Use of comorbidity measures to predict the risk of death in Brazilian in-patients

Detalhes bibliográficos
Autor(a) principal: Martins, Monica
Data de Publicação: 2010
Tipo de documento: Artigo
Idioma: por
eng
Título da fonte: Revista de Saúde Pública
Texto Completo: https://www.revistas.usp.br/rsp/article/view/32790
Resumo: OBJECTIVE: To assess the use of comorbidity measures to predict the risk of death in Brazilian in-patients. METHODS: Data from the Sistema de Informações Hospitalares do Sistema Único de Saúde (Unified Health System Hospital Information System) were used, which enables only one secondary diagnosis to be recorded. A total of 1,607,697 hospitalizations were selected, all of which occurred in Brazil, between 2003 and 2004, and whose main diagnoses were: ischemic heart disease, congestive cardiac failure, stroke and pneumonia. Charlson Index and Elixhauser comorbidities were the comorbidity measures used. In addition, the simple record of a certain secondary diagnosis was also used. Logistic regression was applied to assess the impact of comorbidity measures on the estimate of risk of death. The baseline model included the following variables: age, sex and main diagnosis. Models to predict death were assessed, based on C-statistic and Hosmer-Lemeshow test. RESULTS: Hospital mortality rate was 10.4% and mean length of stay was 5.7 days. The majority (52%) of hospitalizations occurred among men and mean age was 62.6 years. Of all hospitalizations, 5.4% included a recorded secondary diagnosis, although the odds ratio between death and presence of comorbidity was 1.93. The baseline model showed a discriminatory capacity (C-statistic) of 0.685. The improvement in the models, attributed to the introduction of comorbidity indices, was poor, equivalent to zero when C-statistic with only two digits was considered. CONCLUSIONS: Although the introduction of three comorbidity measures in distinct models to predict death improved the predictive capacity of the baseline model, the values obtained are still considered insufficient. The accuracy of this type of measure is influenced by the completeness of the source of information. In this sense, high underreporting of secondary diagnosis, in addition to the well-known lack of space to note down this type of information in the Sistema de Informações Hospitalares, are the main explanatory factors for the results found.
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spelling Use of comorbidity measures to predict the risk of death in Brazilian in-patients Uso de medidas de comorbilidades para predicción de riesgo de óbito en pacientes brasileros hospitalizados Uso de medidas de comorbidades para predição de risco de óbito em pacientes brasileiros hospitalizados ComorbidadeMortalidade HospitalarRisco AjustadoAvaliação de Serviços de SaúdeComorbilidadMortalidad HospitalariaAjuste de RiesgoEvaluación de Servicios de SaludComorbidityHospital MortalityRisk AdjustmentHealth Services Evaluation OBJECTIVE: To assess the use of comorbidity measures to predict the risk of death in Brazilian in-patients. METHODS: Data from the Sistema de Informações Hospitalares do Sistema Único de Saúde (Unified Health System Hospital Information System) were used, which enables only one secondary diagnosis to be recorded. A total of 1,607,697 hospitalizations were selected, all of which occurred in Brazil, between 2003 and 2004, and whose main diagnoses were: ischemic heart disease, congestive cardiac failure, stroke and pneumonia. Charlson Index and Elixhauser comorbidities were the comorbidity measures used. In addition, the simple record of a certain secondary diagnosis was also used. Logistic regression was applied to assess the impact of comorbidity measures on the estimate of risk of death. The baseline model included the following variables: age, sex and main diagnosis. Models to predict death were assessed, based on C-statistic and Hosmer-Lemeshow test. RESULTS: Hospital mortality rate was 10.4% and mean length of stay was 5.7 days. The majority (52%) of hospitalizations occurred among men and mean age was 62.6 years. Of all hospitalizations, 5.4% included a recorded secondary diagnosis, although the odds ratio between death and presence of comorbidity was 1.93. The baseline model showed a discriminatory capacity (C-statistic) of 0.685. The improvement in the models, attributed to the introduction of comorbidity indices, was poor, equivalent to zero when C-statistic with only two digits was considered. CONCLUSIONS: Although the introduction of three comorbidity measures in distinct models to predict death improved the predictive capacity of the baseline model, the values obtained are still considered insufficient. The accuracy of this type of measure is influenced by the completeness of the source of information. In this sense, high underreporting of secondary diagnosis, in addition to the well-known lack of space to note down this type of information in the Sistema de Informações Hospitalares, are the main explanatory factors for the results found. OBJETIVO: Evaluar el uso de medidas de comorbilidad para predecir el riesgo de óbito en pacientes brasileros. MÉTODOS: Fueron utilizados datos de internaciones obtenidos del