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Abstract(s)
Este trabalho aborda o problema de gestão de camas hospitalares numa Unidade de Cuidados Intensivos (UCI), de um hospital algarvio, região onde a oscilação populacional é evidente ao longo dos meses, atendendo ao turismo existente. O principal objetivo foi compreender o impacto do aumento ou diminuição de camas em UCI, através da criação de um modelo de Simulação por Eventos Discretos (SED), por forma a manter o equilíbrio entre a qualidade do serviço prestado e o impacto económico-financeiro. A UCI do estudo é composta por nove camas. Os dados foram recolhidos do programa B-Simpleã e verificou-se um total de 630 doentes nos dois anos do estudo, dos quais 15,6% não eram residentes no Algarve. A taxa de ocupação mensal variou entre os 55% e os 94%, o tempo médio de internamento foi de 6,28 dias e o tempo médio entre chegadas foi de 1,15 dias.
Utilizou-se o programa Stat::Fit, para encontrar as distribuições probabilísticas com melhor ajustamento ao padrão de chegadas dos doentes e ao tempo de internamento.
O modelo de SED, criado no programa Simul8â, pretendeu simular a taxa de ocupação de cada cama. Foram criados seis cenários de simulação, três com o aumento de camas
hospitalares e três com diminuição e verificou-se o impacto na taxa de ocupação de cada cama. Por outro lado, através do cálculo da probabilidade de todas as camas estarem
ocupadas, percebeu-se a influência no número de doentes a serem transferidos por falta de camas em UCI. Foi feita também uma estimativa do número de enfermeiros necessários para cada cenário.
Os resultados demonstraram que será aceitável o aumento ou diminuição de uma cama. Um maior aumento leva a gastos desnecessários, enquanto uma maior diminuição aumenta a necessidade de transferir doentes para outros hospitais. Dado que a UCI sofre oscilações da taxa de ocupação ao longo do ano, sugere-se, no entanto, que o ajuste de camas não seja feito apenas pela avaliação de um único indicador.
This work addresses the problem of managing hospital beds in an Intensive Care Unit (ICU) of an Algarve hospital, a region where there is a varied population fluctuation over the months, taking into account the existing tourism. The main objective was to understand the impact of increasing or decreasing ICU beds, using a Discrete Event Simulation (DES) model, to maintain the balance between the quality of the service provided and the economicfinancial impact. The ICU studied has nine beds. The data was collected from the B-Simple program and a total of 630 patients were identified in the two years of the study, of which 15.6% were not residents of the Algarve. The monthly occupancy rate of the beds varied between 55% and 94%, the average length of stay was 6.28 days and the average time between arrivals was 1.15 days. The Stat::Fit program was used to find the probabilistic distributions that provide the best fit to represent the patients' arrival interval and the length of stay. The DES model, created in Simul8â, aims to simulate the occupancy rate of each bed. Six simulation scenarios were created, three with an increase in hospital beds and three with a decrease in the number of beds, to assess their impact on the occupancy rate of each bed. On the other hand, by calculating the probability of all beds being occupied, we were able to assess the influence that changing the number of available beds would have on the number of patients to be transferred to other units due to a lack of beds in the ICU. An estimate was also made of the number of nurses needed for each scenario.
This work addresses the problem of managing hospital beds in an Intensive Care Unit (ICU) of an Algarve hospital, a region where there is a varied population fluctuation over the months, taking into account the existing tourism. The main objective was to understand the impact of increasing or decreasing ICU beds, using a Discrete Event Simulation (DES) model, to maintain the balance between the quality of the service provided and the economicfinancial impact. The ICU studied has nine beds. The data was collected from the B-Simple program and a total of 630 patients were identified in the two years of the study, of which 15.6% were not residents of the Algarve. The monthly occupancy rate of the beds varied between 55% and 94%, the average length of stay was 6.28 days and the average time between arrivals was 1.15 days. The Stat::Fit program was used to find the probabilistic distributions that provide the best fit to represent the patients' arrival interval and the length of stay. The DES model, created in Simul8â, aims to simulate the occupancy rate of each bed. Six simulation scenarios were created, three with an increase in hospital beds and three with a decrease in the number of beds, to assess their impact on the occupancy rate of each bed. On the other hand, by calculating the probability of all beds being occupied, we were able to assess the influence that changing the number of available beds would have on the number of patients to be transferred to other units due to a lack of beds in the ICU. An estimate was also made of the number of nurses needed for each scenario.
Description
Keywords
Simulação por eventos discretos Unidade de cuidados intensivos Gestão de camas Capacidade de resposta Simul8