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The purpose of this paper is to explore waiting times in improving access to psychological therapies (IAPT) services before and throughout the COVID-19 pandemic. The paper aims to help develop a better understanding of waiting times in IAPT so that interventions can be developed to address them.

IAPT national data reports was analysed to determine access and in-treatment waiting times before, during and after the COVID-19 pandemic. Time-series data was used to examine referral patterns, waiting list size and waiting times between the period of November 2018 and January 2022. The data covers all regions in England where an IAPT service has been commissioned.

There was a dramatic drop in referrals to IAPT services when lockdown started. Waiting list size for all IAPT services in the country reduced, as did incomplete and completed waits. The reduction in waiting times was short-lived, and longer waits are returning.

This paper aims to contribute to the literature on IAPT waiting times both in relation to, and outside of, COVID-19. It is hoped that the conclusions will generate discussion about addressing long waits to treatment for psychological therapy and encourage further research.

To the best of the authors’ knowledge, there is no published research examining the performance of IAPT waiting times to second appointment. The paper also contributes to an understanding of how IAPT waiting times are measured and explores challenges with the system itself. Finally, it offers an overview on the impact of the COVID-19 pandemic on waiting time performance nationally.

Increased demand and the pressure to reduce health-care costs have led to longer waiting time for patients to make appointments and during the day of hospital visits. The purpose of this study is to identify opportunities to reduce waiting time using lean techniques and discrete-event simulation (DES).

A five-step procedure is proposed to facilitate the effective utilization of lean and DES to improve the performance of the Otolaryngology Head and Neck Surgery Outpatient Clinic at Cleveland Clinic Abu Dhabi. While lean techniques were applied to reduce the potential sources of waste by aligning processes, a DES model was developed to validate the proposed solutions and plan patient arrivals under dynamic conditions and different scenarios.

Aligning processes resulted in an efficient patient flow reducing both waiting times. DES played a complementary role in verifying lean solutions under dynamic conditions, helping to plan the patient arrivals and striking a balance between the waiting times. The proposed solutions offered flexibility to improve the clinic capacity from the current 176 patients up to 479 (without violating the 30 min waiting time policy) or to reduce the patient waiting time during the visit from the current 33 min to 4.5 min (without violating the capacity goal of 333 patients).

Proposing and validating lean solutions require reliable data to be collected from the clinic and such a process could be laborious as data collection require patient and resource tracing without interfering with the regular functions of the clinic.

The work enables health-care managers to conveniently conduct a trade-off analysis and choose a suitable inter-arrival time – for every physician – that would satisfy their objectives between resource utilization (clinic capacity) and average patient waiting time.

Successful implementation of lean requires a supportive and cooperative culture from all stakeholders involved.

This study presents an original and detailed application of lean techniques with DES to reduce patient waiting times. The adopted approach in this study could be generalized to other health-care settings with similar objectives.

The experience of waiting for service is often the first direct interaction between customers and most service delivery processes. The literature on satisfaction with waiting has paralleled the literature on general service satisfaction, in which the relative importance of actual performance, perceived performance, and the disconfirmation between expected performance and perceived performance has been the subject of much debate. This paper presents an empirical study of satisfaction with waiting for service in a fast food environment. The study demonstrates that actual waiting time, perceived waiting time, and the disconfirmation between expected waiting time and perceived waiting time are all related to satisfaction with the waiting experience. It further demonstrates that the relative importance of each of these variables in predicting satisfaction depends on the differences in the needs of the customers. The implications for both theory and practice are significant: the importance of the perception of the experience increases as the importance of the satisfaction measure increases. More specifically, for customers who are concerned about time, the perception of the time spent waiting is a better predictor of satisfaction than the actual waiting time.