Sistema de Informaciones Hospitalarias del Sistema Único de Salud, que permite el registro de solamente un diagnóstico secundario. Fueron seleccionadas 1.607.697 internaciones ocurridas en Brasil en 2003 y 2004, cuyos diagnósticos principales fueron enfermedad isquémica del corazón, insuficiencia cardiaca congestiva, enfermedades cerebro-vasculares y neumonía. El Índice de Charlson y las comorbilidades de Elixhauser fueron las medidas de comorbilidad utilizadas; el simple registro de algún diagnóstico secundario fue también empleado. La regresión logística fue aplicada para evaluar el impacto de las medidas de comorbilidad en la estimativa de la probabilidad de óbito. El modelo de base incluyó las siguientes variables: edad, sexo y diagnóstico principal. Los modelos de predicción de óbitos fueron evaluados con base en la estadística C y en la prueba de Hosmer-Lemeshow. RESULTADOS: La tasa de mortalidad hospitalaria fue 10,4% y el tiempo promedio de permanencia fue 5,7 días. La mayoría (52%) de las internaciones ocurrió en hombres y la edad promedio fue 62,6 años. Del total de internaciones, 5,4% presentaba un diagnóstico secundario registrado, pero el odds ratio entre óbito y presencia de comorbilidad fue de 1,93. El modelo de base presentó una capacidad de discriminación (estadística C) de 0,685. La mejoría en los modelos atribuida a la introducción de los índices de comorbilidad fue débil - equivalió a cero cuando se consideró la estadística C con solamente dos dígitos. CONCLUSIONES: A pesar de la introducción de las tres medidas de comorbilidad en los distintos modelos de predicción de óbito haya mejorado la capacidad predictiva del modelo de base, los valores obtenidos aún son considerados insuficientes. La precisión de este tipo de medida es influenciada por la completitud de la fuente de información. En ese sentido, el alto sub-registro de diagnóstico secundario, aliado a la conocida insuficiencia de espacio para anotación de este tipo de información en el Sistema de Informaciones Hospitalarias, son los principales elementos explicativos de los resultados encontrados. OBJETIVO: Avaliar o uso de medidas de comorbidade para predizer o risco de óbito em pacientes brasileiros. MÉTODOS: Foram utilizados dados de internações obtidos do Sistema de Informações Hospitalares do Sistema Único de Saúde, que permite o registro de somente um diagnóstico secundário. Foram selecionadas 1.607.697 internações ocorridas no Brasil em 2003 e 2004, cujos diagnósticos principais foram doença isquêmica do coração, insuficiência cardíaca congestiva, doenças cérebro-vasculares e pneumonia. O Índice de Charlson e as comorbidades de Elixhauser foram as medidas de comorbidade utilizadas; o simples registro de algum diagnóstico secundário foi também empregado. A regressão logística foi aplicada para avaliar o impacto das medidas de comorbidade na estimava da chance de óbito. O modelo de base incluiu as seguintes variáveis: idade, sexo e diagnóstico principal. Os modelos de predição de óbitos foram avaliados com base na estatística C e no teste de Hosmer-Lemeshow. RESULTADOS: A taxa de mortalidade hospitalar foi 10,4% e o tempo médio de permanência foi 5,7 dias. A maioria (52%) das internações ocorreu em homens e a idade média foi 62,6 anos. Do total de internações, 5,4% apresentava um diagnóstico secundário registrado, mas o odds ratio entre óbito e presença de comorbidade foi de 1,93. O modelo de base apresentou uma capacidade de discriminação (estatística C) de 0,685. A melhoria nos modelos atribuída à introdução dos índices de comorbidade foi fraca - equivaleu a zero quando se considerou a estatística C com somente dois dígitos. CONCLUSÕES: Embora a introdução das três medidas de comorbidade nos distintos modelos de predição de óbito tenha melhorado a capacidade preditiva do modelo de base, os valores obtidos ainda são considerados insuficientes. A precisão desse tipo de medida é influenciada pela completitude da fonte de informação. Nesse sentido, o alto sub-registro de diagnóstico secundário, aliado à conhecida insuficiência de espaço para anotação desse tipo de informação no Sistema de Informações Hospitalares, são os principais elementos explicativos dos resultados encontrados. Universidade de São Paulo. Faculdade de Saúde Pública2010-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://www.revistas.usp.br/rsp/article/view/3279010.1590/S0034-89102010005000003Revista de Saúde Pública; Vol. 44 No. 3 (2010); 448-456 Revista de Saúde Pública; Vol. 44 Núm. 3 (2010); 448-456 Revista de Saúde Pública; v. 44 n. 3 (2010); 448-456 1518-87870034-8910reponame:Revista de Saúde Públicainstname:Universidade de São Paulo (USP)instacron:USPporenghttps://www.revistas.usp.br/rsp/article/view/32790/35291https://www.revistas.usp.br/rsp/article/view/32790/35292Copyright (c) 2017 Revista de Saúde Públicainfo:eu-repo/semantics/openAccessMartins, Monica2012-07-10T02:20:15Zoai:revistas.usp.br:article/32790Revistahttps://www.revistas.usp.br/rsp/indexONGhttps://www.revistas.usp.br/rsp/oairevsp@org.usp.br||revsp1@usp.br1518-87870034-8910opendoar:2012-07-10T02:20:15Revista de Saúde Pública - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Use of comorbidity measures to predict the risk of death in Brazilian in-patients
