Lean six sigma methodologies improve clinical laboratory efficiency and reduce turnaround times

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

BACKGROUND

Highly 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.

OBJECTIVE

To 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 METHODS

This 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.

RESULTS

Strong 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.

CONCLUSION

BD 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.

Routine Pathological Examination of Clinically Presumed Dupuytren Disease: Does It Add Value?

BACKGROUND

In surgery for Dupuytren disease (DD), palmar fascia specimens are routinely submitted for pathological evaluation. The purpose of this study was to determine the rate of discordant diagnosis and the value of, and costs associated with, routine pathological analysis of palmar fascia tissue extracted in surgery for clinically diagnosed DD.

METHODS

All pathology reports for in-house palmar fascia specimens obtained in surgery for clinically diagnosed DD (time period: January 2001 to December 2020) were retrieved from one academic institution. All specimens were classified by a hierarchical free-text string matching algorithm (HFTSMA) and searched for evidence of malignancy. The primary outcome was percentage of concordant, discrepant, and discordant diagnoses. Secondary outcomes included anatomical location and costs. The HFTSMA was used to capture the anatomical location. Costs included professional, laboratory processing, and ancillary fees based on the Ontario Schedule of Benefits.

RESULTS

The search retrieved 1323 pathology reports, with 1480 palmar fascia specimens, from 1078 individual patients. By diagnosis, 96.1% of specimens (1422/1480) were concordant (fibromatosis), 3.9% (58/1480) were discrepant (scarring/fibrosis, benign fascia/connective tissue, or other benign findings), and 0% (0/1480) were discordant. The most common location was ring finger (n = 381, 48.7%). Ancillary testing was minimal. The cost per palmar fascia specimen was estimated to be CAD $34.57. The institutional costs were approximately CAD $2558.18/year.

CONCLUSIONS

Routine pathological examination of specimens in cases of clinically diagnosed DD does not yield additional clinically important findings and may not warrant their costs.

Designing optimal experiments in metabolomics

BACKGROUND

Metabolomics data is often complex due to the high number of metabolites, chemical diversity, and dependence on sample preparation. This makes it challenging to detect significant differences between factor levels and to obtain accurate and reliable data. To address these challenges, the use of Design of Experiments (DoE) techniques in the setup of metabolomic experiments is crucial. DoE techniques can be used to optimize the experimental design space, ensuring that the maximum amount of information is obtained from a limited sample space.

AIM OF REVIEW

This review aims at providing a baseline workflow for applying DoE when generating metabolomics data.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The review provides insights into the theory of DoE. The review showcases the theory being put into practice by highlighting different examples DoE being applied in metabolomics throughout the literature, considering both targeted and untargeted metabolomic studies in which the data was acquired using both nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry techniques. In addition, the review presents DoE concepts not currently being applied in metabolomics, highlighting these as potential future prospects.

The influence of various sample storage conditions and sample bacterial contamination on concentrations of routine biochemical parameters

Background

The pre-analytical (PA) phase is the most vulnerable phase of the laboratory testing procedure, with critical procedures-collection, handling, sample transport, and time and temperature of sample storage. This study aimed to examine the stability of basic biochemical parameters depending on the samples' storage conditions and the number of freeze-thaw cycles (FTCs). In parallel, the presence of sample bacterial contamination during routine laboratory work was examined.

Methods

Two plasma pools (ethylenediaminetetraacetic acid (EDTA), and sodium-fluoride/potassium oxalate plasma (NaF)) were stored at +4 ˚C/-20 ˚C. Total chole - sterol (TC), glucose, triglycerides (TG), urea, and albumin concentrations were measured using BioSystems reagents (cholesterol oxidase/peroxidase, glucose oxidase/per - oxidase, glycerol phosphate oxidase/peroxidase, urease/ salicylate, and bromcresol green method, respectively) on Ilab 300+. Sample bacterial contamination was determined by 16S rRNA sequence analysis. The expe - riment encompassed a 5 day-period: Day 1-fresh sample, Day 2-1st FTC, Day 3-2nd FTC, Day 4-3rd FTC, Day 5-4th FTC. The appearance of bacteria in two consecutive samples was the experiment's endpoint.

Primer Part 1 - Preparing a laboratory quality improvement project

Quality in laboratory medicine encompasses multiple components related to total quality management, including quality control (QC), quality assurance (QA), quality indicators, and quality improvement (QI). Together, they contribute to minimizing errors (pre-analytical, analytical, or post-analytical) in clinical service delivery and improving process appropriateness and efficiency. In contrast to static quality benchmarks (QC, QA, quality indicators), the QI paradigm is a continuous approach to systemic process improvement for optimizing patient safety, timeliness, effectiveness, and efficiency. Healthcare institutions have placed emphasis on applying the QI framework to identify and improve healthcare delivery. Despite QI's increasing importance, there is a lack of guidance on preparing, executing, and sustaining QI initiatives in the field of laboratory medicine. This has presented a significant barrier for clinical laboratorians to participate in and lead QI initiatives. This three-part primer series will bridge this knowledge gap by providing a guide for clinical laboratories to implement a QI project that issuccessful and sustainable. In the first article, we introduce the steps needed to prepare a QI project with focus on relevant methodology and tools related to problem identification, stakeholder engagement, root cause analysis (e.g., fishbone diagrams, Pareto charts and process mapping), and SMART aim establishment. Throughout, we describe a clinical vignette of a real QI project completed at our institution focused on serum protein electrophoresis (SPEP) utilization. This primer series is the first of its kind in laboratory medicine and will serve as a useful resource for future engagement of clinical laboratory leaders in QI initiatives.

