Avaliação do desempenho e cenários alternativos em um samu utilizando o modelo hipercubo estacionário e não-estacionário
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Data
2017-10-09
Autores
Beojone, Caio Vítor [UNESP]
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Editor
Universidade Estadual Paulista (Unesp)
Resumo
Vários Sistemas de Atendimento Emergenciais (SAE’s) sofrem com as variações diárias da demanda e da disponibilidade das ambulâncias. Nesses sistemas pode haver flutuação do desempenho ao longo do dia devido, por exemplo, a mudança no número de servidores e nas taxas de chegada, levando à necessidade de considerar explicitamente tais variações em uma extensão ao modelo hipercubo ainda não explorada na literatura. Como ocorre em alguns SAE’s, as ambulâncias melhor equipadas são reservadas para o atendimento exclusivo de chamados com risco de vida. Dessa maneira, a política de despacho pode ser diferenciada com a finalidade de reservar totalmente o atendimento de alguns servidores para certas gravidades de ocorrências. Além disso, somam-se à natureza aleatória desses sistemas, como por exemplo, as incertezas da disponibilidade das ambulâncias, a chegada de um novo chamado e sua localização. Nesse contexto, os objetivos do presente estudo são: (i) estender o modelo hipercubo de filas para reserva total de capacidade, dependendo do tipo do chamado; (ii) estender o modelo hipercubo de filas para torná-lo mais eficiente computacionalmente, sem haver perda de precisão durante a modelagem e resolução; e (iii) propor uma abordagem baseada no modelo hipercubo não-estacionário para organização do trabalho das ambulâncias em qualquer momento do dia. Para verificar a viabilidade e a aplicabilidade dessas abordagens, é realizado um estudo de caso no SAMU da cidade de Bauru (SAMU-Bauru) que, além de reservar suas ambulâncias avançadas para ocorrências mais graves, é afetado pelas variações diárias na demanda e disponibilidade das ambulâncias. Além da configuração original do SAMU-Bauru, estudada em duas etapas, foram analisados um total de quatro cenários alternativos que consideram questões importantes: o impacto do aumento na demanda do período mais congestionado; a mitigação desse impacto incluindo uma nova ambulância; a alteração do horário das pausas diárias; e o impacto de aumentos na demanda em horários específicos do dia. Foram calculadas importantes medidas de desempenho para cada cenário como a carga de trabalho, tempos médios de espera e tempos médios de resposta. Os resultados mostram que as extensões realizadas no modelo hipercubo são capazes de analisar satisfatoriamente sistemas como o SAMU-Bauru, além de possibilitar a criação e mensuração de propostas de melhorias nos níveis táticos e operacionais.
Many Emergency Service Systems face daily variations on demand and ambulance availability. These systems may suffer, for example, performance fluctuations throughout the day, changes on the number of servers and on arrival rates, leading to the need to explicitly consider such variations in a hypercube model extension not yet explored in the literature. As occurs in some SAMU’s, which reserve their best equipped ambulances to exclusively serve life-threating requests. Therefore, the dispatch policy can be differentiated in order to completely reserve the service of some ambulances to more severe requests. These problems add up to the random nature of these systems with uncertainties upon ambulance availability or the arrival of a new request and its location. Thus, this study aims to: (i) extend the hypercube queueing model to be able to capture the complete capacity reservation of advanced ambulances, depending on the request classification; (ii) extend the hypercube model in order to make it more computationally efficient, without losing any information during modeling and resolution. (iii) propose an approach based on nonstationary hypercube queueing model to organize the operation of ambulances at any time of the day. To verify the feasibility of these approaches, a case study is carried out on the SAMU from Bauru city (SAMU-Bauru), which, in addition to the advanced ambulance reservation for life-threating requests, is affected by daily variations in demand and ambulance availability. In addition to the original configuration of SAMU-Bauru, studied on a two-step approach, we studied a total of four alternative scenarios that exploited important matters as: the impact of average demand increase on the congestion peak; mitigation of this impact by including a new ambulance; changing the schedule of daily breaks; and the impact of increases in the demand at specific hours of the day. We calculated important performance measures for each scenario, such as workload, mean waiting times and mean response times. Results show that the proposed extensions to the hypercube model are capable of satisfactorily analyze systems such as SAMU-Bauru, besides making it possible to create and to measure improvements proposals in tactical and operational levels.
Many Emergency Service Systems face daily variations on demand and ambulance availability. These systems may suffer, for example, performance fluctuations throughout the day, changes on the number of servers and on arrival rates, leading to the need to explicitly consider such variations in a hypercube model extension not yet explored in the literature. As occurs in some SAMU’s, which reserve their best equipped ambulances to exclusively serve life-threating requests. Therefore, the dispatch policy can be differentiated in order to completely reserve the service of some ambulances to more severe requests. These problems add up to the random nature of these systems with uncertainties upon ambulance availability or the arrival of a new request and its location. Thus, this study aims to: (i) extend the hypercube queueing model to be able to capture the complete capacity reservation of advanced ambulances, depending on the request classification; (ii) extend the hypercube model in order to make it more computationally efficient, without losing any information during modeling and resolution. (iii) propose an approach based on nonstationary hypercube queueing model to organize the operation of ambulances at any time of the day. To verify the feasibility of these approaches, a case study is carried out on the SAMU from Bauru city (SAMU-Bauru), which, in addition to the advanced ambulance reservation for life-threating requests, is affected by daily variations in demand and ambulance availability. In addition to the original configuration of SAMU-Bauru, studied on a two-step approach, we studied a total of four alternative scenarios that exploited important matters as: the impact of average demand increase on the congestion peak; mitigation of this impact by including a new ambulance; changing the schedule of daily breaks; and the impact of increases in the demand at specific hours of the day. We calculated important performance measures for each scenario, such as workload, mean waiting times and mean response times. Results show that the proposed extensions to the hypercube model are capable of satisfactorily analyze systems such as SAMU-Bauru, besides making it possible to create and to measure improvements proposals in tactical and operational levels.
Descrição
Palavras-chave
Teoria das filas, Pesquisa operacional em saúde, Serviço médico emergencial, Sistemas não-estacionários, Reserva de capacidade, Queueing theory, Operational research on health services, Emergency medical systems, Nonstationary systems, Capacity reservation