Operating room planning and scheduling: A literature review.

This paper provides a review of recent research on operating room planning and scheduling. We evaluate the literature on multiple fields that are related to either the problem setting (e.g. performance measures or patient classes) or the technical features (e.g. solution technique or uncertainty incorporation). Since papers are pooled and evaluated in various ways, a diversified and detailed overview is obtained that facilitates the identification of manuscripts related to the reader's specific interests. Throughout the literature review, we summarize the significant trends in research on operating room planning and scheduling and we identify areas that need to be addressed in the future.Health care; Operating room; Scheduling; Planning; Literature review;

Maximising patient throughput using discrete-event simulation

As the National Health Service (NHS) of England continues to face tighter cost saving and utilisation government set targets, finding the optimum between costs, patient waiting times, utilisation of resources, and user satisfaction is increasingly challenging. Patient scheduling is a subject which has been extensively covered in the literature, with many previous studies offering solutions to optimise the patient schedule for a given metric. However, few analyse a large range of metrics pertinent to the NHS. The tool presented in this paper provides a discrete-event simulation tool for analysing a range of patient schedules across nine metrics, including: patient waiting, clinic room utilisation, waiting room utilisation, staff hub utilisation, clinician utilisation, patient facing time, clinic over-run, post-clinic waiting, and post-clinic patients still being examined. This allows clinic managers to analyse a number of scheduling solutions to find the optimum schedule for their department by comparing the metrics and selecting their preferred schedule. Also provided is an analysis of the impact of variations in appointment durations and their impact on how a simulation tool provides results. This analysis highlights the need for multiple simulation runs to reduce the impact of non-representative results from the final schedule analysis

Maximising patient throughput using discrete-event simulation

As the National Health Service (NHS) of England continues to face tighter cost saving and utilisation government set targets, finding the optimum between costs, patient waiting times, utilisation of resources, and user satisfaction is increasingly challenging. Patient scheduling is a subject which has been extensively covered in the literature, with many previous studies offering solutions to optimise the patient schedule for a given metric. However, few analyse a large range of metrics pertinent to the NHS. The tool presented in this paper provides a discrete-event simulation tool for analysing a range of patient schedules across nine metrics, including: patient waiting, clinic room utilisation, waiting room utilisation, staff hub utilisation, clinician utilisation, patient facing time, clinic over-run, post-clinic waiting, and post-clinic patients still being examined. This allows clinic managers to analyse a number of scheduling solutions to find the optimum schedule for their department by comparing the metrics and selecting their preferred schedule. Also provided is an analysis of the impact of variations in appointment durations and their impact on how a simulation tool provides results. This analysis highlights the need for multiple simulation runs to reduce the impact of non-representative results from the final schedule analysis

Alimentación de un modelo de simulación mediante una conexión entre un sistema de información, R y SDLPS

Redacción del paper: alimentación de un modelo de simulación mediante una conexión entre un sistema de información, R y SDLPSEste trabajo desarrolla una metodología para alimentar de forma más automatizada un modelo de simulación. Para ello se generó un código de programación hecho con el lenguaje R que: 1) se conecta con base de datos; 2) valida los datos y 3) alimenta un modelo de simulación descrito en SDL e implementado en el software de simulación SDLPS, el cual lee la información generada en R. Este desarrollo se aplicó a un proceso de un hospital chileno. Los principales beneficios son: Es aplicable a distintas áreas y procesos; aumenta la oportunidad de la verificación y validación operacional del modelo; facilita el monitoreo del sistema en periodos más cortos y permite la experimentación más temprana de distintos escenarios para evaluar y planificar soluciones ante eventuales problemas.Preprin

Análise de uma unidade de processamento de roupas de um hospital através da simulação a eventos discretos