Turnaround Time of the Hematology Results of Cancer Patients During the COVID-19 Pandemic: An Opportunity to Initiate a Quality Improvement Process

INTRODUCTION

Turnaround time (TAT) is a crucial clinical parameter that reflects the performance of a laboratory especially in the context of oncology and the COVID-19 pandemic. Based on the Lean Six Sigma methodology, we performed a retrospective analysis of the TAT of the complete blood count (CBC) of cancer patients with the aim of reducing this delay in the future.

MATERIALS AND METHODS

Over one month of the COVID-19 pandemic, a retrospective evaluative audit was carried out on the TAT of the CBC in an oncology department. The root causes of failures of the overall analysis process were detected. The initiation of an improvement approach was implemented through the creation of an improvement flowchart and a new request form. The hospital information system (HIS) data were exported to Microsoft Excel® (Microsoft Corporation, Redmond, Washington, United States). Using the collected data, the mean, standard deviation, median, and interquartile range were calculated using IBM SPSS Statistics for Windows, Version 23, (Released 2015; IBM Corp., Armonk, New York, United States). All time intervals were expressed in minutes.

RESULTS

Among 263 intra-laboratory TATs analyzed, the median intra-lab TAT was 56 minutes (interquartile range (IQR): 36-80 minutes). A total of 82% of the analyses were performed in less than 90 minutes with a predominance of the interval 30-59 at 42.9%. The main causes of failures were essentially the lack of time stamping of the samples as well as the lack of real-time communication between the biologists and the clinicians. The proposed improvement model is currently being approved by all practitioners whose main items are as follows: At the clinical department level, distinguish the request forms but also the labels of the samples of the oncology hospital by a particular color, indication of clinical signs and sampling time on the request forms and on the HIS. At the laboratory level, create a specific chain for oncology department samples, alarm notification on the HIS, and rapid telecommunication of results for vital situations.

CONCLUSION

The intra-lab TAT of our study is biologically acceptable. Because our work is limited by the phases outside the control of the laboratory, it should lead to a continuous improvement project.

Utilizing Data Analytics And Business Intelligence Tools In Laboratory Workflow

A business intelligence (BI) tool in a laboratory workflow offers various benefits, including data consolidation, real-time monitoring, process optimization, cost analysis, performance benchmarking (quality indicators), predictive analytics, compliance reporting, and decision support. These tools improve operational efficiency, quality control, inventory management, cost analysis, and clinical decision-making. This write up reveals the workflow process and implementation of BI in a private hospital laboratory. By identifying challenges and overcoming them, laboratories can utilize the power of BI and analytics solutions to accelerate healthcare performance, lower costs, and improve care quality. We used navify (Viewics) as a BI platform which relies on an infinity data warehouse for analytics and dashboards. We applied it for pre-analytic, analytic and post-analytic phases in laboratory. We conclude, digitalization is crucial for innovation and competitiveness, enhancing productivity, efficiency, and flexibility in future laboratories.

Revolutionising Quality Management in the Oral Pathology Laboratory: A Deep Dive Into the Six Sigma Methodology

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.

Sigma metric analysis of quality indicators across the testing process as an effective tool for the evaluation of laboratory performance

Background

Laboratories across the world are successfully using quality indicators (QIs) to monitor their performance. We aimed to analyze the effectiveness of using the peer group comparison and statistical tools such as sigma metrics for periodic evaluation of QIs and identify potential errors in the preanalytical, analytical, and postanalytical phases.

Methods

We evaluated the monthly QIs for 1 year. A total of 11 QIs were evaluated across the three phases of the total testing process, using percentage variance, and sigma metric analysis.

Results

Our study observed that based on sigma metric analysis, the performance was good for all the QIs except for the number of samples with the inappropriate specimen hemolyzed samples, clotted samples, and turnaround time (Sigma value < 3). The percentage variance of QIs in all the phases was plotted in a Pareto chart, which helped us in identifying turnaround time and internal quality control performance are the key areas that contribute to almost 80% of the errors among all the QIs.

Conclusion

Laboratory performance evaluation using QIs and sigma metric analysis helped us in identifying and prioritizing the corrective actions in the key areas of the total testing process.

3D Printing as an Effective Quality Assurance Implementation in Massive-Scale SARS-CoV-2 Testing at a SwabSeq Next-Generation Sequencing Laboratory

Massive-scale SARS-CoV-2 testing using the SwabSeq diagnostic platform came with quality assurance challenges due to the novelty and scale of sequencing-based testing. The SwabSeq platform relies on accurate mapping between specimen identifiers and molecular barcodes to match a result back to a patient specimen. To identify and mitigate mapping errors, we instituted quality control using placement of negative controls within a rack of patient samples. We designed 2-dimensional paper templates to fit over a 96-position rack of specimens with holes to show the control tube placements. We designed and 3-dimensionally printed plastic templates that fit onto 4 racks of patient specimens and provide accurate indications of the correct control tube placements. The final plastic templates dramatically reduced plate mapping errors from 22.55% in January 2021 to less than 1% after implementation and training in January 2021. We show how 3D printing can be a cost-effective quality assurance tool to mitigate human error in the clinical laboratory.

