Using lean techniques and discrete-event simulation for performance improvement in an outpatient clinic

Abstract

Purpose 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). Design/methodology/approach 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. Findings 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). Research limitations/implications 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. Practical implications 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. Social implications Successful implementation of lean requires a supportive and cooperative culture from all stakeholders involved. Originality/value 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.

A critical review of implementing lean and simulation to improve resource utilization and patient experience in outpatient clinics

“…Finally, a lean practitioner would seek perfection by continuously monitoring and identifying new ways to elevate the clinic's performance. A recent LM and DES article by Demirli et al. (2021) has followed the approach illustrated in Figure 11, which presents a validation of the suggested approach.…”

“…(2021) has followed the approach illustrated in Figure 11, which presents a validation of the suggested approach. In their work, Demirli et al. (2021) jointly employed LM and DES to improve the performance of an ear, nose and throat (ENT) outpatient clinic.…”

“…Finally, a lean practitioner would seek perfection by continuously monitoring and identifying new ways to elevate the clinic's performance. A recent LM and DES article by Demirli et al (2021) has followed the approach illustrated in Figure 11, which presents a validation of the suggested TQM 35,3 approach. In their work, Demirli et al (2021) jointly employed LM and DES to improve the performance of an ear, nose and throat (ENT) outpatient clinic.…”

“…A recent LM and DES article by Demirli et al (2021) has followed the approach illustrated in Figure 11, which presents a validation of the suggested TQM 35,3 approach. In their work, Demirli et al (2021) jointly employed LM and DES to improve the performance of an ear, nose and throat (ENT) outpatient clinic. First, they have defined their primary objective as decreasing the patient waiting time for the appointment and reducing patient waiting time during the visit by increasing the clinic capacity, increasing the resources utilization and designing an efficient patient flow.…”

Value stream mapping from the customer's perspective: expanding concepts, representations and key performance indicators based on a typical real case study

“…They reported difficulties in obtaining correct data in service operations, thus affecting the correctness of results. Demirli et al (2021) claim that VSM identifies important metrics such as process cycle times and patient waiting times, as well as the total patient lead-time. However, Dinis-Carvalho et al (2019) consider that VSM also has certain limitations, such as: inability to represent different flows; difficulty levels for those who are un-familiar with the tool; absence economic indicators; and absence of layout representation; among others.…”