Lean Improvement Research Articles

Optimizing Hierarchical Condition Category-Risk Adjustment Factor Management in Population Health Using Rapid Process Improvement Methods.

Centers for Medicare & Medicaid Services provides reimbursement through Hierarchical Condition Category (HCC) coding. Medical systems strive toward risk adjustment optimization, often implementing costly chart review processes. Previously, our organization implementing countermeasures through workflows was complex and performed in silos. Our goal was to put in place HCC-Risk Adjustment Factor (RAF) improvement tools to optimize HCC-RAF management in Population Health using rapid process improvement methods. In this quality improvement analysis (IRB#806198), we used Lean methodology to develop tools and implement streamlined processes for providers to manage, document, and code high-risk HCC conditions. Rather than applying costly countermeasures, Transformational Healthcare conducted a Rapid Process Improvement Workshop (RPIW), with workgroups implementing proposed changes, to improve processes. Each of these tools was embedded in standard work, for teams to use in practice. Tools included the development of RPIW-inspired work groups, a Provider Education website, tip sheets, clinical champions, trainings, audits, practice alerts, smart phrases, schedule view tools, severity scores, reports, dashboards, on-screen decision-support tools, coding expertise, and HCC standard work. Quantitatively, Year 1 showed enterprise HCC-RAF scores improved by 4.1%. We were able to develop tools for providers and team members to allow for more optimized pathways. Although quantitatively we realized an improvement in enterprise HCC-RAF score, our overall aim was to improve process flow and limit waste. Leveraging Lean improvement methods for the collective design of tools has supported culture change. In the end, we found that providers are indeed willing to adopt these newly built tools. These tools have optimized operations, allowing providers to work smarter, not harder.

A Structured Model for continuous improvement methodology deployment and sustainment: A Case Study

This research focuses on designing a clear methodology for problem-solving. It investigates the application of a defined ‘Lean’ methodology for the proactive application of process improvement activities using a phased digitized measurement and monitoring system. This case study in a Medtech organisation utilised the Plan, Do, Check, Act (PDCA) model to develop a Lean system and structure to support managing the process improvement or project management element of a Continuous Improvement (CI) framework. The results from the pilot of this study delivered financial gains and demonstrated how a robust structure and methodology to measure improvement activity and success provided a strong, sustainable foundation for customer satisfaction, efficiency, cost reduction and employee engagement improvement. It also highlighted the importance of focusing on proactive process improvement as part of a CI framework. The study provides valuable insights into the effective implementation of Lean principles and process improvement via a sustainable model, thereby contributing to the body of knowledge in this field.. This study demonstrated how the developed model supported process improvement activity underpinning the development of a wider continuous improvement culture to support Lean deployment and sustainment and that systems can drive behaviour. Additionally, this application in the healthcare manufacturing sector adds to the sparse application in the literature from this sector.

Application of Inspection Programs for Risk Assessment by Factory Control Laws

Presently, there is still a high risk of non-compliance with the law in many factories, including cases where factories have risk control measures and have high accident statistics or complaints that come from impacts on communities and the environment at a high rate. The study aims to design and develop a factory inspection program and apply it to analyze and assess compliance risks with factory control laws. Data was collected from 50 factories to collect the risk assessment for compliance with the laws. The program's components consist of inspection to ensure compliance with factory control laws and risk assessment. The study found that the inspection processes and risk assessment compliance with the laws can be improved by using the Lean Work Improvement Principle with the Eliminate, Combine, Rearrange, and Simplify (ECRS) technique, resulting in increased efficiency at an average of 50% and for the conformity verification process by the factory control laws. Applying the factory inspection program according to the factory control laws reduced the audit time by an average of 9.17 hours (Productivity Up to 79%) from using the sample groups. This study has demonstrated the potential and benefits of using a risk assessment program in in-depth analysis for factory control. It can be used as an essential reference for future program development research. The satisfaction assessment results of the sample groups were very high. Besides, experts' comments strongly agreed to implement an inspection program after their usage, instilling confidence in its validity.