Com o passar do tempo a simulação a eventos discretos tem sido utilizada de forma crescente para auxílio à tomada de decisões. Esta já é apontada como uma das técnicas de pesquisa mais utilizadas, devido principalmente à sua versatilidade, flexibilidade e poder de análise. No setor de serviços, embora sua aplicação ainda não seja tão difusa quanto nos ambientes de manufatura, isso não tem sido diferente. Este artigo tem como objetivo desenvolver um projeto de simulação em uma unidade de processamento de roupas de um hospital do interior de São Paulo, como ferramenta de apoio a tomada de decisão gerencial. A simulação permitiu apresentar à direção do hospital a capacidade da unidade de processamentos de roupas, bem como apontar pontos críticos e gargalos do processo. Os resultados alcançados contribuíram para identificar oportunidades de melhoria no sistema, bem como contribuir para com a literatura para uma maior discussão sobre o assunto

Scheduling Elective Surgeries in Multiple Operating Rooms

This thesis focuses on the problem of designing appointment schedules in a surgery center with multiple operating rooms. The conditions under which overlapping surgeries in the surgeons’ schedule (i.e. parallel surgery processing) at the lowest cost are investigated with respect to three components of the total cost: waiting time, idle time, and overtime. A simulation optimization method is developed to find the near-optimal appointment schedules for elective surgical procedures in the presence of uncertain surgery durations. The analysis is performed in three steps. First, three near-optimal operating room schedules are found for different cost configurations based on the secondary data of surgery durations obtained from the Canadian Institute for Health Information. Second, these near-optimal appointment schedules are used to test a parallel scheduling policy where each surgeon has overlapping surgeries scheduled in two operating rooms for the entire session (480 minutes) and only attends the critical portions of surgeries in the two operating rooms. Lastly, another parallel scheduling policy is tested where each surgeon has overlapping surgeries scheduled for half of the session duration (240 minutes) and only has surgeries scheduled in one operating room for the remaining time. These two policies are tested using simulation with scenarios for parallelizable portions of surgeries varying from 0.1 to 0.9 at 0.1 increments and three cost configurations. In the simulated scenarios, the total cost is calculated as the weighted sum of patient waiting time, surgeon idle time, surgeon overtime, operating room idle time, and operating room overtime. Out of the nine scenarios for each policy and each cost configuration, the parallelizable portion of surgeries that result in the lowest total cost is identified. The results from both policies indicate that implementing parallel scheduling policies for surgery types with higher parallelizable portions results in surgeons remaining idle for longer periods during the session. This idle time cost is justified by a decrease in other cost components for surgeries with parallelizable portions 50% or less; however, the total cost is higher for surgeries with parallelizable portions over 50%. In addition, it has been observed that overlapping surgeries with lower parallelizable portions is more expensive than overlapping those over with 50%. Therefore, it is concluded that the surgery types that allow parallel surgery scheduling policies to be implemented at the lowest cost have 50% of their duration parallelizable

Modelación de una unidad de anestesia y pabellones quirúrgicos en un hospital chileno usando un lenguaje de especificación y descripción

En este trabajo se aborda el problema de llevar a cabo una modelización formal de los procesos relacionados con la Unidad de Anestesia y Pabellones Quirúrgicos en un hospital chileno. Para realizar este modelo utilizamos el Lenguaje de Especificación y Descripción (SDL). Como resultado se obtuvo un diseño gráfico que consiste en un sistema con 10 bloques, 50 procesos, 102 canales de comunicación y 126 señales de información. También incluye el entorno del sistema que corresponde a las unidades de emergencia, servicios clínicos y unidades de apoyo. El modelo tuvo bastante éxito para documentar y comprender el conocimiento de los procesos que se desarrollan en la unidad. La metodología propuesta permite diseñar un modelo que analiza el sistema de forma modular y estándar. También ayuda en la gestión hospitalaria y facilita la simulación. . Los hospitales públicos son sistemas complejos, con recursos limitados y alta demanda. En ellos, la unidad de Anestesia y Pabellones Quirúrgicos cumple un rol fundamental en la cadena de servicios prestados, tanto por los recursos como por los costos asociados. El objetivo del presente trabajo es describir el sistema de pabellón y cuantificar su demanda y oferta, mediante técnicas de modelación, teoría de colas y/o simulación. En particular se trabajará con la unidad de Anestesia y Pabellones Quirúrgicos del hospital Dr. Gustavo Fricke, de Viña del Mar, Chile

Implications of Non-Operating Room Anesthesia Policy for Operating Room Efficiency

