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

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

Optimizing a multiple objective surgical case scheduling problem.

The scheduling of the operating theater on a daily base is a complicated task and is mainly based on the experience of the human planner. This, however, does not mean that this task can be seen as unimportant since the schedule of individual surgeries influences a medical department as a whole. Based on practical suggestions of the planner and on real-life constraints, we will formulate a multiple objective optimization model in order to facilitate this decision process. We will show that this optimization problem is NP-hard and hence hard to solve. Both exact and heuristic algorithms, based on integer programming and on implicit enumeration (branch-and-bound), will be introduced. These solution approaches will be thoroughly tested on a realistic test set using data of the surgical day-care center at the university hospital Gasthuisberg in Leuven (Belgium). Finally, results will be analyzed and conclusions will be formulated.Algorithms; Belgium; Branch-and-bound; Constraint; Data; Decision; Experience; Healthcare; Heuristic; Integer; Integer programming; Model; Optimization; Order; Processes; Real life; Scheduling; University;

Scheduling surgical cases in a day-care environment: a branch-and-price approach.

In this paper we will investigate how to sequence surgical cases in a day-care facility so that multiple objectives are simultaneously optimized. The limited availability of resources and the occurrence of medical precautions, such as an additional cleaning of the operating room after the surgery of an infected patient, are taken into account. A branch-and-price methodology will be introduced in order to develop both exact and heuristic algorithms. In this methodology, column generation is used to optimize the linear programming formulation of the scheduling problem. Both a dynamic programming approach and an integer programming approach will be specified in order to solve the pricing problem. The column generation procedure will be combined with various branching schemes in order to guarantee the integrality of the solutions. The resulting solution procedures will be thoroughly tested and evaluated using real-life data of the surgical day-care center at the university hospital Gasthuisberg in Leuven (Belgium). Computational results will be summarized and conclusions will eventually be formulated.Branch-and-price; Column generation; Health care operations; Scheduling;

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;

What is the best practice in domestic inquiry?

Before we go through what is the best practice of domestic inquiry in Malaysia, we have to get ourselves more familiar with the meaning of best practice and domestic inquiry. A best practice is a type of method or strategy universally accepted as preferable to any alternative since it produces results superior for those attained through other means or because it is becoming a typical way of acting. Such as a standard way of implementing and practice domestic inquiry in the work environment. Best practices are an easy solution to obligatory federal norms to retain quality and based on personal-assessment or performance analysis. Some counselling firms spend significant time in the region of best practice and offer pre-made formats to institutionalize business process documentation. Now and again, a best practice is not pertinent or is improper for a specific association’s needs. This assignment will define what particle was required to enhance and maintain the best practice of domestic inquiry to protect the rights at work

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

A multilevel integrative approach to hospital case mix and capacity planning.

Hospital case mix and capacity planning involves the decision making both on patient volumes that can be taken care of at a hospital and on resource requirements and capacity management. In this research, to advance both the hospital resource efficiency and the health care service level, a multilevel integrative approach to the planning problem is proposed on the basis of mathematical programming modeling and simulation analysis. It consists of three stages, namely the case mix planning phase, the master surgery scheduling phase and the operational performance evaluation phase. At the case mix planning phase, a hospital is assumed to choose the optimal patient mix and volume that can bring the maximum overall financial contribution under the given resource capacity. Then, in order to improve the patient service level potentially, the total expected bed shortage due to the variable length of stay of patients is minimized through reallocating the bed capacity and building balanced master surgery schedules at the master surgery scheduling phase. After that, the performance evaluation is carried out at the operational stage through simulation analysis, and a few effective operational policies are suggested and analyzed to enhance the trade-offs between resource efficiency and service level. The three stages are interacting and are combined in an iterative way to make sound decisions both on the patient case mix and on the resource allocation.Health care; Case mix and capacity planning; Master surgery schedule; Multilevel; Resource efficiency; Service level;