Machine learning-based lean service quality improvement by reducing waiting time in the healthcare sector

PurposeThe study presented healthcare service quality, lean thinking and Six Sigma to enhance patient satisfaction. Moreover, the notion of machine learning is combined with lean service quality to bring about the fundamental benefits of predicting patient waiting time and non-value-added activities to enhance patient satisfaction.Design/methodology/approachThe study applied the define, measure, analyze, improve and control (DMAIC) method. In the define phase, patient expectation and perception were collected to measure service quality gaps, whereas in the measure phase, quality function deployment (QFD) was employed to measure the high-weighted score from the patient's voice. The root causes of the high weighted score were identified using a cause-and-effect diagram in the analysis phase.FindingsThe study employed a random forest, neural network and support vector machine to predict the healthcare patient waiting time to enhance patient satisfaction. Performance comparison metrics such as root-mean-square error (RMSE), mean absolute error (MAE) and R2 were accessed to identify the predictive model accuracy. From the three models, the prediction performance accuracy of the support vector machine model is better than that of the neural network and random forest models to predict the actual data.Practical implicationsLean service quality improvement using DMAIC, QFD and machine learning techniques can be generalized to predict patient waiting times. This study provides better realistic insights into patient expectations by announcing waiting times to enable data-driven service quality deliveries.Originality/valuePrior studies lack lean service quality, Six Sigma and waiting time prediction to reduce healthcare waste. This study proposes lean service quality improvement through lean Six Sigma (LSS), i.e. DMAIC and machine learning techniques, along with QFD and cause-and-effect diagram.

Literature Review: Financial Management in Hospitals Using Process Improvement Methods

Financial management in hospitals faces significant challenges due to increasing healthcare costs and the demand to maintain high-quality patient care. Process Improvement methods such as Lean and Continuous Improvement have been adopted by hospitals to address these challenges. This study aims to review the literature regarding the impact of implementing Lean and Continuous Improvement methodologies on hospital financial management. The research methodology employed a systematic approach, analyzing studies published between 2018 and 2023. The results of the review showed that the implementation of Lean and Continuous Improvement methods significantly improved operational efficiency, leading to cost reductions of up to 30%, while simultaneously enhancing patient care quality and staff satisfaction. In conclusion, these methodologies offer a sustainable approach for hospitals to manage financial pressures without compromising the quality of care. Hospitals are encouraged to adopt these strategies to achieve long-term financial stability and operational excellence.

A Model for a Green, Lean Sustainable Improvement with Performance Measurement

A Model for a Green, Lean Sustainable Improvement with Performance Measurement

A-195 Combination of Lean Mindset, Robotics and Digitalization allowed us to manage a 2.5 times increase in workload in our central reference lab

Abstract Background Our Agilus Diagnostics, Gurugram, India is a Central Reference Laboratory and part of the pan-India network over 400 lab in India. Our Gurugram lab delivers 3,200 tubes in the serum work area in 17 hour operations daily and is ISO 15189 and CAP accredited.In Jan 2023, our lab started to support Govt PHC Program samples and our workload increased to 8000 tubes. This was a clear operational and clinical challenge for us with a 2.5 x jump in workload. To achieve this goal, a lean mindset with process improvement steps were to be applied required across the total testing process. This lean approach was supported by cobas ® Lab Automation systems managed by navify ® Lab Operations informatics automation solution. This poster explains our journey of planning, implementing, and delivering on our goal of predictable operational efficiency when faced with this challenge. Methods We took 4 major steps We redesigned lab processes using lean process improvement operational dashboards. This poster will show the metric we track which help eliminate waste in the system. We optimized our total lab automation solution with smart load balancing across cobas ® Pro integrated analyzers and staff friendly recursive workflow. Clear and strict use of off peak hours for maintenance and QC procedures and standardized predictable schedule of operation. This poster will share our time table with key milestones across the 24 hours We built on the Informatics solution using 5 layered Auto verification rules based decision framework. IQC, Systems Flags check, Sample Quality checks, Biological Reference check, custom Auto verification Range, Critical ranges Delta check Criteria, Clinical Correlation Rule are all part of the auto verification logic framework. Results We were able to deliver the following results.Lean process design led to 53% simplification. Number of process steps reduced to 29 from 62 steps across the total testing process. Total Lab Automation has helped improve 90 percentile production TAT by 46% from 250 mins to 135 mins Our 90 % TAT CV has significantly reduced making our production predictable. Over 17,500 results / day reported are subject to auto verification with 87 % of all results auto-verified and auto-approved. Not a single additional employee was added in the analytical or post analytical areas of the lab operations Conclusions Lean Mindset complemented by Total Laboratory Automation along with Decision Automation on an Informatics solution has enhanced lab performance in terms of TAT, Efficiency, and Staff Motivation. This poster will also demonstrate using incremental effectiveness analysis comparative data of key performance indicators, such predictability in production, and efficiency of workforce, senior staff time saved, before and after technology deployment. The challenge of increase in sample workload is real in India and this approach allows for a sustainable way to ensure patient impact with minimum burden on our workforce.

