Waiting Time Analysis Research Articles

Data-Driven Identification and Analysis of Waiting Times in Business Processes

AbstractReducing waiting times in end-to-end business processes is a recurrent concern in the field of business process management. The uptake of data-driven approaches in this field in the past two decades, most notably process mining, has created new opportunities for fine-grained analysis of waiting times based on execution data. As a result, a wide range of approaches for waiting time identification and analysis on the basis of business process execution data have been reported in the literature. In many instances, different approaches have considered different notions of waiting time and different causes for waiting time. At present, there is a lack of a consolidated overview of these manifold approaches, and how they relate to or complement each other. The article presents a literature review that starts with the question of what approaches for identification and analysis of waiting time are available in the literature, and then refines this question by adding questions which shed light onto different causes and notions of waiting time. The survey leads to a multidimensional taxonomy of data-driven waiting time analysis techniques, in terms of purpose, causes, and measures. The survey identifies gaps in the field, chiefly a scarcity of integrated multi-causal approaches to analyze waiting times in business processes, and a lack of empirically validated approaches in the field.

Patient waiting time analysis in a multispecialty ophthalmic outpatient clinic using data analysis and discrete event simulation

Patient waiting time analysis in a multispecialty ophthalmic outpatient clinic using data analysis and discrete event simulation

Waiting Time Analysis for a Network of Signalized Intersections

Vehicle waiting time or stopped delay is one of the major disadvantages of employing signalized intersections (SIs) in road networks. The waiting time delays occur when vehicles stop in the queue, waiting to access the SI, and vary from road lane to road lane with the intersection management (IM) protocol used. In this research line, we propose an analytical expression for estimating the waiting time delays and studying the performance of different IM approaches in a grid network of independent intersections. We consider complex intersections with four legs and two lanes with two left-lane configurations, as well as five state-of-the-art IM approaches: two conventional – Round-Robin (RR) and Trivial Traffic Light Control (TTLC); two adaptive – Max-pressure Control Algorithm (MCA) and Websters Traffic Light Control (WTLC); and one reactive – Synchronous Intersection Management Protocol (SIMP). The waiting time performance of these five IM approaches is compared using two simulation scenarios in the SUMO simulation framework. The simulation results validate the analytical study and show the advantages of employing SIMP, being the IM approach with the lowest waiting time delays.

Patient waiting time analysis in a multi-specialty ophthalmic outpatient clinic using data analysis and discrete event simulation

Patient waiting time analysis in a multi-specialty ophthalmic outpatient clinic using data analysis and discrete event simulation

Trust-Based Beacon Node Localization Algorithm for Underwater Networks by Exploiting Nature Inspired Meta-Heuristic Strategies

Conventional underwater technologies were not able to provide authentication and proper visualization of unexplored ocean areas to accommodate a wide range of applications. The aforesaid technologies face several challenges including decentralization, beacon node localization (for identification of nodes), authentication of Internet of Underwater Things (IoUTs) objects and unreliable beacon node communication between purpose oriented IoT-enabled networks. Recently, new technologies such as blockchain (BC) and the IoUTs have been used to reduce the issues but there are still some research gaps; for example, unreliable beacon messages for node acquisition have significant impacts on node identification and localization and many constrained node resources, etc. Further, the uncertainty of acoustic communication and the environment itself become problems when designing a trust-based framework for the IoUTs. In this research, a trust-based hybrid BC-enabled beacon node localization (THBNL) framework is proposed to employ a secure strategy for beacon node localization (BNL) to mine the underwater localized nodes via the hybrid blockchain enabled beacon node localization (HB2NL) algorithm. This framework helps to merge two disciplines; it is hybrid because it follows the nature and bio inspired meta heuristics algorithms for scheduling the beacon nodes. The performance of the proposed approach is also evaluated for different factors such as node losses, packet delivery ratios, residual and energy consumption and waiting time analysis, etc. These findings show that the work done so far has been successful in achieving the required goals while remaining within the system parameters.

