The re-planning and scheduling of surgical cases in the operating room department after block release time with resource rescheduling

Akbarzadeh, Babak; Moslehi, Ghasem; Reisi–Nafchi, Mohammad; Maenhout, Broos

doi:10.1016/j.ejor.2019.04.037

Cited by 27 publications

(15 citation statements)

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“…Un componente importante dentro de los hospitales es la actividad quirúrgica, se estima que esta genera alrededor de dos tercios de los ingresos y cerca del 40% de los costos en recursos, que incluyen costos de personal e instalaciones (Conforti et al, 2010). La programación de cirugías hace parte de una de las actividades que se abordan dentro de la logística hospitalaria; en esta actividad se deben definir la sincronización de tiempos de inicio y finalización de intervenciones entre los pacientes y recursos disponibles: cirujanos, enfermeras, anestesistas, salas quirúrgicas entre otros (Akbarzadeh et al, 2019). En los últimos años, se estima que la demanda de servicios quirúrgicos aumenta debido al creciente número de afiliaciones a los sistemas de salud y al incremento de la expectativa de vida lo cual genera una mayor necesidad de atención médica por cada década más de vida y triplica los costos del sistema (Velásquez-Restrepo et al, 2013).…”

Section: Introductionunclassified

“…Sin embargo, existe un número importante de trabajos realizados con métodos aproximados y simulación (Zhu et al, 2019). Las metodologías exactas más empleadas son: I) modelos de programación entera mixta (Saadouli et al, 2015) II) modelos de programación multiobjetivo (Zhang et al, 2019), III) programación por restricciones (Younespour et al, 2019;Gür et al, 2019), IV) optimización estocástica (Bovim et al, 2020), V) generación de columnas (Akbarzadeh et al, 2019) y VI) Branch and bound (Ribeiro, Leoneti, y Costa, 2018).La presente investigación propone un modelo matemático basado en programación por compromisos como estrategia de solución al problema de programación de cirugías electivas. Esta técnica ha sido ampliamente aplicada en la bibliografía en distintos problemas y sectores en los casos donde se quieren atender al mismo tiempo diferentes objetivos.…”

Section: Introductionunclassified

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Programación multiobjetivo de quirófanos considerando el bienestar del cliente interno y externo

et al. 2022

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Este estudio tiene como propósito presentar un modelo multiobjetivo para el problema de programación de quirófanos, que sincroniza las necesidades de los clientes externos con los recursos disponibles y al mismo tiempo los requerimientos de los clientes internos. Se emplea la programación por compromisos buscando la eficiencia de los siguientes objetivos: (1) maximización de la preferencia total, (2) minimización de los tiempos ociosos y (3) maximización del número de clientes. La función de preferencia propuesta considera para cada cirugía, la prioridad dada por el médico, su duración y fecha máxima de asignación, logrando atender la urgencia de la cirugía y disminuir el tiempo de espera. El modelo se valida con un caso real en Colombia, y los resultados demuestran un desempeño por encima del 89.9% de cercanía al óptimo ideal en cada uno de los objetivos propuestos. Se concluye que el uso de herramientas multiobjetivo para problemas de programación de cirugías produce buenos resultados en todas las medidas de desempeño consideradas.

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Section: Introductionunclassified

Programación multiobjetivo de quirófanos considerando el bienestar del cliente interno y externo

et al. 2022

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“…• Simulation models in the healthcare context (discrete event simulation, system dynamics and agent-based simulation), i.e. Rashwan et al (2015), Mathews and Long (2015), Lane et al (2000), Djanatliev and Meier (2016), Oh et al (2016), Hussein et al (2017), Babashov et al (2017, Liu (2011), Demir et al (2018, Gul et al (2019) and Cudney et al (2019). • Forecasting hospital demand (A&E, outpatient and inpatient specialties), i.e.…”