Workflow improvement and financial gain after integration of high-throughput sample processing system with flow cytometer in a high-volume pathology laboratory: Results from a prospective comparative study using Lean principles

BackgroundHighly efficient clinical laboratories are essential for monitoring many human illnesses. Ampath Laboratory Services, the largest pathology lab in South Africa, analyzes large numbers of peripheral blood samples for CD4 levels yearly. ObjectiveTo assess productivity and quality of a newer integrated automated solution, the BD FACSDuet™ Sample Preparation System/BD FACSLyric™ Flow Cytometer using conventional assessment methods and Lean concepts. Materials and methodsThis prospective study compared the performance of the BD FACS™ Sample Preparation Assistant [SPA] III and BD FACSCanto™ II Flow Cytometer with the newly introduced integrated system (BD FACSDuet™/BD FACSLyric™). They were validated for accuracy, precision, and external quality assessment. Process mapping and Lean assessment helped identify steps leading to waste. An economic model was developed to characterize workflow and economic impact associated with total daily hands-on time, processing time, and reworks. ResultsStrong linear correlation was present between both systems. Precision and accuracy studies revealed that all coefficient of variation (CV)% values were below 20 % of allowable limits. External proficiency assessments were within limits. The fully automated workflow of BD FACSDuet™/BD FACSLyric™ permitted better consistency with significantly shorter processing time and batch processing and reduced operator interventions. Lean assessment identified defects with motion, over-processing, waiting, and non-utilized talent. Significant reductions in hands-on and total daily processing time that could increase daily specimen testing efficiency and fewer reworks were associated with the BD FACSDuet™/BD FACSLyric™. Lean improvements translated to significant economic savings associated with operator costs and unnecessary reagent consumption. ConclusionBD FACSDuet™/BD FACSLyric™ is an accurate, reliable, and cost-effective fully automated system for high-volume flow cytometry labs that perform T-cell enumeration using a single-platform and single-tube approach.

Smoothly pass the parcel: implementing the theory of swift, even flow

This research examines the application of the Theory of Swift, Even Flow (TSEF) by a distribution company to improve the performance of its processes for parcels. TSEF was deployed by the company after experiencing lean improvement fatigue and diminishing returns from the time and effort invested. This case study combined quantitative and qualitative approaches to develop a good understanding of the operation. This approach enabled the business to utilise Discrete Event Simulation (DES), which facilitated the implementation of TSEF. From this study, the development of a novel DES application revealed the primacy of process variation and throughput time, key factors in TSEF, in driving improvements. The derived DES approach is reproducible and demonstrates its utility with production improvement frameworks. TSEF, through the visualisations and analysis provided by DES, broadened the scope of improvements to an enterprise level, therefore assisting the business managers in driving forward when lean improvement techniques stagnated. The impact of the research is not limited to the theoretical contribution, as the combination of DES and TSEF led to significant managerial insights on how to overcome obstacles and substantiate change.

Analysis of the disruptions of the digital revolution and its impacts on the evolution of continuous improvement methodologies and lean six-sigma

