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;

Taxonomic classification of planning decisions in health care: a review of the state of the art in OR/MS

We provide a structured overview of the typical decisions to be made in resource capacity planning and control in health care, and a review of relevant OR/MS articles for each planning decision. The contribution of this paper is twofold. First, to position the planning decisions, a taxonomy is presented. This taxonomy provides health care managers and OR/MS researchers with a method to identify, break down and classify planning and control decisions. Second, following the taxonomy, for six health care services, we provide an exhaustive specification of planning and control decisions in resource capacity planning and control. For each planning and control decision, we structurally review the key OR/MS articles and the OR/MS methods and techniques that are applied in the literature to support decision making

Simulation analysis of capacity and scheduling methods in the hospital surgical suite

With health-care costs rising and an aging population, the health-care industry is progressively faced with the problem of growing demand and diminishing reimbursements. Hospital administration is often faced with a lack of quantifiable data regarding surgical suite capacity and the impact of adding new surgical procedures. With the inherent variation in surgery due to unique procedures and patients, accurately measuring maximum capacity in the surgical suite through mathematical models is difficult to do without making simplifying assumptions. Several hospitals calculate their operating room (OR) efficiencies by comparing total OR time available to total surgical time used. This metric fails to account for the required non-value added tasks between surgeries and the balance necessary for patients to arrive at the OR as soon as possible without compromising patient satisfaction. Since surgical suites are the financial engine for many hospitals and the decisions made with regard to the surgical suite can significantly impact a hospital’s success, this thesis develops a methodology through simulation to more accurately define current and potential capacity levels within the surgical suite. Additionally, scheduling policies, which schedule patients based on the variability of their surgical time as well as the implementation of flexible ORs capable of servicing multiple operation genres, are examined for individual and interaction effects with regard to surgical suite capacity, patient waiting times, and resource utilization. Through verification and validation, the model is shown to be an effective tool in representing patient flow and testing policies and procedures within the surgical suite. An application to the surgical suite at Chenango Memorial Hospital (Norwich, NY) illustrates the methodology and potential impacts of this research

Optimizing Perioperative Decision Making: Improved Information for Clinical Workflow Planning

Perioperative care is complex and involves multiple interconnected subsystems. Delayed starts, prolonged cases and overtime are common. Surgical procedures account for 40–70% of hospital revenues and 30–40% of total costs. Most planning and scheduling in healthcare is done without modern planning tools, which have potential for improving access by assisting in operations planning support. We identified key planning scenarios of interest to perioperative leaders, in order to examine the feasibility of applying combinatorial optimization software solving some of those planning issues in the operative setting. Perioperative leaders desire a broad range of tools for planning and assessing alternate solutions. Our modeled solutions generated feasible solutions that varied as expected, based on resource and policy assumptions and found better utilization of scarce resources. Combinatorial optimization modeling can effectively evaluate alternatives to support key decisions for planning clinical workflow and improving care efficiency and satisfaction

The Impact of Block Scheduling and Release Time on Operating Room Efficiency

Planning for sufficient surgical capacity at a hospital requires that many tactical and operational decisions be made before the day of surgery. Typically, blocks of time in operating rooms (ORs) are assigned and specific surgical cases are placed in rooms. The hospital monitors utilization to determine the schedule\u27s effectiveness in balancing the risk of overtime with idle time. In this thesis, we will examine how adjusting schedule risk ratios and penalty values, and providing shared, open posting time affected the hospital\u27s ability to identify an efficient but high quality and low cost block schedule. The proposed schedules were tested by assigning surgical cases to ORs and simulating the schedule\u27s performance using recent data from a local hospital. We also show how scheduling accuracy can impact the performance level of the schedules proposed. Once the schedule has been set, the use of block release time is investigated in order to provide insight on how to better fill these ORs and increase utilization levels. Release policies are simulated based on various surgery arrival distributions, capacity levels, and case durations. We will show how different policies involving assigned and open posting rooms impact utilization levels, number of cases not fit into the schedule, and number of cases posted after the block release time