Investigates the extent to which there is a gap between customers’ perception of waiting time compared with the actual waiting time and, whether this gap could be reduced. Maister originally identified eight propositions based around the idea that the perception of waiting lines are modified by a range of factors. Although other studies have discussed Maister’s propositions by identifying the level of management control and customers’ perceptions of waiting lines, rarely has the basic idea ‐ that perceived and actual wait times may be different ‐ been empirically tested. Reviews those studies which have compared actual waiting time with perceived waiting time, before going on to report on the first known UK study. The research involved an experimental study into two of Maister’s propositions involving 300 members of the general public. Tests a control group of 100 people queueing in a small retail food outlet to identify whether there is a significant difference between perceived and actual waiting times. Repeats the measurement on two further random samples of 100 people. Then discusses the implications of this study, and the earlier studies, with respect to a revision of Maister’s original eight propositions. Concludes with a review of how queue management may be carried out more effectively in relation to matching more closely actual and perceived waiting times.

The purpose of this study is to explore the influence of an office canteen layout on operations, specifically on customer behaviour before checkout, waiting times, and congestion.

The current study was made in the context of discovery and exemplification. The sample was not randomly obtained: the method of recruitment was purposive and convenient. Two Dutch office canteens were selected based on their motivation to participate in the study. A small exploratory study aiming to report on current practices and to inform on possibilities for future research and intervention. With direct observations the behaviour, waiting times, and congestion of 47 customers were analyzed. Customer behaviour was reported qualitatively, waiting times and congestion were reported quantitatively.

Canteens where customers can move freely before checkout queue, allow them to move away from congestion towards food products and to have more favourable waiting times than customers in canteens with layouts requiring a strict order and line‐up for self‐service and checkout.

The results contribute to the managerial repertoire of facilities managers by illuminating latent positive influences of facility layout on operations, which can stimulate the design of better facilities.

This paper contributes to the understanding of how facilities are interwoven with operations. It also informs on possibilities for future research in this area, for instance, combining approaches that originate from facilities management and operations management. This may lead to future research to recommend specific designs or behaviour‐inducing layouts for increased operational enhancements.

The purpose of this paper is to investigate what factors influence the gap between caller's perception of how long they think they waited and how long they actually waited on hold and to determine what call managers can do to reduce this gap called estimation error.

A field experiment was conducted with a corporation's call center.

The findings were: the higher the estimation error of callers, the less satisfied they are; music increases estimation error, unless callers can choose the music; waiting information reduces estimation error; callers with urgent issues have more estimation error and they overestimate more; and females have higher estimation error and they overestimate more than males.

Limitations are one call center in one context. Implications are identification of antecedents of overestimation.

The paper provides guidelines for call center managers for reducing estimation error and increasing caller satisfaction. It discusses the need for understanding callers and measuring items that are important to them.

The study investigates an under researched variable called estimation error. Study also provides information about some of the causes for why consumers overestimate or underestimate their waiting time. Study provides guidelines from an actual call center and discusses variables that managers can easily use to decrease estimation error and overestimation.

This study examined the waiting times to board an attraction at a theme park (Tokyo DisneySea in Japan) using a simulation based on measured values. Park visitors often complain that waiting times are too long; guests (Disney's term for park visitors) must stand in long, slow-moving queues outdoors in all weather, enduring heat, cold, rain and wind. This can undermine their health and reduce customer satisfaction. To date, no research has offered a scientific approach to solve the problem in the context of theme park queues.

The attraction examined two queues: a short waiting queue for guests with priority entry tickets and a long waiting queue for guests without priority entry tickets. The total number of guests with priority entry tickets remained a constant value, as in the current system; however, the author designed the number as a monotonically increasing function to reduce the waiting times for nonpriority entry. It was impractical to analyze queues or try to explain proposed wait time reduction methods using theories and mathematical models alone. Therefore, the author used a simulation study based on real data to demonstrate the proposed method of this study.

The simulation results indicated that the proposed method significantly decreased guests' waiting times in the nonpriority entry queue, without changing the number of guests in both priority and nonpriority entry queues.

Simple queues can be analyzed using theoretical calculations, but complicated queue systems require simulation methods. Therefore, this paper cannot provide a theoretical basis for the method.

