RESUMO
Objetivo: Analizar el impacto de la implementación de medidas para reducir el número de pacientes ubicados en urgencias en es pera de cama de hospitalización. Método: Tipo de estudio: comparativo con un análisis retrospectivo. Se compararon dos periodos: periodo 1 (nov 06-oct 07) y periodo 2 (nov 07-oct 08). Ámbito: Hospitalde Sant Boi, hospital general de 126 camas, en Sant Boi de Llobregat (Barcelona). Medidas implementadas: disminución de la estancia prequirúrgica, incremento de la cirugía mayor ambulatoria (CMA) y potenciación del ingreso en una unidad de corta estancia médica (UCE). Variables estudiadas: admisiones en el SUH, ingresos hospitalarios, ingresos de CMA, el número de días en que hay al menos 1 paciente pendiente de cama hospitalaria en el SUH a las 8:00 horas, estancia promedio hospitalaria, actividad y estancia promedio en la UCE. Resultados: El total de admisiones en el SUH fue de 57.140 en el periodo 1, y 71.280 en el periodo 2, con 4.840 (8,4%) y 5.385 (7,5%) ingresos, respectivamente. La estancia media de hospitalización disminuyó de 5,2 días a 4,5 días (p < 0,001). En 86 días del periodo 1, uno o más pacientes permanecían en el SUH pendientes de cama (307 pacientes/año), frente a 11 días en el período 2 (26 pacientes/año). Conclusiones: En nuestra experiencia, las medidas de gestión aplicadas fueron eficaces en la disminución del número de pacientes pendientes de cama en urgencias (AU)
Objective: To analyze the impact of hospital management measures to reduce the number of patients held in an emergency department while awaiting admission. Methods: Type of study: retrospective, comparing 2 periods, November 2006 to October 2007 and November 2007 to October 2008. Setting: Hospital de Sant Boi, a 126-bed general hospital in Sant Boi de Llobregat in the province of Barcelona. Management measures: decreased presurgical stay, increased use of ambulatory surgical procedures, and increased use of a medical short-stay unit. Variables studied: emergency department admissions, hospital ward admissions, admissions for ambulatory surgical procedures, number of days in which at least 1 patient was in the emergency department at 8 A.M. while waiting for a bed, mean hospital stay, and admissions and average time spent in the short-stay unit. Results: A total of 57140 patients were admitted to the emergency department in the first period and 71280 in the second period; 4840 (8.4%) were admitted to hospital in the first period and 5385 (7.5%) in the second. The average length of stay was 5.19 days in the first period and 4.54 days in the second (P<.001). At least 1 patient was waiting in the emergency department for a hospital bed to become available on 86 days in the first period (307 patients/year) and11 days in the second period (26 patients/year). Conclusions: The management measures applied in this case were effective in reducing the number of patients held in the emergency department while waiting for admission (AU)
Assuntos
Serviço Hospitalar de Emergência/organização & administração , Número de Leitos em Hospital/estatística & dados numéricos , Administração dos Cuidados ao Paciente/métodos , Eficiência Organizacional/normas , Melhoria de Qualidade , Mau Uso de Serviços de Saúde , Hospitalização/tendênciasRESUMO
Fundamento: La prevalencia de discapacidad en la poblacióngeneral presenta una gran variabilidad geográfica, de manera queidentificar aquellos factores que pudieran explicarla será importantepara la planificación de políticas sociales. En este trabajo se analizala variabilidad de la discapacidad por comunidades autónomasdesde una doble vertiente, los factores individuales y del entorno.Métodos: Los datos proceden principalmente de la Encuestade Discapacidad, Deficiencias y Estado de Salud de 1999 y delInebase, ambas del Instituto Nacional de Estadística (INE). Secalculó la prevalencia de discapacidad simple y ajustada por edadde las CCAA. Se analizan los factores individuales asociados a ladiscapacidad mediante una regresión logística y los factores individualesy de la comunidad autónoma conjuntamente con unaregresión logística de dos niveles.Resultados: La prevalencia de discapacidad muestra una diferenciamáxima de 5,75 puntos entre las comunidades autónomas.En la regresión logística la comunidad de residencia fue estadísticamentesignificativa (OR: 3,35 en la de mayor prevalencia respectoa la de menor) junto con otras variables individuales: edad (ORde 40-64= 1,78 OR de 65-79= 1,87 y OR de >79= 3,34), sexo (ORmujer= 0,66), situación laboral (OR sin trabajo=2,25 OR amascasa/estudiante=1,39 y OR otros=2,03), estado de salud (OR regular=1,69 OR malo/muy malo= 2,05) y enfermedades crónicas (OR1-3=1,56 OR4-6=1,82 OR>6=2,59). En la regresión de dos niveleslas variables individuales explican poca varianza (s=0,261) y ningunade las variables relativas a las CCAA mejora el modelo.Conclusiones: Las características individuales no explicansuficientemente la variabilidad de la discapacidad entre CCAA yno se han identificado variables del entorno que sean significativas(AU)