Six Sigma can significantly reduce costs of poor quality of the surgical instruments sterilization process and improve surgeon and operating room personnel satisfaction

Operating room (OR) management is a complex multidimensional activity combining clinical and managerial aspects. This longitudinal observational study aimed to assess the impact of Six-Sigma methodology to optimize surgical instrument sterilization processes. The project was conducted at the operating theatre of our tertiary regional hospital during the period from July 2021 to December 2022. The project was based on the surgical instrument supply chain analysis. We applied the Six Sigma lean methodology by conducting workshops and practical exercises and by improving the surgical instrument process chain, as well as checking stakeholders' satisfaction. The primary outcome was the analysis of Sigma improvement. Through this supply chain passed 314,552 instruments in 2022 and 22 OR processes were regularly assessed. The initial Sigma value was 4.79 ± 1.02σ, and the final one was 5.04 ± 0.85σ (SMD 0.60, 95%CI 0.16-1.04, p = 0.010). The observed improvement was estimated in approximately $19,729 of cost savings. Regarding personnel satisfaction, 150 questionnaires were answered, and the overall score improved from 6.6 ± 2.2 pts to 7.0 ± 1.9 pts (p = 0.013). In our experience the application of the Lean Six Sigma methodology to the process of handling the surgical instruments from/to the OR was cost-effective, significantly decreased the costs of poor quality and increased internal stakeholder satisfaction.

Modelling CD4 reagent usage across a national hierarchal network of laboratories in South Africa

Background

The National Health Laboratory Service is mandated to deliver cost-effective and efficient diagnostic services across South Africa. Their mandate is achieved by a network of laboratories ranging from centralised national laboratories to distant rural facilities.

Objective

This study aimed to establish a model of CD4 reagent utilisation as an independent measure of laboratory efficiency.

Methods

The efficiency percentage was defined as finished goods (number of reportable results) over raw materials (number of reagents supplied) for 47 laboratories in nine provinces (both anonymised) for 2019. The efficiency percentage at national and provincial levels was calculated and compared to the optimal efficiency percentage derived using pre-set assumptions. Comparative laboratory analysis was conducted for the provinces with the best and worst efficiency percentages. The possible linear relationship between the efficiency percentage and call-outs, days lost, referrals, and turn-around time was assessed.

Results

Data are reported for 2 806 799 CD4 tests, with an overall efficiency percentage of 84.5% (optimal of 84.98%). The efficiency percentage varied between 75.7% and 87.7% between provinces, while within the laboratory it ranged from 66.1% to 111.5%. Four laboratories reported an efficiency percentage ranging from 67.8% to 85.7%. No linear correlation was noted between the efficiency percentage, call-outs, days lost, and turn-around time performance.

Conclusion

Reagent efficiency percentage distinguished laboratories into different utilisation levels irrespective of their CD4 service level. This parameter is an additional independent indicator of laboratory performance, with no relationship with any contributing factors tested, that can be implemented across pathology disciplines for monitoring reagent utilisation.

What this study adds

This study provides an objective methodology to assess reagent utilisation as an independent measure of laboratory efficiency. This model could be applied to all routine pathology services.

Development and clinical evaluation of an online automated quality control system for improving laboratory quality management

BACKGROUND

We developed an efficient online automated quality control (AUTO QC) system and tested its feasibility on automatic laboratory assembly lines.

METHODS

AUTO QC is based on developed quality control software (Smart QC) and designed adaptable consumables before. We applied the system to two assembly lines in our laboratory. Using third-party quality control samples, we evaluated the impact of the online AUTO QC system on out-of-control rate, biosecurity risk, turnaround time (TAT) and cost.

RESULTS

AUTO QC significantly decreased the occurrence rate of the Westgard quality control rules 1_3S/2_2S/R_4s and 1_2S, representing out-of-control and warning, respectively. The out-of-control rates were reduced by 58%, and the potential biosecurity risk of the samples decreased by 90%. The AUTO QC implementation also reduced the median TAT (by 7 min), the number of full-time employees and the cost of the quality control samples (by 45%).

CONCLUSIONS

The total laboratory AUTO QC system can improve the quality and stability of QC testing and reduce cost.