The proposed method offers benefits to managers of any event or location seeking to manage queue times and not just theme parks (e.g. exhibitions, concerts, etc.). Advance tickets are equivalent to priority entry tickets, so applying the proposed method can shorten waiting times on the day of the event.

This study has important practical implications for queues management, and the proposed approach is a unique system that reduces waiting times, thus increasing customer satisfaction. The proposed method can be applied to similar types of priority entry systems.

The purpose of this paper is to investigate the effects of capacity decisions regarding the number of servers/chefs and tables on identifying a change in the number of wait-related anxious customers, customer losses and customers served to meet the waiting time standards of an actual upscale restaurant.

The authors applied a simulation model to present the consequences of restaurant capacity decisions based on waiting time standards. Arena Simulation Software, licensed by Rockwell Automation, was used for modeling and identifying distributions of the data set provided by the restaurant. An experiment was designed for an upscale restaurant with existing five servers/chefs and 50 tables by changing these resources to measure the changes in customers' wait-related anxiety and other service performance indicators.

The results showed that an additional server/chef on weekends decreases the daily average number of anxious customers by nearly 33% and increases the daily average number of customers served by nearly 3% and has a little positive effect of decreasing customer losses. Table insertion for high- and low-requested seating areas had an only positive effect on decreasing customer losses.

In this study, the service capacity is dependent on waiting time, and it is addressed to study the relationship with customers' wait-related anxiety, which is a subjective metric. This study developed a point of view for identifying anxious customers whose waiting times are much longer than their cooking and delivery duration expectations regarding their meal preferences in the cooking stage and waiting experiences in the service entry.

The purpose of this paper is to use Lean Six Sigma (LSS) to reduce patient waiting time in a Kuwaiti private hospital obstetrics and gynaecology clinic.

The define, measure, analyse, improve and control methodology was used. The “define” stage involved identifying patients’ needs, system capabilities and project objectives. The “measure” stage assessed the system’s current state through data collection on waiting times. Dunnett’s test, control charts and process capability analysis were used to ensure data accuracy. In the “analyse” stage, an Ishikawa diagram and Pareto chart were constructed, showing that overbooking appointments, doctors’ unscheduled breaks and doctors not arriving on time were the root causes of the problem. The “improve” stage used an Arena simulation model to represent current and improved system status. The proposed solutions were implemented and monitored in the “control” stage.

A sigma-level improvement of 300 per cent (0.5–2.0) was realized for appointment patients on Saturdays, with a 67 per cent reduction in waiting time. For walk-ins, the sigma level improved by 288 per cent (0.8–3.1), with a 55 per cent reduction in waiting time. For weekday appointments, the sigma level improved by 111 per cent (0.9–1.9), with a 63 per cent reduction in waiting time. For walk-ins, the sigma level improved by 69 per cent (1.6–2.7), with a 46 per cent reduction in waiting time. A cost–benefit analysis estimated the present project value at $656,459, leading to a total of $5,820,319 in savings by 2025.

This paper fulfils the need for process improvement, increasing patients’ satisfaction and hospitals’ profitability using LSS.

To assess and plan alterations in outpatient clinic structure, produces a computer simulation of an outpatient clinic based on detailed time and role measurements from the authors’ clinic. The simulation which used an object‐oriented design method is able to indicate the impact of changes in clinic structure using patient and doctor waiting times in clinic as endpoint measures. Examines the effects of changes in clinic size, consultation time, patient mix, appointment scheduling and non‐attendance. Finds that patient waiting time could be shortened considerably by using an optimizing appointment scheduler to determine appointment intervals. Clinic mix influences patient waiting time, which was shorter with a 1 in 4 ratio of new to follow‐up patients. In mixed clinics, new patients appointments are optimally spread throughout the clinic to reduce patient waiting time. In all new or all follow‐up clinics, waiting time is improved if the appointment interval reflects the consultation time. Computer modelling can help in optimizing clinic management so improving the delivery of care in outpatient services.