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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 purpose of this paper is to explore and critically review the existing literature on applications of Lean Methodology (LM) and Discrete-Event Simulation (DES) to improve resource utilization and patient experience in outpatient clinics. In doing, it is aimed to identify how to implement LM in outpatient clinics and discuss the advantages of integrating both lean and simulation tools towards achieving the desired outpatient clinics outcomes.

A theoretical background of LM and DES to define a proper implementation approach is developed. The search strategy of available literature on LM and DES used to improve outpatient clinic operations is discussed. Bibliometric analysis to identify patterns in the literature including trends, associated frameworks, DES software used, and objective and solutions implemented are presented. Next, an analysis of the identified work offering critical insights to improve the implementation of LM and DES in outpatient clinics is presented.

Critical analysis of the literature on LM and DES reveals three main obstacles hindering the successful implementation of LM and DES. To address the obstacles, a framework that integrates DES with LM has been recommended and proposed. The paper provides an example of such a framework and identifies the role of LM and DES towards improving the performance of their implementation in outpatient clinics.

This study provides a critical review and analysis of the existing implementation of LM and DES. The current roadblocks hindering LM and DES from achieving their expected potential has been identified. In addition, this study demonstrates how LM with DES combined to achieve the desired outpatient clinic objectives.

This case study aims to demonstrate the strengths of the Lean Six Sigma (LSS) methodology to improve the acute ischemic stroke (AIS) treatment rates and reduce process lead time at Baruch Padeh Medical Center (BPMC), a rural hospital in the Galilee region of Northern Israel. The LSS project redefined the BPMC stroke care pathway and increased its efficacy.

The LSS methodology was implemented in September 2017 by integrating lean principles and the Six Sigma DMAIC (Define–Measure–Analyze–Improve–Control). Existing procedures, field observation, ad hoc measurement and in-depth interviews were utilized, and the GEMBA method was implemented to identify root cause and improve actions optimizing the stroke pathway.

The presented case shows the usefulness of the LSS methodology in improving quality performance in a rural hospital. The intervention allowed the BPMC to improve the intravenous tissue plasminogen activator (IV-tPA) administration rate (+15.2%), reducing the process lead time. The lead time of door-to-computer tomography decreased from 52 to 26 min, and the door-to-needle time decreased from 94 to 75 min.

The present case study shows the implementation of the LSS methodology aimed to improve the IV-tPA administration rate and reduce the stroke pathway lead time in a rural hospital. The case demonstrates the potential for the LSS methodology to support the AIS pathway optimization and represents a guide for healthcare organizations located in rural areas.

The purpose of this paper is to determine the major influencing factors for the COVID 19 patients’ satisfaction with a six sigma framework model and to explore the successful deployment of six sigma in the health-care sector a case study on COVID 19 patients’ satisfaction.

The study is based on a descriptive research design conducted in Chennai, India between May to July 2020 wherein 1,000 COVID 19 patients were studied. The convenience sampling method is used by the researcher for data collection. In this research paper, define-measure-analysis-improve-control methodology has been applied and factors such as assurance, process standardization, infrastructure, waiting time, cost were analyzed using quality function deployment (QFD), regression analysis and Monte Carlo simulation.

The applied six sigma model indicated that process standardization contributed the most toward the variation in COVID 19 patients’ satisfaction. Assurance by doctors is the second important factor. The interpersonal quality is important, which indicates a higher level of psychological needs in COVID 19 patients. Waiting time is another important factor influencing COVID 19 patients’ satisfaction. One of the unexpected findings is that cost is insignificant in influencing COVID 19 patients’ satisfaction.

Six Sigma focuses on process variation improvement that encourages data analysis and problem-solving statistical techniques and evaluates the ability of a process to perform defect-free. Six sigma focused toward COVID 19 patients’ satisfaction has not been carried out, which this paper has done.

Izmir, the third largest city of Turkey, is an important trade hub and port. Since its early years, the city has been the home of many civilisations, nations and cultures. The Romani people can be counted among these cultures. In the centre of Izmir city, there are around 500,000 Romani inhabitants. The increasing number of migrants to Izmir and the obligatory settlement options, usually in poorer neighbourhoods, aggravates the situation. Within this context, the focus of administrative authorities on poorer neighbourhoods with a significant Romani majority and its effects to and connections with the urban improvement programme must be re-evaluated considering the benefit of the city and social-institutional support, including non-governmental institutions, must be maintained.