Asymptotic waiting time analysis of finite source $M/GI/1$ retrial queueing systems with conflicts and unreliable server

Asymptotic waiting time analysis of finite source $M/GI/1$ retrial queueing systems with conflicts and unreliable server

Patient waiting time analysis for elective gynecologic surgeries in a tertiary training hospital in the Philippines: A retrospective cross-sectional study

ObjectivesThis study aimed to determine the median waiting time and assess the factors affecting patient waiting time and scheduling for elective gynecologic surgery in a tertiary training hospital in the Philippines. MethodsA retrospective analysis of waiting times for elective gynecologic surgeries was performed. The different time intervals for each step of the process map were determined. Regression models were used to study the relationship between waiting time intervals and demographic data, consideration of malignancy, and surgeries performed. ResultsThe median waiting time from the date of the first consult to surgery was 154 days. Patients with consideration of malignancy and pelvic organ prolapse had significantly longer intervals from the Waitlist Clinic to actual surgery with regression coefficients of 6.76 and 17.53 days, respectively. Other intervals in the process map did not show significant differences. ConclusionsThe median waiting time for elective gynecologic surgeries in a tertiary training institution in the Philippines was longer than global standards. A significant amount of time was spent waiting for diagnostic studies and referral to the Waitlist Clinic. The study recommends regulating and improving systems processes at the hospital and national levels to decrease patient waiting time. Surgical waitlists, referral systems, and benchmarks for safe waiting times should be established.

Markovian Demands on Two Commodity Inventory System with Queue-Dependent Services and an Optional Retrial Facility

The use of a Markovian inventory system is a critical part of inventory management. The purpose of this study is to examine the demand for two commodities in a Markovian inventory system, one of which is designated as a major item (Commodity-I) and the other as a complimentary item (Commodity-II). Demand arrives according to a Poisson process, and service time is exponential at a queue-dependent rate. We investigate a strategy of (s,Q) type control for commodity-I with a random lead time but instantaneous replenishment for commodity-II. If the waiting hall reaches its maximum capacity of N, any arriving primary client may enter an infinite capacity orbit with a specified ratio. For orbiting consumers, the classical retrial policy is used. In a steady-state setting, the joint probability distributions for commodities and the number of demands in the queue and the orbit, are derived. From this, we derive a waiting time analysis and a variety of system performance metrics in the steady-state. Additionally, the physical properties of various performance measures are evaluated using various numerical assumptions associated with diverse stochastic behaviours.

Analysis of Interconnected Arrivals on Queueing-Inventory System with Two Multi-Server Service Channels and One Retrial Facility

Present-day queuing inventory systems (QIS) do not utilize two multi-server service channels. We proposed two multi-server service channels referred to as T1S (Type 1 n-identical multi-server) and T2S (Type 2 m-identical multi-server). It includes an optional interconnected service connection between T1S and T2S, which has a finite queue of size N. An arriving customer either uses the inventory (basic service or main service) for their demand, whom we call T1, or simply uses the service only, whom we call T2. Customer T1 will utilize the server T1S, while customer T2 will utilize the server T2S, and T1 can also get the second optional service after completing their main service. If there is a free server with a positive inventory, there is a chance that T1 customers may go to an infinite orbit whenever they find that either all the servers are busy or no sufficient stock. The orbital customer can request for T1S service under the classical retrial policy. Q(=S−s) items are replaced into the inventory whenever it falls into the reorder level s such that the inequality always holds n<s. We use the standard (s,Q) ordering policy to replace items into the inventory. By varying S and s, we investigate to find the optimal cost value using stationary probability vector ϕ. We used the Neuts Matrix geometric approach to derive the stability condition and steady-state analysis with R-matrix to find ϕ. Then, we perform the waiting time analysis for both T1 and T2 customers using Laplace transform technique. Further, we computed the necessary system characteristics and presented sufficient numerical results.

