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Introduction: Waste in medical research is a relatively well-known issue. However, only a few initiatives exist to address this issue. Lean Management methods (Lean) were developed in industrial manufacturing and later applied within healthcare improvement. Overall, the results from studies of the application of Lean to healthcare appear to be positive in terms of greater efficiency regarding treatment outcomes and patient care. Nevertheless, the application of Lean to improve research processes is not well studied and, given that research alongside clinical practice and experiential knowledge provides the foundation for the treatment and care of patients, it is paramount to identify approaches and review the degree to which they increase efficiency within research procedures. Therefore, this review will scope the landscape of studies that investigated Lean and how to implement Lean in research processes, particularly regarding healthcare research., Methods and Analysis: Our approach follows the methodological framework of Arksey and O'Malley for conducting scoping reviews (PRISMA-ScR). The search strategy for this scoping review was developed using the PCC model. We will identify the relevant literature by searching four search databases: Scopus, Web of Science, Academic Search Premier and Business Source Complete. Next, we will use citation pearl growing to identify all relevant published literature. The data charting process will follow the PRISMA-ScR checklist and will be organised using NVivo. We will generate qualitative and quantitative assessments of the extracted data by using NVivo, RStudio and Excel. We will follow the PRISMA-ScR guideline when reporting the results., Ethics and Dissemination: The review will comprise existing published studies and no primary data will be collected. Our findings will be shared through open access peer-reviewed journals, national and international conferences and emails to all relevant collaborative relationships. We plan to disseminate our findings via academic social media platforms, newspaper articles and blogposts., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: to investigate the contributions of applying the Lean methodology to improve work processes in health and nursing and its impact on associated financial aspects., Method: an integrative review, carried out in six databases, whose sample of ten (100.0%) studies was analyzed and summarized descriptively., Results: the outcomes obtained were stratified into: benefits/barriers to Lean Healthcare implementation; economic aspects involving Lean Healthcare implementation; and process improvements through Lean Healthcare implementation. The majority of studies (60.0%) were carried out in university hospitals, contexts that need to continually improve the quality of services provided, generally with scarce and limited resources, which support the viability of maintaining the teaching, research and extension tripod., Conclusion: three (30.0%) studies highlighted the financial aspects associated with Lean methodology application. The others only mentioned the possibility of financial gains through improving processes and reducing waste.

Objective: This study aims to examine how we can effectively and affordably evaluate the impact of design concepts such as Lean-Led Hospital Design (LLHD) on the allocation of nurses' time spent at different locations. Particularly in patient rooms, as this can be seen as value-adding time., Background: LLHD aims to create a hospital environment that supports value creation for patients and reduces waste. However, only a few studies measure its' effects. One of the reasons for this absence is the lack of an adequate and affordable way to evaluate., Method: Nurses' time spent in patient rooms was used as a proxy for value-adding time. Through studying a pioneering case of LLHD, and drawing on a pre-/postoccupancy evaluation approach, this study used an innovative methodology utilizing mobile tracking devices to adequately provide reliable data about the time nurses spend at specific locations., Results: Our analysis reveals that the answer to the question concerning the impact of LLHD, as advocated by its proponents, on nurses' allocation of time for value-adding activities versus waste time remains inconclusive. Our findings indicate no discernible difference in the amount of value-adding time nurses spent in the old facility compared to the new one., Conclusion: Our experience suggests that mobile tracking devices offer an affordable, efficient means of collecting data that produces objective measurements. Nevertheless, the interpretation of this time-based data necessitates the inclusion of supplementary qualitative information., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background: In this study, we applied a six sigma model to examine cerebrospinal fluid (CSF) biochemical analytes for the first time. Our goal was to evaluate the analytical performance of various CSF biochemical analytes, design an optimized internal quality control (IQC) strategy, and formulate scientific and reasonable improvement plans., Methods: The sigma values of CSF total protein (CSF-TP), albumin (CSF-ALB), chloride (CSF-Cl), and glucose (CSF-GLU) were calculated using the following formula: sigma = [TEa(%)-|bias(%)|]/CV(%). The analytical performance of each analyte was shown using a normalized sigma method decision chart. Individualized IQC schemes and improvement protocols for CSF biochemical analytes were formulated using the Westgard sigma rule flow chart with batch size and quality goal index (QGI)., Results: The distribution of sigma values for CSF biochemical analytes ranged from 5.0 to 9.9, and the sigma values varied for different concentrations of the same analyte. The analytical performance of the CSF assays at the two QC levels is displayed visually in normalized sigma method decision charts. Individualized IQC strategies for CSF biochemical analytes were as follows: for CSF-ALB, CSF-TP and CSF-Cl, use 1 3s with N = 2 and R = 1000; for CSF-GLU, use 1 3s /2 2s /R 4s with N = 2 and R = 450. In addition, priority improvement measures for analytes with sigma values less than 6 (CSF-GLU) were formulated based on the QGI, and their analytical performance was improved after the corresponding improvement measures were taken., Conclusions: The six sigma model has significant advantages in practical applications involving CSF biochemical analytes and is highly useful for quality assurance and quality improvement., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