Lean and Six Sigma as continuous quality improvement frameworks in the clinical diagnostic laboratory

Processes to enhance customer-related services in healthcare organizations are complex and it can be difficult to achieve efficient patient-focused services. Laboratories make an integral part of the healthcare service industry where healthcare providers deal with critical patient results. Errors in these processes may cost a human life, create a negative impact on an organization's reputation, cause revenue loss, and open doors for expensive lawsuits. To overcome these complexities, healthcare organizations must implement an approach that helps healthcare service providers to reduce waste, variation, and work imbalance in the service processes. Lean and Six Sigma are used as continuous process improvement frameworks in laboratory medicine. Six Sigma uses an approach that involves problem-solving, continuous improvement and quantitative statistical process control. Six Sigma is a technique based on the DMAIC process (Define, Measure, Analyze, Improve, and Control) to improve quality performance. Application of DMAIC in a healthcare organization provides guidance on how to handle quality that is directed toward patient satisfaction in a healthcare service industry. The Lean process is a technique for process management in which waste reduction is the primary purpose; this is accomplished by implementing waste mitigation practices and methodologies for quality improvement. Overall, this article outlines the frameworks for continuous quality and process improvement in healthcare organizations, with a focus on the impacts of Lean and Six Sigma on the performance and quality service delivery system in clinical laboratories. It also examines the role of utilization management and challenges that impact the implementation of Lean and Six Sigma in clinical laboratories.

Prioritization of critical success factors for sustainable Lean Six Sigma implementation in Indian healthcare organizations using best-worst-method

Purpose

Recent years have seen an increased demand for healthcare services, presenting a need to improve service quality through the deployment of sustainable Lean Six Sigma (LSS). This study aims to identify critical success factors (CSFs) of sustainable LSS and prioritize them based on their intensity of importance for the effective implementation of sustainable LSS in the healthcare environment.

Design/methodology/approach

The present study identified 33 leading CSFs through a comprehensive literature review and expert experience and classified them into six major categories based on organizational functions. The primacy of these CSFs is established using the best-worst-method (BWM) approach. The significant advantage of this approach is that the decision-maker identifies both the best and worst criteria among alternatives prior to pairwise comparisons, leading to fewer pairwise comparisons and saving time, energy and resources. It also provides more reliable and consistent rankings.

Findings

The findings of the present study highlight the economic and managerial (E&M) CSFs as the most significant CSFs among the major category criteria of sustainable LSS-CSFs, followed by organizational (O), knowledge and learning (K&L), technological (T), social and environmental (S&E), and external factors (EF). Similarly, management involvement and leadership to implement sustainable LSS (E&M1), structured LSS deployment training and education (K&L2), and availability of required resources and their efficient utilization (O2) are ranked as the topmost CSFs among sub-category criteria of sustainable LSS-CSFs.

Practical implications

The prioritization of sustainable LSS-CSFs determined in this study can provide healthcare managers, researchers and decision-makers with a better understanding of the influence on effective deployment of sustainable LSS, resulting in improved service quality in hospitals.

Originality/value

This paper is an original contribution to the analysis of CSFs in an Indian healthcare institute, utilizing the BMW method for ranking the sustainable LSS-CSFs. The advantage of utilizing and distinguishing the performance of this approach compared to other MCDA approaches in terms of (1) least pairwise comparison and violation, (2) consistency (3) slightest deviation and (4) conformity.

"Six Sigma" standard as a level of quality of biochemical laboratories

The principal role of biochemical laboratories is responsibility for reliable, reproducible, accurate, timely, and accurately interpreted analysis results that help in making clinical decisions, while ensuring the desired clinical outcomes. To achieve this goal, the laboratory should introduce and maintain quality control in all phases of work. The importance of applying the Six SIGMA quality model has been analyzed in a large number of scientific studies. The purpose of this review is to highlight the importance of using six SIGMA metrics in biochemical laboratories and the current application of six SIGMA metrics in all laboratory work procedures. It has been shown that the six SIGMA model can be very useful in improving all phases of laboratory work, as well as that a detailed assessment of all procedures of the phases of work and improvement of the laboratory's quality control system is crucial for the laboratory to have the highest level of six SIGMA. Clinical laboratories should use SIGMA metrics to monitor their performance, as it makes it easier to identify gaps in their performance, thereby improving their efficiency and patient safety. Medical laboratory quality managers should provide a systematic methodology for analyzing and correcting quality assurance systems to achieve Six SIGMA quality-level standards.

Externalities of Lean Implementation in Medical Laboratories. Process Optimization vs. Adaptation and Flexibility for the Future

Important in testing services in medical laboratories is the creation of a flexible balance between quality-response time and minimizing the cost of the service. Beyond the different Lean methods implemented so far in the medical sector, each company can adapt the model according to its needs, each company has its own specifics and organizational culture, and Lean implementation will have a unique approach. Therefore, this paper aims to identify the concerns of specialists and laboratory medical services sector initiatives in optimizing medical services by implementing the Lean Six Sigma method in its various variants: a comparative analysis of the implemented models, with emphasis on measuring externalities and delimiting trends in reforming/modernizing the method, a comprehensive approach to the impact of this method implementation, and an analysis of available databases in order to underline the deficit and information asymmetry. The results highlighted that in the case of clinical laboratories, the Lean Six Sigma method is conducive to a reduction of cases of diagnostic errors and saves time but also faces challenges and employees' resistance in implementation.

What factors are associated with improvements in productivity in clinical laboratories in the Asia Pacific Region?

INTRODUCTION

Clinical laboratories usually have a quality management system such as ISO 15189, which provides a framework for quality and competence to perform medical testing and internal systems such as audit and nonconformance to ensure consistent processes. However, organizations need to have access to internal procedures and external competitors' performance to improve their operations. These are often seen as commercial or areas where it is difficult to agree on an acceptable goal.

