The value of Sigma-metrics in laboratory medicine.

While Six Sigma is used in different disciplines to improve quality, Tony Badric and Elvar Theodorsson in a recent paper in CCLM have questioned Six Sigma application in medical laboratory concluding Six Sigma has provided no value to medical laboratory. In addition, the authors have expanded their criticism to Total Analytical Error (TAE) model and statistical quality control. To address their arguments, we have explained the basics of TAE model and Six Sigma and have shown the value of Six Sigma to medical laboratory.

Reducing catheter-related bloodstream infections using Lean Six Sigma methodology.

BACKGROUND: Central venous catheters (CVC) are used for dialysis in end-stage renal disease patients, presenting a significant risk for Catheter-Related Bloodstream Infections (CRBSI). While Lean Six Sigma has been effective in reducing CRBSI, its efficacy outside intensive care units (ICU) remains less explored. This study aims to evaluate the effectiveness of Lean Six Sigma in mitigating CRBSI risks among non-ICU hemodialysis patients. METHODS: The study was conducted in a nephrology department, focusing on patients undergoing hemodialysis with temporary CVC from February to December 2021. The Lean Six Sigma method, using Define-Measure-Analyze-Improve-Control (DMAIC) methodology, was implemented in 2022 to reduce CRBSI incidence. The 2021 CRBSI rate served as the benchmark, with a goal to reduce it by the end of 2022. Value-stream mapping, Fishbone Diagrams, and Root Cause Analysis identified potential CRBSI causes. After implementing targeted improvements, CRBSI rates before and after the intervention were compared. RESULTS: The Lean Six Sigma method significantly decreased CRBSI incidence from 12.79 to 2.32 per 1,000 catheter-days following the implementation of targeted interventions ([Formula: see text]=4.60, P = 0.05). This improvement was observed comparing February-December 2021 with January-December 2022. CONCLUSION: The findings demonstrate the effectiveness of the Lean Six Sigma method in non-ICU settings, suggesting broader applicability in hemodialysis patient care.

Use of the DMAIC Lean Six Sigma quality improvement framework to improve beta-lactam antibiotic adequacy in the critically ill.

Beta-lactam antibiotics are widely used in the intensive care unit due to their favorable effectiveness and safety profiles. Beta-lactams given to patients with sepsis must be delivered as soon as possible after infection recognition (early), treat the suspected organism (appropriate), and be administered at a dose that eradicates the infection (adequate). Early and appropriate antibiotic delivery occurs in >90% of patients, but less than half of patients with sepsis achieve adequate antibiotic exposure. This project aimed to address this quality gap and improve beta-lactam adequacy using the Define, Measure, Analyze, Improve, and Control Lean Six Sigma quality improvement framework. A multidisciplinary steering committee was formed, which completed a stakeholder analysis to define the gap in practice. An Ishikawa cause and effect (Fishbone) diagram was used to identify the root causes and an impact/effort grid facilitated prioritization of interventions. An intervention that included bundled education with the use of therapeutic drug monitoring (TDM; i.e. drug-level testing) was projected to have the highest impact relative to the amount of effort and selected to address beta-lactam inadequacy in the critically ill. The education and TDM intervention were deployed through a Plan, Do, Study, Act cycle. In the 3 months after "go-live," 54 episodes of beta-lactam TDM occurred in 41 unique intensive care unit patients. The primary quality metric of beta-lactam adequacy was achieved in 94% of individuals after the intervention. Ninety-four percent of clinicians gauged the education provided as sufficient. The primary counterbalance of antimicrobial days of therapy, a core antimicrobial stewardship metric, was unchanged over time (favorable result; P = .73). Application of the Define, Measure, Analyze, Improve, and Control Lean Six Sigma quality improvement framework effectively improved beta-lactam adequacy in critically ill patients. The approach taken in this quality improvement project is widely generalizable to other drugs, drug classes, or settings to increase the adequacy of drug exposure.

Innovative UPLC technique for concurrent quantification of etofenamate and benzyl nicotinate in the presence of methylparaben and benzyl alcohol in their topical cream: Greens, white, and Six Sigma methodologies.