Background: The prevalence of disability shows a highgeographical variability and the identification of factors that couldexplain these variations can be usuful to the heath and socialwelfare planning. Here the analysis of disability variations amongautonomous regions in Spain is made taking into accountindividual and geographical setting factors together.Methods: Data come from the Spanish Disability,Impairment and Health Status survey of 1999 and from Inebaseboth of the National Institute for Statistics. The prevalence ofdisability crude and adjusted by age was calculated for eachautonomous region. Individual factors related to disability areidentified by means of a logistic regression. The analysisaccounting for both, individual and geographical setting factorswas performed by means of a logistic regression of two levels.Results: Disability prevalence showed a maximum differenceof 5.75 points among regions. In a logistic regression the region ofresidence was statistically significant (OR: 3.35 in the highestrated region related to the lowest) beside several individual factors:age (OR 40-64= 1,78 OR 65-79= 1,87 and OR >79= 3,34), sex(OR women= 0,66), working status (OR unemployment=2,25 ORhousewife/student=1,39 y OR other=2,03), health status (ORregular= 1,69 OR bad/very bad= 2,05) and chronic diseases (OR1-3=1,56 OR 4-6=1,82 OR >6=2,59). Individual factors accountedfor a very few variance at the two levels regression model(s=0,261) and none of the regional variables improved the model.Conclusions: Individual factors do not explain enough theobserved disability variations among the regions and none factorrelated to the geographical setting has been identified asstatistically significant(AU)
Assuntos
Humanos , Pessoas com Deficiência/estatística & dados numéricos , Análise de Pequenas Áreas , Estudos Transversais , Análise Multivariada , Espanha/epidemiologiaRESUMO
BACKGROUND: The prevalence of disability shows a high geographical variability and the identification of factors that could explain these variations can be useful to the heath and social welfare planning. Here the analysis of disability variations among autonomous regions in Spain is made taking into account individual and geographical setting factors together. METHODS: Data come from the Spanish Disability, Impairment and Health Status survey of 1999 and from Inebase both of the National Institute for Statistics. The prevalence of disability crude and adjusted by age was calculated for each autonomous region. Individual factors related to disability are identified by means of a logistic regression. The analysis accounting for both, individual and geographical setting factors was performed by means of a logistic regression of two levels. RESULTS: Disability prevalence showed a maximum difference of 5.75 points among regions. In a logistic regression the region of residence was statistically significant (OR: 3.35 in the highest rated region related to the lowest) beside several individual factors: age (OR 40-64= 1.78 OR 65-79= 1.87 and OR >79= 3.34), sex (OR women= 0.66), working status (OR unemployment=2.25 OR housewife/student=1.39 y OR other=2.03), health status (OR regular= 1.69 OR bad/very bad= 2.05) and chronic diseases (OR 1-3=1.56 OR 4-6=1.82 OR > 6=2.59). Individual factors accounted for a very few variance at the two levels regression model (s=0.261) and none of the regional variables improved the model. CONCLUSIONS: Individual factors do not explain enough the observed disability variations among the regions and none factor related to the geographical setting has been identified as statistically significant.
Assuntos
Pessoas com Deficiência/estatística & dados numéricos , Adolescente , Adulto , Idoso , Criança , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Prevalência , Espanha/epidemiologia , Adulto JovemRESUMO
BACKGROUND: In the next future an important demographical ageing will imply a rise in the levels of co morbidity, disability and dependence of the population. The objective if this work was to estimate the dependences profile by means of assessing the levels of severity of the disability in the Spanish general population. METHODS: Data come from the disease, disability and health status survey of 1999 of the Spanish Institute for Statistics, which includes 36 limitations with an score of severity (from 0= absence to 4= unable). These limitations were grouped in five kinds of disability, the mean score of severity was computed for each one, and grouped in five levels of dependence. To check the relationship between limitations and severity an analysis of correspondence was performed. To identify the pattern of dependence a multiple correspondence and a clusters analysis were computed using the variables of age, sex, kind of disability and level of dependence. RESULTS: There is a relationship between severity and some limitations (being the limitation on daily activities associated to the highest severity). Five groups of dependent people were identified. Those with lower dependence were middle aged, men and having sensorial disabilities and those with higher dependence were mainly women, older than 80 and with disabilities on mobility and on the activities of daily living. CONCLUSIONS: There are five groups of dependent population and this study allows estimating its frequency among the general population what will be very useful to evaluate the amount of resources necessary to take care of them.