METHOD

In 2019, 1158 laboratories from 17 countries/regions in the Asia Pacific Region answered the survey, including 399 Chinese sites. The survey collected information on quality, turnaround time and productivity.

RESULTS

Median productivity for laboratories in the Asia Pacific Region not including Chinese sites was 25 samples/FTE/day for small laboratories (workload: <250 samples/day), 100 for medium-sized laboratories (workload: 251-1000 samples/day) and 220 for large laboratories (workload: >1001 samples/day). The parameters associated with increased productivity in some laboratories were automation, middleware, Lean Six Sigma quality improvement activities and International Accreditation.

CONCLUSION

This survey provides evidence of an association of quality improvement activities on laboratory productivity. There are differences in the effect of these activities in Chinese and non-Chinese laboratories in the Asia Pacific Region. The survey confirmed that the implementation of automation is associated with increased median productivity in all sites. Implementation of Lean Six Sigma and International Accreditation is associated with increased productivity in large laboratories.

Preventing dispensing errors through the utilization of lean six sigma and failure model and effect analysis: A prospective exploratory study in China

AIMS

To utilize lean six sigma (LSS) and failure model and effect analysis (FMEA) to prevent dispensing errors in a Chinese teaching hospital.

METHODS

Medication errors (MEs) reported to the China Core Group of the international network for the rational use of drugs (INRUD) by pharmacists at the hospital were collected. Following LSS methodology, the data analysis was structured according to define, measure, analyse, improve, and control (DMAIC) phases, and typical LSS tools (Pareto diagrams, brainstorming sessions) were used to determine the risk factors leading to dispensing errors. FMEA was applied to generate the risk priority numbers (RPNs) of MEs events, and key medications targeted for error prevention strategies were identified through quantitative analysis of the impacts of failure. Finally, corrective measures to prevent MEs were implemented and monitored for efficacy.

RESULTS

Before the implementation of this programme, a total of 603 cases of dispensing errors were reported from the Year 1 to Year 6, reaching an average rate of incidence of 0.33 cases per 10 000 medication orders delivered, and no difference was found between these years (P = .9424). There was also no difference as location, error type, contributing factors, cause classification were considered. We then determined the real cause behind dispensing errors, and a total of 67 medications were targeted for specific error prevention strategies. One year after intervention, progress had been achieved in the following aspects: the incidence rate of dispensing errors was significantly decreased compared with the previous years (0.19, P = .007). Simultaneously, the incidence rate of dispensing errors occurred in outpatient pharmacy (0.04, P = .0008), with junior pharmacists (0.15, P = .0258), with LASA medications (0.06, P = .0319), as well as with memory-based errors were significantly decreased (0.03, P = .0191).

CONCLUSION

The combination of LSS and the FMEA tool can be an efficient approach for helping reduce MEs in pharmacy dispensing.

Utilizing process improvement strategies to generate clinic templates and improve patient flow in pediatric otolaryngology

OBJECTIVES

To examine outcomes from process improvement strategies aimed to: 1) develop computer generated physician clinic templates using captured and historic clinical data, and, 2) introduce said new template designs while maintaining historic daily patient volumes.

METHODS

An Institutional Review Board approved retrospective review of time stamped data collection in a tertiary facility pediatric otolaryngology clinic.

RESULTS

A discrete-event simulation was built from timestamps associated with clinic interaction milestones. The data were analyzed to develop standard clinic templates with the goal to reduce patient overall visit length by 10%. A total of 12,052 clinic visits were analyzed, 8,045 before (avg. of 62.9 visits/day) and 4,007 after (avg. of 65.7 visits/day) template standardization. The change led to a 10.5% (5.5 min, p < 0.001) decrease in total clinic visit time from 52.3 ± 25.9 min to 46.8 ± 25.0 min. This data extrapolated over a year is estimated to save 1,567 clinic hours. Secondarily, it was found that patient experience was not affected as a result of this change.

CONCLUSION

Discrete-event simulation, using the principles of process improvement, is effective in guiding clinic operational redesign. This quality improvement project decreased the average length of clinic visit by 10% with no impact on historic high clinic volumes. Patient flow can improve in high volume pediatric otolaryngology practices by using process improvement strategies and discrete-event simulations to create standardized provider templates. Theoretically, this strategy can lead to improved patient and physician experiences along with an increase in patient visits over time.

Evaluation of Sigma metric approach for monitoring the performance of automated analyzers in hematology unit of Alexandria Main University Hospital

INTRODUCTION

Sigma metric offers a quantitative framework for evaluating process performance in clinical laboratories. This study aimed to evaluate the analytical performance of automated analyzers in hematology unit of Alexandria Main University Hospital using the sigma metric approach.

MATERIALS AND METHODS

Quality control data were collected for 6 months, and sigma value was calculated from hematology analyzers SYSMEX (XN 1000, XT 1800i), ADVIA (2120i, 2120), and coagulation analyzers SYSMEX CA 1500 (3610, 6336).