This research paper delves into the importance of continuous and lean improvements within the context of Industry 4.0. As businesses navigate the digital revolution, enhancing efficiency, effectiveness, and adaptability becomes paramount for maintaining competitiveness. The paper examines the principles of continuous and lean improvements, assessing their relevance in the Industry 4.0 landscape. Utilizing a grounded theory approach, it scrutinizes Industry 4.0 characteristics, market dynamics, disruptive forces, change management tools, and the attainment of lean operations. The findings emphasize the crucial role of continuous and lean improvements in enabling firms to navigate the dynamic Industry 4.0 landscape, effectively respond to market disruptions, and deliver enhanced value to customers. By providing actionable insights, the research paper equips companies to thrive in the digital revolution and leverage Industry 4.0 for sustainable growth. Data from 156 firms, gathered through a five-points-Likert scale questionnaire, informs the research paper. The Statistical Package for the Social Sciences (SPSS) and Analysis of Moment Structures (AMOS) software are used for statistical analyses that look at multicollinearity, content validity, and consistency, construct validity, Analysis of Variance (ANOVA), and the links between technological disruptions, the rise of agile companies, and overall performance. Results indicate that industry transformations directly and indirectly influence the evolution of Industry 4.0 and agility, empowering companies to develop effective strategies to overcome challenges posed by the digital revolution. To achieve this, companies must overhaul production systems, adopt innovative relationship management approaches, recognize and utilize existing organizational knowledge, and integrate it into product development, production operations, and marketing strategies.

Simulation and EVSM-based Lean Line Improvement

Simulation and EVSM-based Lean Line Improvement

Reducing Erythrocyte Sedimentation Rate Ordering: De-implementation and Diagnostic Stewardship.

The Choosing Wisely campaign recommends against the routine use of erythrocyte sedimentation rate (ESR) for the assessment of acute undiagnosed inflammation or infection. We examined ESR and C-reactive protein (CRP) ordering practices at a large, freestanding children's hospital. We found that 80% of ESR orders were placed concurrently with a CRP order. We aimed to reduce the ESR testing rate by 20% within 6 months in both inpatient and emergency department (ED) settings. Applying Lean process improvement principles, we interviewed stakeholders from multiple subspecialties and engaged the institutional laboratory stewardship committee to identify the root causes of ESR ordering and design interventions. We conducted provider education (November 2020) and employed clinical decision support through an order panel in the electronic health record (April 2021). The outcome measures were monthly ESR testing rate per 1000 patient days (inpatient) and per 1000 ED visits, analyzed using statistical process control charts. CRP testing rate was a balancing measure. After intervention implementation, the ESR testing rate decreased from 11.4 to 8.9 tests per 1000 inpatient patient days (22% decrease) and from 49.4 to 29.5 tests per 1000 ED visits (40% decrease). This change has been sustained for >1 year postintervention. Interventions were effective even during the coronavirus disease 2019 pandemic when there was a rise in baseline ED ESR ordering rate. CRP testing rates did not increase after the interventions. Education and clinical decision support were effective in reducing the ESR ordering rate in both inpatient and ED settings.

A Realist Review Protocol into the Contexts and Mechanisms That Enable the Inclusion of Environmental Sustainability Outcomes in the Design of Lean Healthcare Improvement Interventions.

Healthcare makes a significant contribution to the social, economic and environmental benefits of communities. It is correspondingly a significant employer and consumer of both energy and consumables, often at high costs. Lean, a quality improvement methodology focuses on the elimination of non-value add (NVA) activities (steps that do not add value from the perspective of the customer) to improve the flow of people, information or goods. Increasingly, Lean thinking is evolving from its initial focus on eliminating NVA to a more holistic approach that encompasses sustainability. However, little work has been undertaken intentionally, including environmental sustainability outcomes in Lean healthcare interventions. Realist review methodology facilitates an understanding of the extent to which an intervention works, for whom, in what context, why and how, and has proven useful in research relating to Lean interventions in healthcare settings. This protocol provides details for a realist review that will enable an understanding of the specific contexts in which certain mechanisms are activated that enable the inclusion of environmental sustainability outcomes in the design of Lean healthcare improvement interventions.