Waiting time analysis in a paediatric outpatient clinic in South East Nigeria

Objective: Waiting time is a resource investment by the patient for the desired goal of being attended to by the physician. It is the time taken or spent in waiting to be attended to by a physician in a health facility. It is important because waiting time is an essential determinant of patient satisfaction in health care practice, and its study would expose the bottleneck areas in patient’s time-flow so that the facility can improve services with that regard.
 Materials and Methods: A cross-sectional study of time spent by paediatric patients in the outpatient department of Alex Ekwueme Federal University Teaching Hospital Abakaliki by secretly following the patients from arrival at CHOP till after consultation. Means were calculated of time spent in various areas. 
 Results: Of the 384 patients observed, the mean (SD) total time spent in the hospital was 142.58 (23.17) minutes while waiting time and consultation time were 113.15(18.01) and 24.43 (10.38) minutes respectively. The mean time spent at the nurse’s bay was 23.79 (6.47) minutes, while that spent at the queue was 22.94 (8.98) minutes. The time spent at the records unit was the highest, with a mean time of 47.2 (17.42) minutes. 
 Conclusion: The long waiting time obtained from the current study is mostly attributable to delays from the records/registration unit, therefore conceited efforts aimed at improvement of service delivery in this unit will reduce patient waiting time and invariably patient satisfaction.

Patient waiting time Analysis at Service Points in the Ultrasound Unit of a Nigerian Teaching Hospital

Background: Quality of service, as perceived by patients in any healthcare facility is to a great extent, dependent on the waiting time. Reducing patients waiting time increases patients satisfaction and improves system efficiency.
 Purpose: To measure and analyze the waiting time of patients at the service points in the ultrasound unit of a Nigerian tertiary hospital and to determine the mean examination time for the different ultrasound investigations carried out.
 Methods: This prospective cross-sectional study was carried out in the ultrasound unit of the Radiology department at the University of Nigeria Teaching Hospital (UNTH) Ituku/Ozalla, Enugu. The waiting and examination times of patients were measured directly through observation of system operations. The waiting time at the various service points identified as costing, update, payment and examination were recorded. Mean, range and standard deviation of waiting and service times formed the descriptive statistics for the. For inferential statistics, ANOVA test was carried out to test for significance in the different service point waiting times, and the different examination times for the different investigations.
 Results: Mean waiting time was 3 hours 31 seconds and average exam time was 26 minutes 31 seconds. Analysis of variance on the service point where patients wait the most showed that the point after making the payment was the most significant. There was no significant difference found in the amount of time spent on different examinations (P< 0.05).
 Conclusion: Timely delivery of services is of optimum importance, considering the need for patient-centred service. With the information provided on the waiting time at the different service points in a typical teaching hospital ultrasound unit, departmental managers will be guided in the planning of the departmental operations, to enhance patient satisfaction and system efficiency.

The Waiting Time Analysis of Educated Workers in Sumbawa Regency

<p align="justify">The purpose of this study is to analyze the causes and dilemmas of educated workers in Sumbawa Regency to experience waiting times in looking for or finding work in accordance with the demand side hypothesis of wage levels, types of work, education levels. From the supply side namely gender (gender specific), majoring in education, and work experience. This study used a quantitative approach with the type of descriptive research. The population in this study was the educated workforce in Sumbawa Regency with the last education such as Senior high school , D-I / II / III, or S1 and 100 samples were taken. This research data used primary data from questionnaire results. The results of this study indicated that educated workers experience waiting time or unemployed due to the level of education that was not in accordance with the demands of existing jobs or not in accordance with the majors they completed. Educated workers were willing to accept any job if they did not get work for a certain time but still consider the level of wages, type of work, and level of education.</p>

Analytical and computational aspects of the infinite buffer single server N policy queue with batch renewal input

In this paper we provide a complete analysis of an infinite buffer batch arrival GIX/M/1 queue with N threshold policy. According to this policy, as soon as the system becomes empty, the server stops service and turns into an idle state. It again resumes service when the number of customers in the queue reaches N or more. Based on the supplementary variable and the difference equation method, we propose an algorithm to obtain the steady-state probability distribution of the system-size at pre-arrival and arbitrary epochs. We perform the waiting time analysis of the model and derive the mean waiting time of an arbitrary customer along with other performance measures. Finally, we validate our analytical results by some numerical examples and conduct certain numerical experiments to study the impact of parameters on the performance characteristics of the system. The work carried out in this paper provides a substantial methodological contribution in dealing with N policy queueing models, particularly with renewal arrival process.