RESULTS

For the normal control level, satisfactory mean sigma value ≥3 was observed for all of the studied parameters by all analyzers. For the high control level, red blood cell count by ADVIA 2120, and hematocrit by ADVIA (2120i and 2120) performed poorly with a mean sigma value <3. For the low control level, red blood cell count by ADVIA (2120i and 2120), hemoglobin by ADVIA 2120, hematocrit by ADVIA (2120i and 2120) and SYSMEX XN 1000, platelet count by the SYSMEX XT 1800i also performed poorly with a mean sigma value <3. Satisfactory mean sigma value of ≥3 was observed for prothrombin time and activated partial thromboplastin time for both normal and pathological control levels and analyzers.

CONCLUSION

Sigma metrics can be used as a guide to make QC strategy and plan QC frequency and can facilitate the comparison of the same assay performance across multiple systems. Harmonization for TEa source is recommended to standardize sigma value calculation.

Improved Sample Quality and Decreased Turnaround Time When Using Plasma Blood Collection Tubes with a Mechanical Separator in a Large University Hospital

BACKGROUND

Serum is commonly used for clinical chemistry testing but many conditions can affect the clotting process, leading to poor sample quality and impaired workflow. With serum gel tubes, we found a high proportion of sample probe aspiration errors on our Beckman AU5800 analyzers. We decided to implement the BD Barricor™ plasma tubes, and we validated an off-specification centrifugation scheme and verified that results obtained for 65 chemistry and immunochemistry tests were comparable to those obtained in serum gel tubes. Finally, we evaluated the impact of this new tube on sample error rate and laboratory turnaround time.

METHODS

To validate centrifugation settings, 50 paired samples were collected in Barricor tubes and centrifuged at 1912 × g for 10 min or 5 min (off-specification). To compare serum gel tubes with Barricor plasma tubes, 119 paired samples were collected from volunteers and results were analyzed using weighed Deming regression. Finally, the proportion of aspiration errors and laboratory TAT for potassium were measured before and after implementing Barricor tubes.

RESULTS

Barricor tubes showed clinically acceptable equivalence to serum gel tubes for the studied analytes, and the off-specification centrifugation scheme did not affect the results. Implementing Barricor tubes improved the laboratory workflow by decreasing the aspiration error rates (2.01% to 0.77%, P < 0.001) and lowering hemolysis (P < 0.001). The laboratory TAT for potassium were also significantly lowered (P < 0.001).

CONCLUSION

Use of Barricor tubes instead of serum gel tubes leads to better sample quality, shorter more reproducible laboratory TAT, and decreases costs associated with error management.

Improving turnaround time of molecular diagnosis of Middle East respiratory syndrome coronavirus in a hospital in Saudi Arabia

Background

There have been 2562 laboratory-confirmed cases of Middle East respiratory syndrome coronavirus (MERS-CoV) in 27 countries, with a case fatality rate of 34.5%. Data on the turnaround time (TAT) are lacking. We report TAT for MERS-CoV samples over time.

Methods

This is a monocentric study and the TAT for the reporting of 2664 MERS-CoV polymerase chain reaction (PCR) results were calculated in hours from the time of the receipt of respiratory samples to the reporting of the results.

Results

The mean TAT±standard deviation was significantly lower in 2018 compared with previous years (19.25±13.8). The percentage of samples processed within 24 h increased from 42.3% to 73.8% in 2015 and 2018, respectively (p<0.0001). The mean TAT was 19.2 h in 2018 and was significantly lower than previous years.

Conclusions

The TAT for the MERS-CoV results decreased during the study period. Timely reporting of MERS-CoV PCR results may aid in further enhancing infection control measures.

Categorising specimen referral delays for CD4 testing: How inter-laboratory distances and travel times impact turn-around time across a national laboratory service in South Africa

Background

The South African National Health Laboratory Service provides laboratory services for public sector health facilities, utilising a tiered laboratory model to refer samples for CD4 testing from 255 source laboratories into 43 testing laboratories.

Objective

The aim of this study was to determine the impact of distance on inter-laboratory referral time for public sector testing in South Africa in 2018.

Methods

A retrospective cross-sectional study design analysed CD4 testing inter-laboratory turn-around time (TAT) data for 2018, that is laboratory-to-laboratory TAT from registration at the source to referral receipt at the testing laboratory. Google Maps was used to calculate inter-laboratory distances and travel times. Distances were categorised into four buckets, with the median and 75th percentile reported. Wilcoxon scores were used to assess significant differences in laboratory-to-laboratory TAT across the four distance categories.

Results

CD4 referrals from off-site source laboratories comprised 49% (n = 1 390 510) of national reporting. A positively skewed distribution of laboratory-to-laboratory TAT was noted, with a median travel time of 11 h (interquartile range: 7–17), within the stipulated 12 h target. Inter-laboratory distance categories of less than 100 km, 101–200 km, 201–300 km and more than 300 km (p < 0.0001) had 75th percentiles of 8 h, 17 h, 14 h and 27 h.

Conclusion

Variability in inter-laboratory TAT was noted for all inter-laboratory distances, especially those exceeding 300 km. The correlation between distance and laboratory-to-laboratory TAT suggests that interventions are required for distant laboratories.

