UNASSIGNED: Radiotherapy plans with excessive complexity exhibit higher uncertainties and worse patient-specific quality assurance (PSQA) results, while the workload of measurement-based PSQA can impact the efficiency of the radiotherapy workflow. Machine Learning (ML) and Lean Six Sigma, a process optimization method, were implemented to adopt a targeted PSQA approach, aiming to reduce workload, risk of failures, and monitor complexity.
UNASSIGNED: Lean Six Sigma was applied using DMAIC (define, measure, analyze, improve, and control) steps. Ten complexity metrics were computed for 69,811 volumetric modulated arc therapy (VMAT) arcs from 28,612 plans delivered in our Institute (2013-2021). Outlier complexities were defined as >95th-percentile of the historical distributions, stratified by treatment. An ML model was trained to predict the gamma passing rate (GPR-3 %/1mm) of an arc given its complexity. A decision support system was developed to monitor the complexity and expected GPR. Plans at risk of PSQA failure, either extremely complex or with average GPR <90 %, were identified. The tool\'s impact was assessed after nine months of clinical use.
UNASSIGNED: Among 1722 VMAT plans monitored prospectively, 29 (1.7 %) were found at risk of failure. Planners reacted by performing PSQA measurement and re-optimizing the plan. Occurrences of outlier complexities remained stable within 5 %. The expected GPR increased from a median of 97.4 % to 98.2 % (Mann-Whitney p < 0.05) due to plan re-optimization.
UNASSIGNED: ML and Lean Six Sigma have been implemented in clinical practice enabling a targeted measurement-based PSQA approach for plans at risk of failure to improve overall quality and patient safety.

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.

Six Sigma Foundations is a statistical standard that indicates an exceptionally high level of quality, along with a customer satisfaction management approach that intends to lower error rates and boost process efficiency. The Define, Measure, Analyse, Improve, and Control (DMAIC) approach is a fundamental component of Six Sigma and provides an organised framework for process improvement. In contrast to conventional techniques that are more manual-based, Six Sigma emphasises and focuses on making decisions based on facts and evidence. The key to the success of Six Sigma is its reliance on statistical methods. Advanced tools like Pareto charts, histograms, regression analysis, and fishbone diagrams are used ardently for the benefit of customers and to reduce the overall error rate. To support clinical decision-making, a clinical laboratory\'s primary responsibility is to generate test results that are accurate, repeatable, fast, and appropriately interpreted. Ensuring desired clinical outcomes must be the ultimate objective. To accomplish this goal, laboratories must prioritise cost-effectiveness while establishing and maintaining quality in all laboratory procedures. The concept of the Lean Six Sigma (LSS) methodology, which mainly centres on efficiency by discerning and eradicating actions or operations that do not provide any benefit to the organisation, is combined with the proposition of Six Sigma, which emphasises data-driven analyses and optimization. The integration of these powerful concepts aids in the overall improvement of the organisations adopting these techniques. This review provides a brief overview of the benefits of the LSS methodology and its implementation in the oral pathology laboratory.

This research investigates the requirement for and relationship and implementation of a total productive maintenance (TPM) and Reliability Centred Maintenance (RCM) strategy within an Active Pharmaceutical Ingredient (API) Plant. This research aimed to study the tools and techniques of TPM and Reliability Engineering and then deploy a designed model to an API plant. A case study involving Design for Lean Six Sigma phases of Define, Measure, Analyse, Design, and Verify was utilised to build an API site TPM pilot program. Data was collected using interviews across Company \'X\'s local and Global Engineering teams. Process runtime, downtime and plant availability metrics were compiled and a new design for Total Productive Maintenance and Reliability was proposed and verified. A maintenance framework was designed to optimally incorporate Total Productive Maintenance, Reliability and Operational Excellence with an emphasis on Overall Equipment Efficiency (OEE) realizing a 33 % reduction in planned maintenance activities, a 70 % reduction in Corrective Maintenance, Cleaning for Maintenance was reduced by 50 %, the pilot maintenance area of the centrifuge has its OEE increased by 20 % and plant availability increased by two hundred and 6 h. This research highlights the importance of Total Productive Maintenance as a key component of an effective maintenance strategy and its potential to transform maintenance practices. Based on this research and results, TPM is recommended to be applied to any API manufacturing organization. A limitation of the study is that it is a single-site case study. The novelty of this research is based upon the emphasis on Reliability Engineering to remove non-value add Maintenance time from the manufacturing schedule. The Total Productive Maintenance & Reliability model designed and implemented in this research is unique in the literature and can be leveraged by engineering professionals and academics to understand the benefits of TPM.

