Maximising the patient flows throughout the emergency care patient pathway is one of the most important objectives in the healthcare system. The emergency department (ED) is the critical point of this pathway in most hospitals, as the potential delays reduce the number of patients seen in the recommended time. One of the key delays in the ED is the waiting time of a patient prior to treatment, which can be reduced by optimising the patient treatment schedules with priorities. In this paper, a novel blocking patient flow (BPF) algorithm is developed and tested using the real data from a hospital in Brisbane, Australia. Initially, a simulation model of real-life ED operations is developed by characterising patient interarrival and treatment times according to different disease categories. Subsequently, a BPF heuristic algorithm is designed and benchmarked via computational experiments using two dominance rules: first come first served (FCFS) and shortest processing time (SPT). The computational results show that the proposed approach leads to a reduction of the total waiting time by more than 8 % in comparison to the current hospital practice, which implies that more patients will be served in a specified time window.

This study tends to investigate and assess the average waiting time (WT) in Dubai primary healthcare services centers. Healthcare centers will face critical problems if WT is not solved properly. Accordingly, this study tries to dig a deep insight on such problem and provides proper suggestions to reduce WT. An Electronic Medical Record audit is used to count the patients’ WT during a four-week period in health care service centers employing a universal sampling approach. All patients who visit the health medical centers during such period are considered for the study purpose except those need emergency services. A self-administered questionnaire is used to collect the needed records about WT longevity causes from direct em-ployees who use to interact patients in a continuous basis. The questionnaires are distributed in 12 healthcare centers throughout Emirate of Dubai in UAE. A total of 76,780 electronic medical records are audited for patients and 938 responses are analyzed for the employee survey. The study finds that about 45.2% of the patients were registered within less than 7 minutes of their visit and the mean WT was 11.7 minutes of entrance. While more than two third of them (75.3%) waited less than 30 minutes and the average consultation WT was 34.2 minutes. 65.9% of patients waited less than 28 days to get their appointment and the average appointment WT was 35 days. The data collected from employees denoted that the main causes of patients’ WT were high workload level, insufficient work procedure, employees-supervisor interaction problems and adequate facilities availability. There is a need for healthcare leaders and managers in charges in this sector to reduce patients’ complaints while waiting and to solve the WT problem in a planned manner.

Poor urban planning and traffic congestion lead to excessive delays in workers’ transit times and decrease their quality of life, especially in emerging countries. Several medium and large companies have a need to hire a transport service for their staff. In this type of transportation system, there is a heterogeneous fleet of vehicles, which are assigned to a set of predefined routes. However, the total transport delay can be even greater if the private transportation system is inefficient or not controlled. The approach proposed in this study seeks to optimize the private transport service by defining the best allocation of its fleet to its routes. A mathematical model is proposed to minimize user wait times. This approach is validated using real data obtained from a transport company in Co-lombia. The results demonstrate the quantitative benefits that can be achieved when the proposed approach is implemented, represented by a considerable reduction in user wait times.