Interpol review of forensic science management literature 2016-2019

This paper reviews and summarizes the forensic management literature from late 2016 to late 2019, covering laboratory decision making, business strategy, and industry identity and transparency. The review papers are also available at the Interpol website at: https://www.interpol.int/content/download/14458/file/Interpol%20Review%20Papers%202019.pdf.

Workflow optimization in a clinical laboratory using Lean management principles in the pre-analytical phase

Background

The application of the Lean methodology in clinical laboratories can improve workflow and user satisfaction through the efficient delivery of analytical results. The purpose of this study was to optimise delivery times of the test results at a clinical laboratory, using Lean management principles in the pre-analytical phase.

Methods

A prospective study with a quasi-experimental design was implemented. Staff functions were restructured and sample flows were modified. Delivery times of clinical results (glucose and haematocrit; 6648 data) from the Medicine and Adult Emergency services for years 2017 and 2018 were compared.

Results

A reduction (p < 0.05) in turnaround times in the delivery of glucose test results at the adult emergency service was observed (84 to 73 min, 13%, pre and post). In addition, there was a non-significant reduction in the turnaround times for glucose (Medicine) and haematocrit in both services. In the analytical and post-analytical phase (not intervened), an increase in turnaround times was observed in some cases.

Conclusions

Other studies have indicated that the application of the Lean methodology in clinical laboratories improves workflow, increasing effectiveness and efficiency. This study showed an improvement in the delivery time of test results (glucose - Emergency), giving rise to a culture of cooperation and continuous improvement. It would, however, be essential to address the management model integrating the analytical and post-analytical phases.

Adjusting Quality Control Chart Limits for WBC, RBC, Hb, and PLT Counts to Reduce Daily Control Risks in Hospital Laboratory

BACKGROUND

To continuously improve medical quality and provide clinicians with more accurate blood test reports, this study collected blood quality control data in 2017 from a medical examination laboratory in a teaching level hospital located in Taoyuan City, Taiwan.

MATERIAL AND METHODS

The quality control data were arranged and analyzed from daily complete blood count (CBC), including white blood cells (WBC), red blood cells (RBC), hemoglobin (Hb), and platelets (PLT) recorded by a laboratory blood analyzer. Using the empirical Bayesian method, we estimated the variation of concentrations of the last and current batches to establish a novel control chart with adjusted upper and lower limits for the current batch, and then compared results with the traditional Shewhart method. The average run length (ARL) and sensitivity of the empirical Bayesian method were explored.

RESULTS

The study found that ARL showed a qualified capability for the four blood routine tests when using the empirical Bayesian method. Compared to the Levey-Jennings control chart, the novel control chart presents an alert earlier when a deviation occurs and shows a fake alert later when there is no deviation.

CONCLUSION

The parallel tests showed that the longer the time is, the better the test's proficiency. We concluded that the empirical Bayesian method could be applied effectively to improve the capability of daily control in CBC laboratory tests.

Evaluation of Biomedical Laboratory Performance Optimisation using the DEA Method

Introduction

The Slovenian Resolution on the National Healthcare Plan notes that the country’s medical laboratory activities are fragmented, which may result in cost-inefficiency and a reduction in the quality of the services provided. Defining the efficiency of laboratory service providers can therefore help us to pursue the objectives of the Resolution, i.e. to consolidate and integrate laboratory activities.

Methods

Using the DEA method, we conducted an analysis of the efficiency of 20 biomedical laboratories in Slovenia, and made a comparison with a “virtual” laboratory, i.e. a merger of laboratories within a selected organisational unit. By testing different DEA models, we sought to determine whether the use of different input variables caused significant differences in the laboratories’ efficiency scores.

Results

The research results show that inefficiency resulting from the size of the units is 1.5 times greater than process inefficiency. Using a non-parametric Wilcoxon Signed Rank test, we determined, at a risk level of 0.05, that there was no difference between the efficiency results when using two different technical efficiency DEA models. When evaluating the virtually merged laboratory, we determined that, under all three models, the virtual laboratory achieved 100% VRS efficiency. However, when the CRS methodology was used, the laboratory showed a certain degree of scale inefficiency.

Conclusions

When evaluating merger of medical laboratories we note that the DEA method is methodologically suitable for evaluating the effects of health policy implementation, and is an appropriate tool for identifying where the field of laboratory medicine might be further developed and improved.

Reducing Errors in Radiology Specimen Labeling Through Use of a Two-person Check

Improper specimen labeling of biopsy samples can cause substantial harm to patients through diagnostic delays, administration of inappropriate treatments, and can result in a loss of trust in the healthcare system. Specimen labeling errors are considered a relevant safety metric in our department and tracked on a rolling basis. One imaging section was noted to have nearly completely eliminated these errors through implementation of a 2-person check prior to submission to pathology. The purpose of this intervention was to identify the causes of continued specimen labeling errors in radiology and to standardize the specimen labeling workflow across the department of radiology to include the best practice identified in breast imaging utilizing a 2-person check. Preintervention, 31 specimen labeling errors were reported by the procedural staff over a period of 149 weeks resulting in an error rate of 0.21 errors per week. Postintervention, 3 specimen labeling errors occurred in the next 46 weeks resulting in a rate of 0.07 errors per week, a 68.8% decrease in the specimen labeling error rate. This quality improvement project highlights the process flaws which contribute to medical errors and demonstrates a potential pathway to try and reduce these errors and patient harm without significant investment in capital or new technology.