Enfoque metodológico para el aprovechamiento de mermas de transformación agrícola basado en manufactura esbelta: Caso de estudio en una finca cafetera en Colombia

Improvements in production systems that use the lean manufacturing approach known as “Lean” have the objective of eliminating or reducing waste or process inefficiencies (muda). This approach is increasingly adopted by different industrial sectors, including agriculture. Although Lean improvements are traditionally applied to existing processes from cultivation to distribution, opportunities to intervene in processing wastes (losses) are left aside. This article presents a methodological approach framed in five Lean principles, made up of six activities aimed at the design of new processes that make use of the losses generated by harvesting and agricultural transformation. The methodological approach is applied in a Colombian coffee farm where parchment coffee transformation processes are developed. A parallel losses composting process is designed that transforms defective, green, overripe beans, coffee pulp, mucilage and husk. The results show that by applying the methodological approach on the coffee farm, a level of losses transformation of 86% is achieved. Molting is also reduced for both the current parchment coffee production line and the composting line to 35% and 50% respectively. The main reductions are reprocessing and waiting times. Finally, a 30.3% reduction is obtained in the time of activities that do not add value, making both the current and proposed processes more efficient and with better delivery times.

Six Sigma in preconstruction: case study on improving of reinforcement steel processing

Lean process improvements are crucial for enhancing production efficiency. In my research, I examine the application of the DMAIC methodology to develop the MEP facility within the framework of lean Six Sigma. Highlighting the challenges of precast concrete production, my study details how lean management aids in efficient process design and measurement. Introducing lean Six Sigma methodology involves standardizing processes and ensuring their effective development, contributing to the facility's efficiency

Implementing the Lean 5S process improvement to boost efficiency and cost savings in hospital supply rooms.

A strong link exists between adequate supply chain management and nurse efficiency and satisfaction. Implementing Lean methodology, specifically 5S process improvement, staff created a unit-based supply room that was clean, safe, and well organized which led to reduced waste, greater efficiency, and cost savings.

Economic Impact of Lean Healthcare Implementation on the Surgical Process.

The objective of this study was to analyse and detail surgical process improvement activities that achieve the highest economic impact. Over 4 years, a team of technicians and healthcare professionals implemented a set of Lean surgical process improvement projects at Vall d'Hebron University Hospital (VHUH), Barcelona, Spain. Methods employed in the study are common in manufacturing environments and include reducing waiting and changeover time (SMED), reducing first time through, pull, and continuous flow. Projects based on these methods now form part of the daily routine in the surgical process. The economic impact on the hospital's surgical activity budget was analysed. Process improvements have led to annual operational savings of over EUR 8.5 million. These improvements include better patient flow, better management of information between healthcare professionals, and improved logistic circuits. The current cultural shift towards process management in large hospitals implies shifting towards results-based healthcare, patient-perceived value (VBHC), and value-added payment. A Lean project implementation process requires long-term stability. The reason a considerable number of projects fail to complete process improvement projects is the difficulty involved in establishing the project and improving management routines. Few studies in the literature have investigated the economic impact of implementing Lean management a posteriori, and even fewer have examined actual cases. In this real case study, changes to surgical block management were initiated from stage zero. After being carefully thought through and designed, changes were carried out and subsequently analysed.

Application of lean and quality improvement methods for improving operational performance in coal supply chains: a case study

PurposeThe application of lean and quality improvement methods is very common in process improvement projects at organisational levels. The purpose of this research is to assess the adoption of Lean Six Sigma™ approaches for addressing a complex process-related issue in the coal industry.Design/methodology/approachThe sticky coal problem was investigated from the perspective of process-related issues. Issues were addressed using a blended Lean value stream of supply chain interfaces and waste minimisation through the Six Sigma™ DMAIC problem-solving approach, taking into consideration cross-organisational processes.FindingsIt was found that the tendency to “solve the problem” at the receiving location without communication to the upstream was, and is still, a common practice that led to the main problem of downstream issues. The application of DMAIC Six Sigma™ helped to address the broader problem. The overall operations were improved significantly, showing the reduction of sticky coal/wagon hang-up in the downstream coal handling terminal.Research limitations/implicationsThe Lean Six Sigma approaches were adopted using DMAIC across cross-organisational supply chain processes. However, blending Lean and Six Sigma methods needs to be empirically tested across other sectors.Practical implicationsThe proposed methodology, using a framework of Lean Six Sigma approaches, could be used to guide practitioners in addressing similar complex and recurring issues in the manufacturing sector.Originality/valueThis research introduces a novel approach to process analysis, selection and contextualised improvement using a combination of Lean Six Sigma™ tools, techniques and methodologies sustained within a supply chain with certified ISO 9001 quality management systems.

