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

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

Operating theatre scheduling with patient recovery in both operating rooms and recovery beds

International audienceThis paper investigates the impact of allowing patient recovery in the operating room when no recovery bed is available. Three types of identical resources are considered: transporters, operating rooms and recovery beds. A fixed number of patients must be planned over a term horizon, usually one or two weeks. The surgery process is modelled as follows: each patient is transported from the ward to the operating theatre. Then the patient visits an operating room for surgery operation and is transferred to the recovery room. If no recovery bed is available, the patient wakes up in the operating room until a bed becomes available. The operating room needs to be cleaned after the patient's departure, before starting another operation. Finally, the patient is transported back to the ward after his recovery. We consider several criteria based on patients' completion times. We propose a Lagrangian relaxation-based method to solve this operating theatre scheduling problem. The efficiency of this method is then validated by numerical experiments. A comprehensive numerical experiment is then performed to quantify the benefit of allowing patient recovery in operating rooms. We show that the benefit is high when the workload of the recovery beds is high

Operating Room Scheduling in Teaching Hospitals

Operating room scheduling is an important operational problem in most hospitals. In this paper, a novel mixed integer programming (MIP) model is presented for minimizing Cmax and operating room idle times in hospitals. Using this model, we can determine the allocation of resources including operating rooms, surgeons, and assistant surgeons to surgeries, moreover the sequence of surgeries within operating rooms and the start time of them. The main features of the model will include the chronologic curriculum plan for training residents and the real-life constraints to be observed in teaching hospitals. The proposed model is evaluated against some real-life problems, by comparing the schedule obtained from the model and the one currently developed by the hospital staff. Numerical results indicate the efficiency of the proposed model compared to the real-life hospital scheduling, and the gap evaluations for the instances show that the results are generally satisfactory

Stochastic surgery selection and sequencing under dynamic emergency break-ins

Anticipating the impact of urgent emergency arrivals on operating room schedules remains methodologically and computationally challenging. This paper investigates a model for surgery scheduling, in which both surgery durations and emergency patient arrivals are stochastic. When an emergency patient arrives he enters the first available room. Given the sets of surgeries available to each operating room for that day, as well as the distributions of the main stochastic variables, we aim to find the per-room surgery sequences that minimise a joint objective, which includes over- and under-utilisation, the amount of cancelled patients, as well as the risk that emergencies suffer an excessively long waiting time. We show that a detailed analysis of emergency break-ins and their disruption of the schedule leads to a lower total cost compared to less sophisticated models. We also map the trade-off between the threshold for excessive waiting time, and the set of other objectives. Finally, an efficient heuristic is proposed to accurately estimate the value of a solution with significantly less computational effort.Anticipating the impact of urgent emergency arrivals on operating room schedules remains methodologically and computationally challenging. This paper investigates a model for surgery scheduling, in which both surgery durations and emergency patient arrivals are stochastic. When an emergency patient arrives he enters the first available room. Given the sets of surgeries available to each operating room for that day, as well as the distributions of the main stochastic variables, we aim to find the per-room surgery sequences that minimise a joint objective, which includes over- and under-utilisation, the amount of cancelled patients, as well as the risk that emergencies suffer an excessively long waiting time. We show that a detailed analysis of emergency break-ins and their disruption of the schedule leads to a lower total cost compared to less sophisticated models. We also map the trade-off between the threshold for excessive waiting time, and the set of other objectives. Finally, an efficient heuristic is proposed to accurately estimate the value of a solution with significantly less computational effort.A

Developing a multi-methodological approach to hospital operating theatre scheduling

Operating theatres and surgeons are among the most expensive resources in any hospital, so it is vital that they are used efficiently. Due to the complexity of the challenges involved in theatre scheduling we split the problem into levels and address the tactical and day-to-day scheduling problems.Cognitive mapping is used to identify the important factors to consider in theatre scheduling and their interactions. This allows development and testing of our understanding with hospital staff, ensuring that the aspects of theatre scheduling they consider important are included in the quantitative modelling.At the tactical level, our model assists hospitals in creating new theatre timetables, which take account of reducing the maximum number of beds required, surgeons’ preferences, surgeons’ availability, variations in types of theatre and their suitability for different types of surgery, limited equipment availability and varying the length of the cycle over which the timetable is repeated. The weightings given to each of these factors can be varied allowing exploration of possible timetables.At the day-to-day scheduling level we focus on the advanced booking of individual patients for surgery. Using simulation a range of algorithms for booking patients are explored, with the algorithms derived from a mixture of scheduling literature and ideas from hospital staff. The most significant result is that more efficient schedules can be achieved by delaying scheduling as close to the time of surgery as possible, however, this must be balanced with the need to give patients adequate warning to make arrangements to attend hospital for their surgery.The different stages of this project present different challenges and constraints, therefore requiring different methodologies. As a whole this thesis demonstrates that a range of methodologies can be applied to different stages of a problem to develop better solutions

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;