Robot Waiting Time Analysis and Its Impact on Wafer Delay Time of Single-Arm Cluster Tools

Abstract With the circuit width of a wafer being decreased below 10 nanometers, it is important to reduce the wafer delay time in a process module as much as possible since too long wafer delay time has negative influence on the wafer quality. To do so, based on a Petri net model, we examine the characteristic of the robot wait time under the steady state by an earliest starting strategy. It is found that a unique steady state is reached by such a strategy, leading to inevitable wafer delays in the system. Then, a robot-waiting-time-controlled method is presented to reduce the wafer delays as much as possible by appropriately regulating the robot idle time. Finally, two industrial examples show that the robot-waiting-time-controlled method outperforms the earliest starting strategy in terms of the wafer delay reduction.

Patient waiting time Analysis at Service Points in the Ultrasound Unit of a Nigerian Teaching Hospital

Background: Quality of service, as perceived by patients in any healthcare facility is to a great extent, dependent on the waiting time. Reducing patients' waiting time increases patients' satisfaction and improves system efficiency. Purpose: To measure and analyze the waiting time of patients at the service points in the ultrasound unit of a Nigerian tertiary hospital and to determine the mean examination time for the different ultrasound investigations carried out. Methods: This prospective cross-sectional study was carried out in the ultrasound unit of the Radiology department at the University of Nigeria Teaching Hospital (UNTH) Ituku/Ozalla, Enugu. The waiting and examination times of patients were measured directly through observation of system operations. The waiting time at the various service points identified as costing, update, payment and examination were recorded. Mean, range and standard deviation of waiting and service times formed the descriptive statistics for the. For inferential statistics, ANOVA test was carried out to test for significance in the different service point waiting times, and the different examination times for the different investigations. Results: Mean waiting time was 3 hours 31 seconds and average exam time was 26 minutes 31 seconds. Analysis of variance on the service point where patients wait the most showed that the point after making the payment was the most significant. There was no significant difference found in the amount of time spent on different examinations (P < 0.05). Conclusion: Timely delivery of services is of optimum importance, considering the need for patient-centred service. With the information provided on the waiting time at the different service points in a typical teaching hospital ultrasound unit, departmental managers will be guided in the planning of the departmental operations, to enhance patient satisfaction and system efficiency.

Patient arrival pattern and waiting time analysis for a tertiary hospital radiology department

Background: High patient load and ineffective appointment scheduling has been linked to hospital overcrowding. This article investigated the appointment scheduling method, patient waiting times and overall treatment times. These figures were subsequently compared against patient arrival and examination times. Method: In total, 768 adult ambulant patients were part of a real-time observation that was conducted in a tertiary hospital's radiology department in Nigeria. The scheduling method, arrival time, treatment time and waiting time for each patient was noted. The analytical software, MATLAB, was used for data analysis. Results: A single block appointment time of 7.30 was given to all patients. For any given day, mean patient arrival per hour (arrival rate) was 7 ± 5.4 patients per hour. Patient arrival rate distribution showed a pattern that resulted in the identification of three segments with stable arrival rates: 7:00–10:00, 10:00-13:00 and 13:00-16:00 with arrival rates of 12, 6 and 2 patients per hour, respectively. The mean waiting time was 116.2 minutes.

Melting of CaSiO3 Perovskite at High Pressure.

Ab initio molecular dynamics simulations predict that CaSiO3 perovskite melts at 5600 K at 136 GPa, and 6400 K at 300 GPa, significantly higher than MgSiO3 perovskite. The entropy of melting (1.8 kB per atom) is much larger than that of many silicates at ambient pressure and of simple liquids and varies little with pressure. The volume of melting decreases rapidly with increasing pressure, to 3 % at 136 GPa, producing a melting slope that diminishes rapidly with pressure. We determine the melting temperature via the ZW method, combining the Z method, for which we clarify the theoretical basis, with a waiting time analysis. The ZW method results are internally confirmed by integrating the Clausius‐Clapeyron equation, which also yields our results for the entropy and volume of melting. We find the eutectic composition on the MgSiO3‐CaSiO3 join to be x Ca = 0.26 at 136 GPa and that metasilicate melt is denser than coexisting silicates.