The efficacious treatment of muscle and joint pain relies heavily on etofenamate (ETO) and benzyl nicotinate (BN), which possess robust anti-inflammatory and pain-relieving properties when paired with methylparaben (MP) or benzyl alcohol (BA). In this study, we have established and validated innovative RP-UPLC methods for assessing ETO and BN in the presence of MP or BA in their dosage forms, employing eight green tools to evaluate their eco-friendliness and effectiveness. Reversed phase-ultra-performance liquid chromatography (RP-UPLC) technique employs a flow rate of 0.3 mL/min on Waters Acquity UPLC BEH Column (C18, 1.7 µm, 100 mm × 2.1 mm), detection at 254 nm using a photo diode array (PDA) detector and mobile phase of 0.05 M KH2PO4 buffer, acetonitrile, and methanol (50:15:35, v/v/v) adjusted pH 6.0 with 0.2% triethylamine. For ETO, BN, MP, and BA, the calibration curves were linear and ranged from 0.005 to 1.0, from 0.001 to 0.2, from 0.002 to 0.08, and from 0.0001 to 0.1 mg/mL, respectively. The correlation value was 0.9999, and the accuracy findings ranged from 98.81% to 100.56%. Consequently, the methodology has been successfully implemented in assay testing for the pharmaceuticals in the presence of the MP or BA, demonstrating the high selectivity of these approaches. The present study presents the Blue Applicability Grade Index (BAGI), an innovative approach that complements green metrics in practical white analytical chemistry. According to the International Council for Harmonisation (ICH) criteria, the procedures were effectively validated.

Applying the six-sigma methodology to determine the limits of quality control (QC) tests for a specific linear accelerator.

PURPOSE: We aimed to show the framework of the six-sigma methodology (SSM) that can be used to determine the limits of QC tests for the linear accelerator (Linac). Limits for QC tests are individually determined using the SSM. METHODS AND MATERIALS: The SSM is based on the define-measure-analyze-improve-control (DMAIC) stages to improve the process. In the "define" stage, the limits of QC tests were determined. In the "measure" stage, a retrospective collection of daily QC data using a Machine Performance Check platform was performed from January 2020 to December 2022. In the "analyze" stage, the process of determining the limits was proposed using statistical analyses and process capability indices. In the "improve" stage, the capability index was used to calculate the action limits. The tolerance limit was established using the larger one of the control limits in the individual control chart (I-chart). In the "control" stage, daily QC data were collected prospectively from January 2023 to May 2023 to monitor the effect of action limits and tolerance limits. RESULTS: A total of 798 sets of QC data including beam, isocenter, collimation, couch, and gantry tests were collected and analyzed. The Collimation Rotation offset test had the min-Cp, min-Cpk, min-Pp, and min-Ppk at 2.53, 1.99, 1.59, and 1.25, respectively. The Couch Rtn test had the max-Cp, max-Cpk, max-Pp, and max-Ppk at 31.5, 29.9, 23.4, and 22.2, respectively. There are three QC tests with higher action limits than the original tolerance. Some data on the I-chart of the beam output change, isocenter KV offset, and jaw X1 exceeded the lower tolerance and action limit, which indicated that a system deviation occurred and reminded the physicist to take action to improve the process. CONCLUSIONS: The SSM is an excellent framework to use in determining the limits of QC tests. The process capability index is an important parameter that provides quantitative information on determining the limits of QC tests.

Optimizing workflow of urgent stroke endovascular intervention: A focused lean six sigma project.

INTRODUCTION: Urgent endovascular intervention is currently accepted as the primary and critical therapeutic approach to patients whose acute ischemic stroke results from a large arterial occlusion (LAO). In this context, one of the quality metrics most widely applied to the assessment of emergency systems performance is the "door-to-puncture" (D-P) time. We undertook a project to identify the subinterval of the D-P metric causing the most impact on workflow delays and created a narrowly focused project on improving such subinterval. METHODS: Using the DMAIC (i.e., define, measure, analyze, improve and control) approach, we retrospectively reviewed our quality stroke data for calendar year (CY) 2021 (i.e., baseline population), completed a statistical process control assessment, defined the various subintervals of the D-P interval, and completed a Pareto analysis of their duration and their proportional contribution to the D-P interval. We retooled our workflow based on these analyses and analyzed the data resulting from its implementation between May and December 2022 (i.e., outcome population). RESULTS: The baseline population included 87 patients (44 men; mean age = 67.2 years). Their D-P process was uncontrolled, and times varied between 35-235 minutes (Mean = 97; SD = 38.40). Their door to angiography arrival (D-AA) subinterval was significantly slower than their arrival to puncture (AA-P) (73.4 v. 23.5 minutes; p < 0.01), accounted for 73% of the average length of the D-P interval. The group page activation to angiography arrival (GP-AA) subinterval accounted for 41.5% of the entire D-AA duration, making it the target of our project. The outcome population originally consisted of 38 patients (15 men; mean age = 70.3 years). Their D-P process was controlled, its times varying between 43-177 minutes (Mean = 85.8; SD = 34.46), but not significantly difference than the baseline population (p = 0.127). Their target subinterval GP-AA varied between 0-37 minutes and was significantly improved from the baseline population (Mean = 13.21 v. 29.68; p < 0.001). CONCLUSIONS: It seems feasible and reasonable to analyze the subinterval components of complex quality metrics such as the D-P time and carry out more focused quality improvement projects. Care must be exercised when interpreting the impact on overall system performance, due to unexpected variations within interdependent subprocesses. The application of a robust and comprehensive LSS continuous quality improvement process in any CSC will have to include individualized focused projects that simultaneously control the different components of overall system performance.