Optimizing Cash Flows and Minimizing Simultaneous Turnovers in Operating Room Scheduling

Currently, the scheduling of surgical suites follows either an open booking or block booking framework. Under block booking, medical departments (or surgeons) that provide certain types of services (e.g. ophthalmology, orthopedics, cardiology) are assigned fixed blocks of time that are used to divide access to the operating rooms (ORs) among different specialties. Two integer-programming based methods of generating block schedules are investigated in this research. The first approach focuses on optimizing cash flows, an area not studied previously within the OR scheduling domain. Results indicate that while there is some utility of this approach in improving the liquidity of a healthcare facility, its contribution towards increasing overall revenues is marginal. The second approach aims to minimize simultaneous turnovers of operating rooms. Although reduction in turnover times is a frequently studied area in literature, the solution presented here is novel in its attempt to minimize the occurrences of turnovers in two or more rooms at the same time, which places a strain on shared resources and leads to delays in planned start times of procedures. Results for this approach are promising in reduction of turnover times and consequently, workload on resources required to perform turnovers. Both approaches begin with the study of existing schedules to derive key insights into the chosen target parameters and then propose alternative schedules to optimize the aforementioned objectives. The proposed methods are designed to be minimally disruptive so as to remain feasible in real life scenarios

Managing Elective and Non-elective Case Assignments for an Operating Room Suite

The success of operating room management depends on all levels of decision making, from strategic to tactical and operational decisions. One key decision in systems with block booking is to assign sufficient amount of block time to surgeons and surgery groups. While the typical method of block assignment identifies the share of surgery groups from OR times based on average of past usage, this method does not count for the difference between cost of under and overtime. One of the goals of this research is to develop a decision framework for block assignment. This work is presented in chapter two. In this part first, I provide with the linear program that finds the length of block assigned to surgery groups while considering the amount of past undertime and overtime. This model then simplifieded through valid assumptions. In addition, a case study is conducted to support the usefulness of the method. The results show that 12 months of past data is sufficient amount of data to use in this method. Also, this method of block allocation out performs the existing time series method in literature. Another key decision in an OR suite is to how manage elective and non-elective surgeries. The short and long term decisions regarding these two surgery types can change the waiting time of patients and the number of turned away surgeries. In order to accommodate elective and non-elective surgeries at lower cost to system and patients, both short and long term decisions play important roles. The long term decisions regarding the combination of rooms to choose in the system as well as the allocation to choose with the selected room combination are important decisions for OR managers. For short time decision making on the day of surgery a policy that indicate how to use share resources among the two surgery types is another important decision that OR managers need to nd an answer to. In this research I try to provide with methods and models that can guide managers in decision making process. In this research using Markov decision processes (MDP), I introduce a model that could be used to find the optimal policy for use of operating rooms that are considered as shared resources while minimizing the overall cost of the system including waiting, turn-away and overtime. For that I focus on the system with a dedicated OR to non-elective surgeries and a flexible (shared) OR. I also model this system using simulation with Arena, by relaxing the MDP assumptions of steady state and the arrival and surgery times to find a policy that can minimize the cost of system. The simulation better reflects the real system of hospitals however it takes a long time to find a policy using taking simulation approach. In addition to that, the policy from simulation does not guarantee optimality. Moreover, the result of case study shows that relaxing MDP assumptions, simulation model finds the same policy as MDP. However, the MDP model could find an optimal policy in seconds. Although MDP could be used to model the most common existing combinations of operating rooms, however, the optimal policy from MDP may be hard to implement. Therefore I use Markov chain to model combinations of operating rooms and define policies to be used on the day of surgery for accommodating elective and non-elective surgeries. I compare the performance of systems under defined policies by considering input parameters at different levels. I also consider several allocations under each system to find the best system and allocation. Results of this work shows that overall system with all flexible ORs has the minimum cost. However, some other systems may perform better in specific situations and scenarios. The best policy (among the studied policies) is depending on the room combinations and the chosen allocation