BACKGROUND: Routine clinical biochemistry tests are crucial for clinical diagnostics and play a key role in enhancing outpatient turnover efficiency and patient satisfaction. This study aimed to implement Lean Six Sigma in the biochemistry laboratory of a hospital in China to improve efficiency and quality by reducing turnaround time.
METHODS: The study was conducted from January to December 2023, using the DMAIC (Define, Measure, Analyze, Improve, Control) framework, and employed tools such as the voice of the customer, Value Stream Mapping, \'5 whys\' technique, Nominal Group Technique, and Pareto chart.
RESULTS: The turnaround time for outpatient routine clinical biochemistry tests was reduced from 139 min to 58 min (p < 0.05), effectively increasing both patient and physician satisfaction.
CONCLUSIONS: Lean Six Sigma aimed to reduce the turnaround time for biochemical tests have significant advantages. This study confirms the effectiveness of Lean Six Sigma in a Chinese clinical laboratory setting and provides guidance for optimizing efficiency in global clinical laboratories with limited implementation experience, constrained technical and equipment resources, and high demand for medical diagnostics.

Under Taiwan\'s National Health Insurance (NHI) system, it\'s crucial for all healthcare providers to accurately submit medical expense claims to the National Health Insurance Administration (NHIA) to avoid incorrect deductions. With changes in healthcare policies and adjustments in hospital management strategies, the complexity of claiming rules has resulted in hospitals expending significant manpower and time on the medical expense claims process. Therefore, this study utilizes the Lean Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) management approach to identify wasteful and non-value-added steps in the process. Simultaneously, it introduces Robotic Process Automation (RPA) tools to replace manual operations. After implementation, the study effectively reduces the process time by 380 min and enhances Process Cycle Efficiency (PCE) from 69.07 to 95.54%. This research validates a real-world case of Lean digital transformation in healthcare institutions. It enables human resources to be allocated to more valuable and creative tasks while assisting hospitals in providing more comprehensive and patient-centric services.

BACKGROUND: Lean, especially Value Stream Mapping is increasingly used in hospitals to optimize processes. This method, which originated in the automotive industry, enables all staff involved in the process to make it more customer-friendly. Despite the widely reported success of Lean projects, they have failed in some cases. This study investigated the contextual factors and mechanisms that contribute to a successful implementation of Value Stream Mapping.
METHODS: Value Stream Mapping was applied to the discharge process in four breast cancer centers. A mixed-method approach was used in two steps. First, to verify the successful implementation, defined as time optimization, time measurement was conducted at three points in time and analyzed using an ANOVA. Second, an analysis of contextual factors was combined with a qualitative content analysis of mechanisms based on normalization process theory, using routine data, meeting protocols, field notes, and interview transcripts as data source.
RESULTS: At one of the four breast cancer centers, lead- and waiting time were significantly reduced; at the others, these reductions did not occur. Failure/success cannot be explained by the size of the hospital, the number of cases or staffing levels. The variable project team composition is evident, especially leadership involvement.
CONCLUSIONS: A comparative analysis was conducted to identify the factors that led to success. These factors were: participation of all leaders relevant to the process, in the case of the discharge process including medical and nursing leaders; dissemination of the changes from the project team to colleagues including its sense and possibility to discuss it; joint reflection of the implementation process in regular work team meetings.
CONCLUSIONS: These results confirm the important role of leadership in implementation projects. Leadership support enabled the mechanisms found. The used combination of theoretical approaches from management research and implementation science determined the interpretation and should be applied more often in implementation science.

Optimising available resources and minimising production costs and throughput time is vital for first-tier suppliers in the worldwide automotive sector. To develop this type of optimisation and efficiency, MAHLE applied Action Research (AR) in one of its factories located in Spain. A multidisciplinary collaborative work team was created with the aim of deploying the AR initiative in combination with Lean Manufacturing and Six Sigma tools. Four improvement and learning cycles were deployed and key performance metrics were defined to collect and measure data in order to analyse the improvements achieved. The application of the AR initiative in the production line of a power filter device enabled improvements in both production times and quality indicators in the manufacturing process. The most outstanding results were the improvements made in the decrease in initial throughput time (34.78%) and in average daily rejections (73.53%). In addition, the AR initiative generated practical and theoretical contributions for business and academia, allowing the AR initiative to be applied in other areas of the company, and contributing to the current state of the art in the industrial application of this methodology.