Uso de medidas de comorbilidades para predicción de riesgo de óbito en pacientes brasileros hospitalizados
Uso de medidas de comorbidades para predição de risco de óbito em pacientes brasileiros hospitalizados
title Use of comorbidity measures to predict the risk of death in Brazilian in-patients
spellingShingle Use of comorbidity measures to predict the risk of death in Brazilian in-patients
Martins, Monica
Comorbidade
Mortalidade Hospitalar
Risco Ajustado
Avaliação de Serviços de Saúde
Comorbilidad
Mortalidad Hospitalaria
Ajuste de Riesgo
Evaluación de Servicios de Salud
Comorbidity
Hospital Mortality
Risk Adjustment
Health Services Evaluation
title_short Use of comorbidity measures to predict the risk of death in Brazilian in-patients
title_full Use of comorbidity measures to predict the risk of death in Brazilian in-patients
title_fullStr Use of comorbidity measures to predict the risk of death in Brazilian in-patients
title_full_unstemmed Use of comorbidity measures to predict the risk of death in Brazilian in-patients
title_sort Use of comorbidity measures to predict the risk of death in Brazilian in-patients
author Martins, Monica
author_facet Martins, Monica
author_role author
dc.contributor.author.fl_str_mv Martins, Monica
dc.subject.por.fl_str_mv Comorbidade
Mortalidade Hospitalar
Risco Ajustado
Avaliação de Serviços de Saúde
Comorbilidad
Mortalidad Hospitalaria
Ajuste de Riesgo
Evaluación de Servicios de Salud
Comorbidity
Hospital Mortality
Risk Adjustment
Health Services Evaluation
topic Comorbidade
Mortalidade Hospitalar
Risco Ajustado
Avaliação de Serviços de Saúde
Comorbilidad
Mortalidad Hospitalaria
Ajuste de Riesgo
Evaluación de Servicios de Salud
Comorbidity
Hospital Mortality
Risk Adjustment
Health Services Evaluation
description OBJECTIVE: To assess the use of comorbidity measures to predict the risk of death in Brazilian in-patients. METHODS: Data from the Sistema de Informações Hospitalares do Sistema Único de Saúde (Unified Health System Hospital Information System) were used, which enables only one secondary diagnosis to be recorded. A total of 1,607,697 hospitalizations were selected, all of which occurred in Brazil, between 2003 and 2004, and whose main diagnoses were: ischemic heart disease, congestive cardiac failure, stroke and pneumonia. Charlson Index and Elixhauser comorbidities were the comorbidity measures used. In addition, the simple record of a certain secondary diagnosis was also used. Logistic regression was applied to assess the impact of comorbidity measures on the estimate of risk of death. The baseline model included the following variables: age, sex and main diagnosis. Models to predict death were assessed, based on C-statistic and Hosmer-Lemeshow test. RESULTS: Hospital mortality rate was 10.4% and mean length of stay was 5.7 days. The majority (52%) of hospitalizations occurred among men and mean age was 62.6 years. Of all hospitalizations, 5.4% included a recorded secondary diagnosis, although the odds ratio between death and presence of comorbidity was 1.93. The baseline model showed a discriminatory capacity (C-statistic) of 0.685. The improvement in the models, attributed to the introduction of comorbidity indices, was poor, equivalent to zero when C-statistic with only two digits was considered. CONCLUSIONS: Although the introduction of three comorbidity measures in distinct models to predict death improved the predictive capacity of the baseline model, the values obtained are still considered insufficient. The accuracy of this type of measure is influenced by the completeness of the source of information. In this sense, high underreporting of secondary diagnosis, in addition to the well-known lack of space to note down this type of information in the Sistema de Informações Hospitalares, are the main explanatory factors for the results found.
publishDate 2010
dc.date.none.fl_str_mv 2010-06-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://www.revistas.usp.br/rsp/article/view/32790
10.1590/S0034-89102010005000003
url https://www.revistas.usp.br/rsp/article/view/32790
identifier_str_mv 10.1590/S0034-89102010005000003
dc.language.iso.fl_str_mv por
eng
language por
eng
dc.relation.none.fl_str_mv https://www.revistas.usp.br/rsp/article/view/32790/35291
https://www.revistas.usp.br/rsp/article/view/32790/35292
dc.rights.driver.fl_str_mv Copyright (c) 2017 Revista de Saúde Pública
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2017 Revista de Saúde Pública
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Universidade de São Paulo. Faculdade de Saúde Pública
publisher.none.fl_str_mv Universidade de São Paulo. Faculdade de Saúde Pública
dc.source.none.fl_str_mv Revista de Saúde Pública; Vol. 44 No. 3 (2010); 448-456
Revista de Saúde Pública; Vol. 44 Núm. 3 (2010); 448-456
Revista de Saúde Pública; v. 44 n. 3 (2010); 448-456
1518-8787
0034-8910
reponame:Revista de Saúde Pública
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Revista de Saúde Pública
collection Revista de Saúde Pública
repository.name.fl_str_mv Revista de Saúde Pública - Universidade de São Paulo (USP)
repository.mail.fl_str_mv revsp@org.usp.br||revsp1@usp.br
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