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.

Implementing patient safety and quality improvement in dermatology. Part 2: Quality improvement science.

Quality improvement (QI) in medicine is reliant on a team-based approach and an understanding of core QI principles. Part 2 of this continuing medical education series outlines the steps of performing a QI project, from identifying QI opportunities, to carrying out successive Plan-Do-Study-Act cycles, to hard-wiring improvements into the system. QI frameworks will be explored and readers will understand how to interpret basic QI data.

Investigating the quality of hemovigilance process using the first two steps of Six Sigma model: a cross-sectional study.

BACKGROUND AND PURPOSE: Hemovigilance is a set of monitoring methods that covers the blood transfusion chain, from collecting blood and blood products to monitoring the blood recipients. To this end, any error in this process can have serious and irreparable consequences for patients. The present study aimed to investigate the quality of hemovigilance process in Iran, using the first two steps of Six Sigma model. METHODS: This was a quantitative cross-sectional study that was conducted over 6 months (from August 20, 2021, to February 20, 2022) at Afzalipour Hospital in Iran, using the first two steps of Six Sigma model. The study population comprised of all inpatients who needed blood or blood product transfusion in various departments of Afzalipour Hospital, among whom 477 patients were selected via stratified sampling in three shifts (morning, evening, and night). The datasheet was used to record errors in the three shifts. This research was conducted, using the DMAIC cycle's "define" and "measure" steps. RESULTS: In the define step, the hemovigilance process at Afzalipour Hospital was divided into two categories of normal process and emergency process. Each of these processes consists of several sub-processes, including "phlebotomy," "requesting blood and blood products from the department," "preparation of application by the blood bank," " sending a request from the blood bank to the blood transfusion center," "transfusing blood and blood products," and "returning the blood and blood products to the blood bank and waste disposal." In the measure step, the quality of hemovigilance process was evaluated based on sub-processes and labels at morning, evening and night shifts. The sub-process of sending a request from the blood bank to the blood transfusion center had the highest error rate with a sigma level of 1.5. Also, the evening and night shifts had a sigma level of 1.875, and the clinical and registration labels had a sigma level of 1.875. The overall sigma level of hemovigilance process was calculated to be 2. CONCLUSION: The results of this study showed that the quality of hemovigilance process at Afzalipour Hospital was poor. By employing the first two steps of Six Sigma method, we identified the existing errors in the hemovigilance process of Afzalipour hospital in order to assist hospital managers to take the necessary measures to improve this process.

Six Sigma in blood transfusion services: A dream too big in a third world country?

BACKGROUND AND OBJECTIVES: Transfusion errors can occur anywhere from blood donation to final blood transfusion. They are a source of increased cost and patient mortality. Automated workflows can reduce transcription errors, but resource-poor centres still use semi-automated/manual method for testing including manual labelling of column agglutination cards/testing tubes. Missing out any details on these cards can lead to errors in reporting results, wastage and loss of resources and effort. The aim of this study was to implement Six Sigma DMAIC (Define, Measure, Analyse, Improve and Control) methodology to reduce transcription errors while labelling gel card in immunohaematology lab to zero defect. MATERIALS AND METHODS: In this prospective study, transcription errors while manually performing 200 tests with 1400 opportunities were analysed. Baseline variables like number of errors, defects per million opportunities and sigma level in our current setup were measured. With the application of DMAIC methodology, root cause analysis for each error using Ishikawa diagram and structured Interviews were done to identify causes. A multipronged approach to deal with errors was done to improve critical areas using brainstorming sessions and developing training sheets for practice. After implementing the changes, baseline variables were reanalysed. RESULTS: Application of DMAIC resulted in an overall reduction in defects from 34.86% to 0.56% with sigma level improvement from 1.89 to 4.08. CONCLUSION: Six Sigma methodology can be used in a resource-poor setting even with lack of automation to ensure error-free process flow.