USING THE LEAN MANUFACTURING METHODOLOGY TO IMPROVE THE QUALITY OF THE ENTERPRISE'S BUSINESS PROCESSES

Formulation of the problem. In the conditions of global competition, lean production acquires special importance. For enterprises all over the world, the only way to survive in the market is to produce goods and provide services that most fully satisfy the demands of consumers, while using advanced management methods and technologies. Lean manufacturing is one of the modern tools of production organization and management technology, which is used to improve the quality of products and services, the most complete satisfaction of consumer needs, while ensuring a careful attitude to the company's resources and their savings.
 The purpose of the study is the further development of methodological, methodical and practical approaches to the concept of Lean manufacturing to improve the quality of the enterprise's business processes.
 Research methods. The research used scientific methods, such as theoretical generalization, comparison, analysis, synthesis.
 Result. In the process of research, a comparison of traditional business management and the concept of lean production was made and revealed. that the concept of lean production has such advantages as the transition from centralized, vertical management to horizontal, involvement of all employees in the process, teamwork, focus on rational use of resources. The concept of lean production is aimed at eliminating the following main types of losses: overproduction of goods; waiting for raw materials, semi-finished products, necessary service information; unnecessary movement of materials; redundant processing steps arising due to errors in the design of business processes; excessive stocks and business processes leading to their occurrence; unjustified rotation of personnel in the work process; production of waste; underutilization of employees' creative potential.
 Conclusions. Six main elements and 52 components (requirements) of Lean manufacturing are defined based on the SAE J4000 standard for more successful application of lean manufacturing ideas in practice production to analyze the levels of implementation of lean manufacturing methodology components and elements. The main elements of the concept of lean manufacturing, the development and improvement of which should be focused on, are: company management and trust in it; enterprise personnel; information environment; chain "supplier – organization – consumer"; product; business processes. An important role in the concept of lean manufacturing is played by the 5S ordering system and the system of general maintenance of TPM equipment .
 Keywords: lean manufacturing; losses; flow of value creation; 5S ordering system; system of general maintenance of TPM equipment; SAE standard J4000.

Topical Application of Acerola Cherry Powder in Combination With Rosemary Extract Extends the Shelf Life of Beef Chuck Roll and Bone-In Short Rib Steaks

Improving the shelf life of steaks from beef chuck rolls and bone-in short ribs, items commonly exported, will increase the demand of beef in international markets. Our objectives were to determine the effect of topically applying combinations of acerola cherry powder and rosemary extract on steak color and lipid oxidation of beef chuck roll and bone-in short rib. USDA Choice beef chuck rolls (Institutional Meat Purchase Specifications [IMPS] 116A; N=9) andbone-in short ribs (IMPS 123A; N=18) were aged (0°C) 28 d and cut into 1.0 cm-thick steaks. Steak treatments included the following: untreated control (C) or topically sprayed (2 mL) with an acerola cherry powder solution (0.05% A), rosemary extract solution (0.10% R), or mixture of acerola cherry powder and rosemary extract (M1=0.05% A+0.1% R; M2=0.1% A+0.1% R; M3=0.05% A+0.2% R; M4=0.1% A+0.2% R). On day 0 of retail display, oxygen consumption, metmyoglobin-reducing activity, and lipid oxidation were measured. Lipid oxidation was evaluated again following 4 d of retail display. Chuck roll steak color was scored twice daily, whereas short rib lean and bone marrow color were scored once daily throughout 4 d of retail display. Treating chuck roll steaks with M2, M3, and M4 decreased lipid oxidation compared to C and A (P=0.004). In short rib steaks, lipid oxidation remained constant from day 0 to 4 treated with M4 but increased for all other treatments (P<0.001). Chuck roll steaks treated with A, M2, and M3 were redder than C steaks (P=0.001). On days 0 and 4, untreated bone marrow was less red than all the antioxidant treated bone marrow (P=0.011). Antioxidant treatment did not improve subjective lean color for the chuck roll (P=0.324) or bone-in short rib (P=0.081). Topical application of M4 (0.1% acerola cherry powder and 0.2% rosemary extract) reduced lipid oxidation in both chuck roll and bone-in short rib steaks. Additionally, antioxidants alone or in combination with one another improve objective redness scores by up to 2 points; however, the subjective color panel did not observe lean color improvement.