Changes in healthcare tend to be project-based with whole system change, which acknowledges the interconnectedness of socio-technical factors, not the norm. This paper attempts to address the question of whole system change posed by the special issue and brings together other research presented in this special issue. A case study approach was adopted to understand the deployment of a whole system change in the acute hospital setting along four dimensions of a socio-technical systems framework: culture, system functioning, action, and sense-making. The case study demonstrates evidence of whole system improvement. The approach to change was co-designed by staff and management, projects involving staff from all specialities and levels of seniority were linked to each other and to the strategic objectives of the organisation, and learnings from first-generation projects have been passed to second and third-generation process improvements. The socio-technical systems framework was used retrospectively to assess the system change but could also be used prospectively to help healthcare organisations develop approaches to whole system improvement.

OBJECTIVE: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.

Lean Six Sigma (LSS) has been recognized as an effective management tool for improving healthcare performance. Here, LSS was adopted to reduce the risk of healthcare-associated infections (HAIs), a critical quality parameter in the healthcare sector.
Lean Six Sigma was applied to the areas of clinical medicine (including general medicine, pulmonology, oncology, nephrology, cardiology, neurology, gastroenterology, rheumatology, and diabetology), and data regarding HAIs were collected for 28,000 patients hospitalized between January 2011 and December 2016. Following the LSS define, measure, analyse, improve, and control cycle, the factors influencing the risk of HAI were identified by using typical LSS tools (statistical analyses, brainstorming sessions, and cause-effect diagrams). Finally, corrective measures to prevent HAIs were implemented and monitored for 1 year after implementation.
Lean Six Sigma proved to be a useful tool for identifying variables affecting the risk of HAIs and implementing corrective actions to improve the performance of the care process. A reduction in the number of patients colonized by sentinel bacteria was achieved after the improvement phase.
The implementation of an LSS approach could significantly decrease the percentage of patients with HAIs.

Research service cores at academic health centers are important in driving translational advancements. Specifically, biostatistics and research design units provide services and training in data analytics, biostatistics, and study design. However, the increasing demand and complexity of assigning appropriate personnel to time-sensitive projects strains existing resources, potentially decreasing productivity and increasing costs. Improving processes for project initiation, assigning appropriate personnel, and tracking time-sensitive projects can eliminate bottlenecks and utilize resources more efficiently. In this case study, we describe our application of lean six sigma principles to our biostatistics unit to establish a systematic continual process improvement cycle for intake, allocation, and tracking of research design and data analysis projects. The define, measure, analyze, improve, and control methodology was used to guide the process improvement. Our goal was to assess and improve the efficiency and effectiveness of operations by objectively measuring outcomes, automating processes, and reducing bottlenecks. As a result, we developed a web-based dashboard application to capture, track, categorize, streamline, and automate project flow. Our workflow system resulted in improved transparency, efficiency, and workload allocation. Using the dashboard application, we reduced the average study intake time from 18 to 6 days, a 66.7% reduction over 12 months (January to December 2015).

OBJECTIVE: Timely communication is important to ensure high-quality health care. To facilitate this, the Gastro Intestinal Oncology Center Amsterdam (GIOCA) stipulated to dispatch medical reports on the day of the patient\'s visit. However, with the increasing number of patients, administrative processes at GIOCA were under pressure, and this standard was not met for the majority of patients. The aim and objective of this study was to dispatch 90% of medical reports on the day of the patient\'s visit by improving the logistic process.
METHODS: To assess the main causes for a prolonged dispatch time and to design improvements actions, the roadmap offered by Lean Six Sigma (LSS) was used, consisting of five phases: Define, Measure, Analyze, Improve and Control (DMAIC roadmap).
RESULTS: Initially, 12.3% of the reports were dispatched on the day of the patient\'s visit. Three causes for a prolonged dispatch time were identified: (1) determining which doctors involved with treatment would compose the report; (2) the reports composed by a senior resident had to be reviewed by a medical specialist; and (3) a medical specialist had to authorize the administration to dispatch the reports. To circumvent these causes, a digital form was implemented in the electronic medical record that could be completed during the multidisciplinary team meeting. After implementation, 90.6% of the reports were dispatched on the day of the visit.
CONCLUSIONS: The dispatch time of reports sent from hospital to primary care can be significantly reduced using Lean Six Sigma, improving the communication between hospital and primary care.