Section: Introduction and Related Workmentioning

confidence: 99%

“…Garg et al (2018), Kumar et al (2018), Gupta et al (2019a), Chhabra et al (2020), Bansal et al (2021a), Kumar et al (2021), Gupta et al (2021) and Bansal et al (2021b). In terms of resource planning in healthcare, a wide range of tools and techniques have been proposed including agent-based simulation (Cabrera et al 2012), discrete event simulation (Izady and Worthington 2012;Rossetti et al 1999;Ahmed and Alkhamis 2009), queuing theory (Belciug and Gorunescu 2015;Hou et al 2019), operating room scheduling (Adan et al 2009;Akbarzadeh et al 2019;Vandenberghe et al 2019) and ambulance deployment (Bertsimas and Ng 2019;Talarico et al 2015;Majzoubi et al 2012) among others. Centeno et al (2003) integrated simulation and integer linear programming to find the optimal staffing requirements and schedules for staff over a planning period.…”

Section: Introduction and Related Workmentioning

confidence: 99%

A hybrid analytical model for an entire hospital resource optimisation

2021

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Given the escalating healthcare costs around the world (more than 10% of the world's GDP) and increasing demand hospitals are under constant scrutiny in terms of managing services with limited resources and tighter budgets. Hospitals endeavour to find sustainable solutions for a variety of challenges ranging from productivity enhancements to resource allocation. For instance, in the UK, evidence suggests that hospitals are struggling due to increased delayed transfers of care, bed-occupancy rates well above the recommended levels of 85% and unmet A&E performance targets. In this paper, we present a hybrid forecasting-simulation-optimisation model for an NHS Foundation Trust in the UK. Using the Hospital Episode Statistics dataset for A&E, outpatient and inpatient services, we estimate the future patient demands for each speciality and model how it behaves with the forecasted activity in the future. Discrete event simulation is used to capture the entire hospital within a simulation environment, where the outputs is used as inputs into a multi-period integer linear programming (MILP) model to predict three vital resource requirements (on a monthly basis over a 1-year period), namely beds, physicians and nurses. We further carry out a sensitivity analysis to establish the robustness of solutions to changes in parameters, such as nurse-to-bed ratio. This type of modelling framework is developed for the first time to better plan the needs of hospitals now and into the future.

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“…Akbarzadeh et al studied the surgical case in which, operation room planners want to make a balance between the capacity and demand. They developed a three-phase column generation-based heuristic to generate a feasible solution and it improved by local branching [26]. Nasiri et al proposed a mathematical model to select and assign elective surgeries on a particular day.…”

Section: Introductionmentioning

confidence: 99%

Robust Bi-Objective Operating Rooms Scheduling Problem Regarding the Shared Resources

et al. 2021

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In recent years, many efforts have been made to provide different strategies for enhancing the scheduling and planning of the operating rooms. The efficient planning and scheduling of ORs is a complex task since it has to account for the availability of human resources, medical equipment, and medication required for each surgery but that are often shared between different ORs. This paper proposes a mathematical approach to enhance the management of OR resources. It presents a bi-objective robust optimization approach for scheduling the surgeries in the ORs and recovery room, regarding the uncertainty of the surgery time, uncertainty of hospitalization time in the recovery room, and shared resources. The first objective function aims to minimize the maximum completion time of the surgeries and the second one minimizes the sum of the earliness-tardiness of the surgical operations. The suggested approach utilizes the multi-choice goal programming approach with utility function to solve the proposed model. The proposed approach is applied to a real case in the Shahid Beheshti hospital, Babol, Iran. The obtained results show that the suggested biobjective robust optimization approach can enhance OR scheduling and should be designed into a decision support system for OR management.

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The re-planning and scheduling of surgical cases in the operating room department after block release time with resource rescheduling

Cited by 27 publications

References 36 publications

Programación multiobjetivo de quirófanos considerando el bienestar del cliente interno y externo

Programación multiobjetivo de quirófanos considerando el bienestar del cliente interno y externo

A hybrid analytical model for an entire hospital resource optimisation

Robust Bi-Objective Operating Rooms Scheduling Problem Regarding the Shared Resources

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