This thesis focuses on examining the use of Non-Operating Room Anesthesia (NORA) policy in Operating Room (OR) scheduling. A NORA policy involves a practice whereby the administration of anesthesia stage is performed outside the OR. The goal of the thesis is to determine whether NORA policy can improve OR efficiency measured by the performance of total costs, which consists of a weighted sum of patient waiting time, OR overtime and idle time. A simulation optimization method is adopted to find near-optimal schedules for elective surgeries in an outpatient setting. The results of a traditional OR scheduling model, where all stages of the surgery are performed in the OR, will be compared to the results of a NORA OR model where the initial anesthesia stage is performed outside of the OR. Two cases are considered for the NORA model given the decrease on mean durations: (1) a model with the same number of surgery appointments and shorter session length and (2) a models with the same session length and more surgery appointments. . The impact of a NORA policy on OR performance is further analyzed by considering scenarios that capture Surgery duration variability and mean surgery durations which are two traits for surgeries that have been shown to impact OR performance. This thesis aims to investigate how a NORA policy performs when standard deviations and mean surgery durations change. The results show that NORA policy can improve OR efficiency in all settings

Optimising hospital designs and processes to improve efficiency and enhance the user experience

The health sector is facing increasing pressure to provide effective, efficient, and affordable care to the population it serves. The National Health Service (NHS) of the United Kingdom (UK) has regularly faced scrutiny with NHS England being issued a number of challenges in recent years to improve operational efficiency, reduce wasted space, and cut expenditure. The most recent challenge issued to NHS England has seen a requirement to save £5bn per annum by 2020, while reducing wasted space from 4.4% to 2.5% across the NHS estate. Similarly, satisfaction in the health service is also under scrutiny as staff retention and patient experiences are used in determining the performance of facilities. [Continues.

Performance analysis and scheduling strategies for ambulatory surgical facilities

Ambulatory surgery is a procedure that does not require an overnight hospital stay and is cost effective and efficient. The goal of this research is to develop an ASF operational model which allows management to make key decisions. This research develops and utilizes the simulation software ARENA based model to accommodate: (a) Time related uncertainties – Three system uncertainties characterize the problem (ii) Surgery time variance (ii) Physician arrival delay and (iii) Patient arrival delay; (b) Resource Capture Complexities – Patient flows vary significantly and capture/utilize both staffing and/or physical resources at different points and varying levels; and (c) Processing Time Differences – Patient care activities and surgical operation times vary by type and have a high level of variance between patient acuity within the same surgery type. A multi-dimensional ASF non-clinical performance objective is formulated and includes: (i) Fixed Labor Costs – regular time staffing costs for two nurse groups and medical/tech assistants, (i i) Overtime Labor Costs – staffing costs beyond the regular schedule, (i i i) Patient Delay Penalty – Imputed costs of waiting time experienced patients, and (iv) Physician Delay Penalty – Imputed costs of physicians having to delay surgical procedures due to ASF causes (limited staffing, patient delays, blocked OR, etc.). Three ASF decision problems are studied: (i) Optimize Staffing Resources Levels - Variations in staffing levels though are inversely related to patient waiting times and physician delays. The decision variable is the number of staff for three resource groups, for a given physician assignment and surgery profile. The results show that the decision space is convex, but decision robustness varies by problem type. For the problems studied the optimal levels provided 9% to 28% improvements relative to the baseline staffing level. The convergence rate is highest for less than optimal levels of Nurse-A. The problem is thus amenable to a gradient based search. (ii) Physician Block Assignment - The decision variables are the block assignments and the patient arrivals by type in each block. Five block assignment heuristics are developed and evaluated. Heuristic #4 which utilizes robust activity estimates (75% likelihood) and generates an asymmetrical resource utilization schedule, is found to be statistically better or equivalent to all other heuristics for 9 out of the 10 problems and (iii) Patient Arrival Schedule – Three decision variables in the patient arrival control (a) Arrival time of first patient in a block (b) The distribution and sequence of patients for each surgery type within the assigned windows and (c) The inter arrival time between patients, which could be constant or varying. Seven scheduling heuristics were developed and tested. Two heuristics one based on Palmers Rule and the other based on the SPT (Shortest Processing Time) Rule gave very strong results