSARIMA). Performance of models varied according to patient classification, such that SS was the best choice when all types of patients were jointly considered, and SARIMA was the most accurate for modeling demands of very urgent (VU) and urgent (U) patients. The MSARIMA models taking into account climatic factors did not improve the performance of the SARIMA models, independent of patient classification.application/pdfengComputational and mathematical methods in medicine. London. Vol. 2016, 3863268, 6 p.Serviços médicos de emergênciaPacientesAssistência ambulatorialForecasting daily volume and acuity of patients in the emergency departmentEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSORIGINAL001008496.pdf001008496.pdfTexto completo (inglês)application/pdf772643http://www.lume.ufrgs.br/bitstream/10183/150410/1/001008496.pdf4c6cc53b944f8e3e8b13a1e90c1cf1f2MD51TEXT001008496.pdf.txt001008496.pdf.txtExtracted Texttext/plain38375http://www.lume.ufrgs.br/bitstream/10183/150410/2/001008496.pdf.txt437d8e00b0ef7955434bc623b812c9c8MD52THUMBNAIL001008496.pdf.jpg001008496.pdf.jpgGenerated Thumbnailimage/jpeg1830http://www.lume.ufrgs.br/bitstream/10183/150410/3/001008496.pdf.jpg957fc40419cd17206bf8387d5e93215bMD5310183/1504102023-05-13 03:27:05.060573oai:www.lume.ufrgs.br:10183/150410Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2023-05-13T06:27:05Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Forecasting daily volume and acuity of patients in the emergency department |
title |
Forecasting daily volume and acuity of patients in the emergency department |
spellingShingle |
Forecasting daily volume and acuity of patients in the emergency department Calegari, Rafael Serviços médicos de emergência Pacientes Assistência ambulatorial |
title_short |
Forecasting daily volume and acuity of patients in the emergency department |
title_full |
Forecasting daily volume and acuity of patients in the emergency department |
title_fullStr |
Forecasting daily volume and acuity of patients in the emergency department |
title_full_unstemmed |
Forecasting daily volume and acuity of patients in the emergency department |
title_sort |
Forecasting daily volume and acuity of patients in the emergency department |
author |
Calegari, Rafael |
author_facet |
Calegari, Rafael Fogliatto, Flavio Sanson Lucini, Filipe Rissieri Neyeloff, Jeruza Lavanholi Kuchenbecker, Ricardo de Souza Schaan, Beatriz D'Agord |
author_role |
author |
author2 |
Fogliatto, Flavio Sanson Lucini, Filipe Rissieri Neyeloff, Jeruza Lavanholi Kuchenbecker, Ricardo de Souza Schaan, Beatriz D'Agord |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Calegari, Rafael Fogliatto, Flavio Sanson Lucini, Filipe Rissieri Neyeloff, Jeruza Lavanholi Kuchenbecker, Ricardo de Souza Schaan, Beatriz D'Agord |
dc.subject.por.fl_str_mv |
Serviços médicos de emergência Pacientes Assistência ambulatorial |
topic |
Serviços médicos de emergência Pacientes Assistência ambulatorial |
description |
This study aimed at analyzing the performance of four forecasting models in predicting the demand for medical care in terms of daily visits in an emergency department (ED) that handles high complexity cases, testing the influence of climatic and calendrical factors on demand behavior. We tested different mathematical models to forecast ED daily visits at Hospital de Cl´ınicas de Porto Alegre (HCPA), which is a tertiary care teaching hospital located in Southern Brazil. Model accuracy was evaluated using mean absolute percentage error (MAPE), considering forecasting horizons of 1, 7, 14, 21, and 30 days.The demand time serieswas stratified according to patient classification using the Manchester Triage System’s (MTS) criteria. Models tested were the simple seasonal exponential smoothing (SS), seasonal multiplicative Holt-Winters (SMHW), seasonal autoregressive integrated moving average (SARIMA), and multivariate autoregressive integrated moving average (MSARIMA). Performance of models varied according to patient classification, such that SS was the best choice when all types of patients were jointly considered, and SARIMA was the most accurate for modeling demands of very urgent (VU) and urgent (U) patients. The MSARIMA models taking into account climatic factors did not improve the performance of the SARIMA models, independent of patient classification. |
publishDate |
2016 |
dc.date.issued.fl_str_mv |
2016 |
dc.date.accessioned.fl_str_mv |
2017-01-04T02:26:51Z |
dc.type.driver.fl_str_mv |
Estrangeiro info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
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article |
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publishedVersion |
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http://hdl.handle.net/10183/150410 |
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1748-6718 |
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001008496 |
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http://hdl.handle.net/10183/150410 |
dc.language.iso.fl_str_mv |
eng |
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eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Computational and mathematical methods in medicine. London. Vol. 2016, 3863268, 6 p. |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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