P234] Waiting and treatment time analysis for radiation therapy treatments

Purpose To analyze the total treatment time and waiting time for the patients in our radiation oncology department. Method Patient treatment and waiting times were analyzed for a total of 3937 appointments during the last 3 years in three linear accelerators (Agility, Synergy and Infinity). With Elekta’s MOSAIQ Radiation Oncology information system (version 2.60, IMPAC Medical Systems), all patient information is collected and accessible, so you can create exhaustive reports. For this study a report including arrival time, wait time, treatment time and total time in the department was created for all radiotherapy treatments. Agility and Synergy are located in the same site, but Infinity is in a satellite location. Agility machine is dedicated mostly to VMAT treatments, meanwhile Synergy carry on only 3D treatments and Infinity performs VMAT as well as 3D treatments. Results Medium total treatment time was 15.1 min; median was 13.9 min. On average, patients arrive 30.5 min before the scheduled time. Therefore mean total time in the department was 45.6 min. In addition, for each machine, results were as follow: Agility: 1214 appointments. Average (minutes): early arrival 44.7, total time 45.3, wait time 30.6 and treatment time 14.8. Only 9.6% of the appointments arrived late. Synergy: 1541 appointments. Average (minutes): early arrival 36.8, total time 45.5, wait time 29.8 and treatment time 15.7. A 9.4% of the appointments arrived late. Infinity: 1182 appointments. Average (minutes): early arrival 22.0, total time 46.1, wait time 31.3 and treatment time 14.8. A 21.9% of the appointments arrived late. Conclusions In summary, patient waiting time and total time are very similar for the three machines. Despite the fact all VMAT treatments have a daily cone beam CT for patient positioning; medium treatment time for Agility is similar to the other machines which perform less VMAT treatments. Furthermore, many patients depend on public/private transport to arrive to their appointments; Infinity machine has the higher rate of late appointments, which could be related with a problem in the transport system. Therefore these results not only provide feedback but also could allow detecting problems and consequently improving waiting times for the patients.

Physician Staffing for Emergency Departments with Time-Varying Demand

Fluctuations in emergency department (ED) patient arrivals during the day are one of the main causes of the long waiting times that are frequently encountered, and ED staffing is one of the key drivers of ED service quality improvement. This paper first proposes discrete-time models for approximating the patient waiting times for any given ED staffing. The waiting time approximation is based on three simple ideas: the separation of patients served in a period and patients overflowed, the combination of M/M/c approximation for patients served and waiting time analysis of overflow patients, and the transformation of the performance evaluation into an optimization problem with the number of overflow patients as decision variables. The resulting waiting time approximations are then integrated into ED staffing optimization models, and variable neighborhood search algorithms are developed to solve the ED staffing models. Numerical experiments with real-life data from Chinese hospitals are performed to validate the proposed models and algorithms. The results show that the proposed methodology is able to significantly reduce the total waiting time of patients without increasing staff capacity. The online appendix is available at https://doi.org/10.1287/ijoc.2017.0799 .

ASYMPTOTIC WAITING TIME ANALYSIS OF A FINITE-SOURCE M/M/1 RETRIAL QUEUEING SYSTEM

The aim of the paper is to derive the distribution of the number of retrial of the tagged request and as a consequence to present the waiting time analysis of a finite-source M/M/1 retrial queueing system by using the method of asymptotic analysis under the condition of the unlimited growing number of sources. As a result of the investigation, it is shown that the asymptotic distribution of the number of retrials of the tagged customer in the orbit is geometric with given parameter, and the waiting time of the tagged customer has a generalized exponential distribution. For the considered retrial queuing system numerical and simulation software packages are also developed. With the help of several sample examples the accuracy and range of applicability of the asymptotic results in prelimit situation are illustrated showing the effectiveness of the proposed approximation.