The importance of intra- and inter-institutional networks for capacity building in severe acute respiratory syndrome coronavirus 2 reverse transcription polymerase chain reaction services: experience from an oncology centre in eastern India

High-throughput, accurate, cost-effective and rapid testing for severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) is the need of the hour in face of the global coronavirus disease pandemic. This target is achievable, within a relatively short time through capacity building of reverse transcription polymerase chain reaction (RT-PCR) tests by utilising the strengths of intra and inter institutional networks. These networks act as force multiplier for vital resources which are required for capacity building, namely, leadership, expertise, equipment, space, infection control inputs and human resources. In this article, we report the experience of capacity building for delivery of RT-PCR tests for SARS CoV-2 from a cancer hospital in Eastern India. The relevance, mode of operation and value addition of this essential public health service are discussed in the context of inter departmental collaboration and interaction with other institutes through the existing diagnostic, surveillance and infection control networks. This networking model for service development and delivery could be used by other centres.

Benchmarking the Lean Six Sigma performance measures: a balanced score card approach

Purpose

The purpose of this paper is to develop the balance score card (BSC) approach based Lean Six Sigma (LSS) performance measurement system and investigate the critical measures currently practiced by Indian manufacturing organizations.

Design/methodology/approach

This study offers insights of LSS performance measurement from manufacturing industry. Initially, the BSC-based framework is developed to recognize the adoption of LSS performance measures. Then, the framework is applied to nine Indian manufacturing organizations to assess the LSS performance measure practice.

Findings

The BSC-based framework of LSS performance evaluation for manufacturing industry is formulated. Then, adoption of these LSS performance measures is investigated with nine Indian manufacturing organizations. The result indicates significant variability in terms of practicing level of LSS measures. However, the majority of organizations are more sensitive to the customer perspectives.

Practical implications

This study reveals a background as to why the performance measurement is required for the success of LSS and for providing practical guidelines for designing performance metrics. The framework interrelates and captures various LSS perspectives and indicator measures, and furnishes a comprehensive outlook of the organization for strategic analysis. This study provides BSC-based template for performing the benchmarking study. This analysis may serve as a reference point for manufacturing organization to determine their system weaknesses, and assist them to concentrate on their most vital and suitable criteria and objectives. However, the analysis contributes to the knowledge on LSS performance measurement system and catches differences in theory and practice, paving the approach to newer research.

Originality/value

This study renders an industry-oriented LSS performance measurement practical approach and suggests the easily adopted vital performance measures for different manufacturing organizations.

An Overview of the Performance Improvement Initiatives by the Ministry of Health in the Kingdom of Saudi Arabia

Saudi Arabia's Ministry of Health (MOH) use corporate performance improvement methodologies to develop and implement performance improvement initiatives designed to continue building on the Ministry's vision of transforming hospital operations and instituting a culture of quality and performance focused on the "patient first" principle. We evaluated the feasibility of setting up a performance improvement unit (PIU) within the MOH to apply the principles of Lean Six Sigma and to change management methodologies. The MOH collaborated with external consultants to implement PIU initiatives in 4 steps: PIU Setup, PIU Capability Building, High-Impact Project Implementation, and Project Sustainability and Knowledge Transfer. PIU units were setup across the 13 provinces over 90 days. The process included the promotion of knowledge sharing to strengthen the skill set of Saudi health care professionals and develop local performance improvement champions within the MOH who could lead, implement, and sustain future projects. Implementation was a challenge; though, early results from the High-Impact Project Implementation phase were encouraging. However, the sustainability of PIU interventions was poor, with performance improvement processes returning to baseline levels within 9 months. This case study shows that PIU implementation is a feasible approach for improving health care delivery in Saudi Arabia. Poor sustainability despite initial success highlights the need to further improve the engagement, incentivization, and training of team leaders and members to achieve long-term success with the program.

Lean six sigma methodologies improve clinical laboratory efficiency and reduce turnaround times

BACKGROUND

Organizing work flow is a major task of laboratory management. Recently, clinical laboratories have started to adopt methodologies such as Lean Six Sigma and some successful implementations have been reported. This study used Lean Six Sigma to simplify the laboratory work process and decrease the turnaround time by eliminating non-value-adding steps.

METHODS

The five-stage Six Sigma system known as define, measure, analyze, improve, and control (DMAIC) is used to identify and solve problems. The laboratory turnaround time for individual tests, total delay time in the sample reception area, and percentage of steps involving risks of medical errors and biological hazards in the overall process are measured.

RESULTS

The pre-analytical process in the reception area was improved by eliminating 3 h and 22.5 min of non-value-adding work. Turnaround time also improved for stat samples from 68 to 59 min after applying Lean. Steps prone to medical errors and posing potential biological hazards to receptionists were reduced from 30% to 3%.

CONCLUSION

Successful implementation of Lean Six Sigma significantly improved all of the selected performance metrics. This quality-improvement methodology has the potential to significantly improve clinical laboratories.