Reduce fluctuations in capacity to improve the accessibility of radiotherapy treatment cost-effectively

This paper is motivated by a case study to reduce the throughput times for radiotherapy treatment. The goal is to find a cost-effective way to meet future throughput targets. A combination of queuing theory and computer simulation was used. First, computer simulation to detect the bottleneck(s) in a multi-step radiotherapy process. Despite, the investment in an additional linear accelerator, the main bottleneck turned out to be the outpatient department (OPD). Next, based on queuing theory, waiting times were improved by reducing the fluctuations in the OPD capacity. Computer simulation was used again to quantify the effect on the total throughput time of a radiotherapy patient. The results showed a reduction in both access times as well as waiting times prior to the consecutive steps: the preparation phase and actual treatment. The paper concludes with practical suggestions on how to reduce the fluctuations in capacity, and seems of interest for other radiotherapy departments or other multi-step situations in a hospital

To pool or not to pool in hospitals: a theoretical and practical comparison for a radiotherapy outpatient department

This paper examines whether urgent and regular patients waiting for a consultation at a radiotherapy outpatient department should be pooled or not. Both queuing theory and discrete event simulation were applied to a realistic case study. The theoretical approach shows that pooling is not always beneficial with regard to the waiting times of urgent patients. Furthermore, the practical approach indicates that the separation of queues may require less capacity to meet the waiting time performance target for urgent as well as regular patients. The results seem to be of general interest for hospital

A survey of health care models that encompass multiple departments

In this survey we review quantitative health care models to illustrate the extent to which they encompass multiple hospital departments. The paper provides general overviews of the relationships that exists between major hospital departments and describes how these relationships are accounted for by researchers. We find the atomistic view of hospitals often taken by researchers is partially due to the ambiguity of patient care trajectories. To this end clinical pathways literature is reviewed to illustrate its potential for clarifying patient flows and for providing a holistic hospital perspective

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

Organizing Multidisciplinary Care for Children with Neuromuscular Diseases

The Academic Medical Center (AMC) in Amsterdam, The Netherlands, recently opened the `Children's Muscle Center Amsterdam' (CMCA). The CMCA diagnoses and treats children with neuromuscular diseases. These patients require care from a variety of clinicians. Through the establishment of the CMCA, children and their parents will generally visit the hospital only once a year, while previously they visited on average six times a year. This is a major improvement, because the hospital visits are both physically and psychologically demanding for the patients. This article describes how quantitative modelling supports the design and operations of the CMCA. First, an integer linear program is presented that selects which patients to invite for a treatment day and schedules the required combination of consultations, examinations and treatments on one day. Second, the integer linear program is used as input to a simulation to study to estimate the capacity of the CMCA, expressed in the distribution of the number patients that can be seen on one diagnosis day. Finally, a queueing model is formulated to predict the access time distributions based upon the simulation outcomes under various demand scenarios

Discrete Event Simulation Models for CT Examination Queuing in West China Hospital

In CT examination, the emergency patients (EPs) have highest priorities in the queuing system and thus the general patients (GPs) have to wait for a long time. This leads to a low degree of satisfaction of the whole patients. The aim of this study is to improve the patients’ satisfaction by designing new queuing strategies for CT examination. We divide the EPs into urgent type and emergency type and then design two queuing strategies: one is that the urgent patients (UPs) wedge into the GPs’ queue with fixed interval (fixed priority model) and the other is that the patients have dynamic priorities for queuing (dynamic priority model). Based on the data from Radiology Information Database (RID) of West China Hospital (WCH), we develop some discrete event simulation models for CT examination according to the designed strategies. We compare the performance of different strategies on the basis of the simulation results. The strategy that patients have dynamic priorities for queuing makes the waiting time of GPs decrease by 13 minutes and the degree of satisfaction increase by 40.6%. We design a more reasonable CT examination queuing strategy to decrease patients’ waiting time and increase their satisfaction degrees