When increasing the quality in clinical laboratories by decreasing measurement uncertainty, reliable methods are needed not only to quantify the performance of measuring systems, but also to set goals for the performance. Sigma metrics used in medical laboratories for documenting and expressing levels of performance, are evidently totally dependent on the "total permissible error" used in the formulas. Although the conventional biological variation (BV) based model for calculation of the permissible (or allowable) total error is commonly used, it has been shown to be flawed. Alternative methods are proposed, mainly also based on the within-subject BV. Measurement uncertainty models might offer an alternative to total error models. Defining the limits for analytical quality still poses a challenge in both models. The aim of the present paper is to critically discuss current methods for establishing performance specifications by using the measurement of sodium concentrations in plasma or serum. Sodium can be measured with high accuracy but fails by far to meet conventional performance specifications based on BV. Since the use of sodium concentrations is well established for supporting clinical care, we question the concept that quality criteria for sodium and similar analytes that are under strict homeostatic control are best set by biology., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Objectives: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has become a common technique in clinical laboratories in recent years. Because most methods are laboratory-developed tests (LDTs), their reproducibility and quality control (QC) have been controversial. In this study, Westgard Sigma Rules were used to evaluate the analytical performance and establish an individualised internal QC (IQC) strategy for these LDTs., Methods: Taking the LC-MS/MS LDT method for homocysteine (Hcy) as an example, the 'desirable specifications' from the Biological Variation Database were used as quality goals. Based on the external quality assessment (EQA) samples, bias was calculated and the coefficient of variation (CV) was also calculated by IQC measurements for six consecutive months. The analytical performance was evaluated by calculated sigma metrics and an IQC strategy was designed using the Westgard Sigma Rules with run size., Results: Over 116 days within 6 months, a total of 850 data points were collected for each of IQC 1 and IQC 2. The monthly coefficient of variation CV% was 2.57-4.01%, which was non-significant (p-value: 0.75). The absolute bias% for IQC1 and IQC2 was 1.23 and 1.87%, respectively. The allowable total error (TEa) was selected as 15.5%, Sigma metrics were 4.02 and 4.30, and the analytical performance was 'Good'. The 1 3s /2 2s /R 4s /4 1s multi rules (n=4, r=1) with a run size of 200 samples were suggested for the Hcy IQC scheme. The quality goal index (QGI) values were over 1.2, indicating that trueness needed to be improved., Conclusions: The analytical performance of the Hcy LC-MS/MS LDT conformed to the Six Sigma rating level, achieving 'good' (four Sigma). Clinical practice indicated that calibration bias was the primary factor affecting trueness., (© 2023 Walter de Gruyter GmbH, Berlin/Boston.)

Background and Aim: Sigma metrics are applied in clinical laboratories to assess the quality of analytical processes. A parameter associated to a Sigma > 6 is considered "world class" whereas a Sigma < 3 is "poor" or "unacceptable". The aim of this retrospective study was to quantify the impact of different approaches for Sigma metrics calculation., Material and Methods: Two IQC levels of 20 different parameters were evaluated for a 12-month period. Sigma metrics were calculated using the formula: (allowable total error (TEa) (%) - bias (%))/(coefficient of variation (CV) (%)). Method precision was calculated monthly or annually. The bias was obtained from peer comparison program (PCP) or external quality assessment program (EQAP), and 9 different TEa sources were included., Results: There was a substantial monthly variation of Sigma metrics for all combinations, with a median variation of 32% (IQR, 25.6-41.3%). Variation across multiple analyzers and IQC levels were also observed. Furthermore, TEa source had the highest impact on Sigma calculation with proportions of Sigma > 6 ranging from 17.5% to 84.4%. The nature of bias was less decisive., Conclusion: In absence of a clear consensus, we recommend that laboratories calculate Sigma metrics on a sufficiently long period of time (>6 months) and carefully evaluate the choice of TEa source., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Introduction: The modern approach to quality control (QC) in medical laboratories implies the development of a risk-based control plan. This paper aims to develop a risk-based QC plan for a laboratory with a small daily testing volume and to integrate the already optimized moving average (MA) control procedures into this plan., Materials and Methods: A multistage bracketed QC plan for ten clinical chemistry analytes was made using a Westgard QC frequency calculator. Previously, MA procedures were optimized by the bias detection simulation method., Results: Aspartate aminotransferase, HDL-cholesterol and potassium had patient-risk sigma metrics greater than 6, albumin and cholesterol greater than 5, creatinine, chlorides, calcium and total proteins between 4 and 5, and sodium less than 4. Based on the calculated run sizes and characteristics of optimized MA procedures, for 6 tests, it was possible to replace the monitoring QC procedure with an MA procedure. For the remaining 4 tests, it was necessary to keep the monitoring QC procedure and introduce MA control for added security., Conclusion: This study showed that even in a laboratory with a small volume of daily testing, it is possible to make a risk-based QC plan and integrate MA control procedures into that plan., Competing Interests: Potential conflict of interest None declared., (Croatian Society of Medical Biochemistry and Laboratory Medicine.)