In Ireland, the extent of outpatient orthopedic waiting lists results in long waiting times for patients, delays in processing referrals, and variation in the consultant caseload. At the study site, the Define, Measure, Analyze, Improve, and Control (DMAIC) Lean Six Sigma framework was applied to evaluate sources of Non-Value-Added (NVA) activity in the process of registering and triaging patients referred to the trauma orthopedic service from the Emergency Department. A pre- (October-December 2021)/post- (April-August 2022) intervention design was employed, utilizing Gemba, Process Mapping, and the TIMWOODS tool. Embracing a person-centered approach, stakeholder Voice of Customer feedback was sought at each stage of the improvement process. Following data collection and analysis, a co-designed pilot intervention (March 2022) was implemented, consisting of a new triage template, dedicated trauma clinic slots, a consultant triage roster, and a new option to refer directly to physiotherapy services. This resulted in the total wait time of patients for review being reduced by 34%, a 51% reduction in the process steps required for registering, and an increase in orthopedic consultant clinic capacity of 22%. The reduction in NVA activities in the process and the increase in management options for triaging consultants have delivered a more efficient trauma and orthopedic pathway.

Objective To increase compliance with Abnormal Involuntary Movement Score (AIMS) documentation for patients taking antipsychotics to recognize and treat tardive dyskinesia in the psychiatry outpatient clinic. Methods The Lean Six Sigma quality improvement (QI) model, utilizing DMAIC steps of define, measure, analyze, improve, control, was followed. Psychiatry attendings and residents were surveyed to assess reasons for AIMS non-documentation, and they ranked their preferred solutions to increase compliance. A random sample of patient charts for individuals on antipsychotic medications was obtained to determine AIMS documentation compliance prior to and following the implementation of improvements. Results The most highly ranked solution was implementing a one-hour AIMS training session. Three months post-intervention, a random sample of 60 patient charts showed that 87% (52/60) of patients had AIMS documented which was a significant increase compared to 3% (1/30) pre-intervention (p<0.001). Conclusion An annual, one-hour AIMS training session for residents improved rates of AIMS documentation.

The Manufacturing sector has suffered to a great extent due to global pandemic COVID-19. This pandemic is forcing the manufacturing industries to look forward to a long term and sustainable business plan, which ensures sustainability in three different aspects i.e. Social, Economic, and Environment. This demands a never before need of higher value to the customer in lesser resources. Implementation of innovative approaches of integrated manufacturing practices i.e. Lean Six Sigma (LSS) and Agile Manufacturing (AM) are need of the hour for long-term business sustainability which can be done by ensuring waste elimination and by adjusting the dynamic changes in the demands and requirements simultaneously without compromising in quality. However, the strategic linkage between LSS and AM practices with the three pillars of sustainability has yet not been described in the literature. In this study an integrated model which consists of six constructs i.e. Managerial practices (C1), Organizational culture practices (C2), Technological practices (C3), Economical Aspects (C4), Social Aspects (C5) and Environmental Aspects (C6) was developed. The purpose of the paper is to scrutinize the relationships between the integrated LSS and AM practices and three aspects of sustainability through Structural Equation Modeling (SEM) technique.. The results of this study depict that there is a correlation exists between integrated LSS -AM practices and sustainability pillars that leads to the improvement of firms\' business competitiveness. This is one of the premier attempts to develop integrated LSS-AM practices structural model with the sustainability aspects.

UNASSIGNED: The American Diabetes Association (ADA) recommends measuring A1c in all inpatients with diabetes if not performed in the prior three months. Our objective was to determine the impact of utilizing Lean Six Sigma to increase the frequency of A1c measurements in hospitalized patients.
UNASSIGNED: We evaluated inpatients with diabetes mellitus consecutively admitted in a community hospital between January 2016 and June 2021, excluding those who had an A1c in the electronic health record (EHR) in the previous three months. Lean Six Sigma was utilized to define the extent of the problem and devise solutions. The intervention bundle delivered between November 2017 and February 2018 included (1) provider education on the utility of A1c, (2) more rapid turnaround of A1c results, and (3) an EHR glucose-management tab and insulin order set that included A1c. Hospital encounter and patient-level data were extracted from the EHR via bulk query. Frequency of A1c measurement was compared before (January 2016-November 2017) and after the intervention (March 2018-June 2021) using χ2 analysis.
UNASSIGNED: Demographics did not differ preintervention versus postintervention (mean age [range]: 70.9 [18-104] years, sex: 52.2% male, race: 57.0% white). A1c measurements significantly increased following implementation of the intervention bundle (61.2% vs 74.5%, P < .001). This level was sustained for more than two years following the initial intervention. Patients seen by the diabetes consult service (40.4% vs 51.7%, P < 0.001) and length of stay (mean: 135 hours vs 149 hours, P < 0.001) both increased postintervention.
UNASSIGNED: We demonstrate a novel approach in improving A1c in hospitalized patients. Lean Six Sigma may represent a valuable methodology for community hospitals to improve inpatient diabetes care.

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.

Community pharmacies represent a highly accessible and convenient setting for vaccination. However, setting-specific barriers exist which contribute to suboptimal vaccination rates, particularly for pneumococcal vaccinations. One proven quality improvement framework growing in use within healthcare settings is Lean Six Sigma (LSS). This paper describes the application of the LSS framework in select locations of a national pharmacy chain. The implementation of a training program for improved recommendation techniques to promote higher rates of pneumococcal vaccinations in high-risk adult populations is also addressed. A mixed-methods approach including pre/post quasi-experimental design and in-depth key informant interviews was used.