Process improvement methodology minimizes barriers to implementing new knowledge., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose: The objective of this paper is to propose a systematic application of Lean Healthcare in the hospitalization activity in the medical clinic entry process., Design/methodology/approach: The methodology used is established in three stages: the first aims to map the process in which the focus activity is inserted, using lean tools, as well as integrating the employees involved in the application. The second is the proposal to apply the systematic, together with the employees, using the A3 tool step by step. Finally, the third stage confirms the applied systematic, collecting the results and analyzing the initial situation with those reached., Findings: As a result, improvements were made in the medical clinic entry process, such as reduced waiting time for patients, at approximately 53.8%, with a decrease in the standard deviation of the times - of approximately 79.14%, and displacement of those involved, of 72%, in addition to eliminating unnecessary activities for the process. Furthermore, the empirical results on the efficiency of this systemic application in medical clinic enable the replication of this proposal, generating a systematic., Research Limitations/implications: Despite establishing a systematic proposal with real results, it is focused on only one application, due to time limitations, may generate a subjective evaluation of the systematic. Thus, for future research, it is recommended to expand this systemic application in other activities of different processes., Practical Implications: The practical implications of this paper are precisely related to the data obtained with the application made, developing a Lean Healthcare systematic not previously seen, which is strategic, systemic and has a roadmap to assist in its application and, in addition, brings with it practical results that prove their efficiency., Social Implications: The social implications of this paper are presented in its empirical results, considering that the study hospital serves, in addition to its host city, 28 other smaller municipalities around it, improving the flow of processes, ensuring better management of the clinic doctor. In addition, the results can assist the processes flow of other medical clinics in hospitals around the world, especially at critical moments, such as pandemics or epidemics., Originality/value: Due to the positive results obtained in the systematic application, this paper fills a gap identified in the literature, proposing a systematic application of Lean Healthcare that is systemic and strategic, in addition to including a roadmap and analysis of data applied in a medium-sized Brazilian hospital, presenting positive practical results exposed in the paper., (© Emerald Publishing Limited.)

Background: Delayed discharges can be a systemic issue. Understanding the systemic factors that contribute to discharge inefficiencies is essential to addressing discharge inefficiencies., Purpose: This article reports on a Lean Six Sigma approach and the process to identifying inefficiencies and systemic barriers to early discharge in a large US academic medical center., Methods: A qualitative methodology guided this project. In particular, direct observation methods were used to help the project team identify factors contributing to discharge inefficiencies., Results: Overall, findings suggest that establishing consistent multidisciplinary team communication processes was a contributing factor to reducing the inefficiencies around discharges. On a more granular level, key barriers included disparate communication systems, disruptors (specifically Kaizen bursts), and unique role challenges., Conclusions: This article provides a framework for addressing discharge inefficiencies. Because the output of the process, a critical contributor to the overall outcome, is often not analyzed, this analysis provides value to others contemplating the same or similar process toward discharge efficiency., Competing Interests: Sue Feldman is a consultant with Guideway Care. Her work there has no relation to the content in this article. The other authors declare no conflicts of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Since it is an important human need and many organizations are involved in the value chain, the agricultural food supply chain is exposed to various risks that arise naturally or through human actions. This study aims to develop the application of a quality function deployment approach to increase the resilience of the food supply chain by understanding customer needs and logistical risks in the food supply chain. In-depth studies with empirical analysis were conducted to determine the importance of customer needs, food supply chain risks, and actions to improve supply chain resilience of SMEs in the agri-food industry. The result shows that the top three customer needs are "attractive, bright color", "firm texture" and "fresh smell". The top three risks in the agri-food supply chain are "improper storage," "Harvest Failure" and "Human Resource Risks" and the top three resilience actions are "continuous training," "preventive maintenance," and "supply chain forecasting." The implications of this study are to propose an idea that broadens the perspective of supply chain resilience in the agri-food industry by incorporating the needs of customers in considering how to mitigate the existing risks to the satisfaction of customers, and it also highlights the relatively low skill and coordination of the workforce in agri-food supply chains., Competing Interests: The authors have declared that no competing interests exist.