Analytical performance evaluation of sensitive and old generation reagent in routine practical use: estradiol experience.

Evaluation of the analytical performance of tests in medical laboratories is important. Total Error (TE) and sigma analysis have been used as a quantitative indicator of quality for many years. The aim of this study is to evaluate the analytical performance of Beckman Coulter Access Estradiol (E2) and Sensitive E2 reagents. Analytical performance of two reagents were evaluated with TE, six sigma and measurement uncertainty values. Two Beckman Coulter Unicel DxI-800 autoanalyzers (A1 and A2) included in the study. Quality control data between December 2017 and December 2019 were used. CLIA-2019 values were used for total allowable error (TEa) limits. Uncertainty values were calculated with ISO/TS 20914. The median TE of the old generation and sensitive E2 reagent were 27.46% (between 13.49 and 48.88) and 11.16% (between 7.08 and 24.81), respectively (p < .005) The process sigma results were below 3 sigma in all months with the old reagent, whereas with the new reagents it was seen to be above 3 sigma in 11 of 12 months for both autoanalyzers. Uncertainty of old reagent is higher than new reagent. Imprecisions decrease as concentration increases with both reagents. The uncertainty values of low concentration levels are greater than high concentration levels. In conclusion, in both auto analyzers, Sensitive E2 reagent was found to have better performance than old reagent in terms of TE, process sigma and measurement uncertainty. We believe that the sensitive E2 reagent still needs further improvement for patients who have low E2 levels.

Redesigning patient flow in orthopedics and radiology clinics via a three-phase 'Kaizen' improvement approach and interrupted time series analysis.

INTRODUCTION: The orthopedics clinic at an academic medical center has low patient satisfaction rates for patients that require an X-ray and have difficulty ambulating. The project aimed to reduce the 'non-value-added' time during appointments by using Lean and Six Sigma methodologies and enhance patient experience. METHODS: An analysis of the current state was conducted using Gemba walks, interviews with subject matter experts and an interrupted time study to assess baseline data. The project was implemented using a three-phase Kaizen event approach. RESULTS: Interventions implemented included: (i) re-engineering patient flow and (ii) standardizing appointment scheduling guidelines. The 'non-value-added' appointment time was measured post-intervention and it decreased from 17 to 8 min (51%), and 87% (N = 47) of patients rated the scheduling process positively. CONCLUSION: Lean, Six Sigma and Kaizen improvement methodologies are invaluable tools to improve operational efficiency. The implemented interventions enhanced patient experience and improved clinic efficiency.

Fully validated UPLC-MS/MS method for quantifying Favipiravir in human plasma boosted lean six sigma: An application for a bioequivalence study.

This research developed and validated a highly sensitive and selective UPLC-MS/MS approach using a triple quadrupole mass spectrometer for quantifying favipiravir. Moreover, we introduced a study evaluating bioequivalence using two drugs, Favibrivix and Avigan, containing favipiravir. Lean Six Sigma verified the capacity and performance of the process. Protein precipitation extraction was utilized to extract favipiravir from the collected human matrices. We used an Acquity UPLCr BEH HILIC column and valproic acid as an internal standard. Furthermore, we conducted the procedure using an isocratic elution comprising acetonitrile and 0.005% ammonia in water (75:25, v/v), a flow rate of 0.25 ml/min, a temperature controlled at 10°C and an injection volume of 1.0 µl. Our UPLC-MS/MS process has a broad range (50-10,000 ng/ml) with a determination coefficient of 0.9980. We validated the method in line with the US Food and Drug Administration. The findings revealed that the test, Favibrivix 200 mg/tablet, and the reference, Avigan® 200 mg/tablet, were statistically bioequivalent in healthy Egyptian participants.

Development and validation of a ultraperformance liquid chromatography-tandem mass spectrometry method for quantifying free and total dabigatran in human plasma: An application for a bioequivalence study.

Dabigatran etexilate mesylate (DABE), a prodrug, quickly changes into dabigatran (DAB) after its oral administration. Accordingly, detecting DABE in plasma is practically unmanageable. An ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) technique was developed and validated to compute free DAB in participants. For the first time, the central composite design, a type of response surface methodology, was applied for optimizing variables affecting the cleavage of glucuronide bond. In addition, the pharmacokinetic parameters of generic medication (okanadab) were determined, and the obtained outcomes were compared with those of the branded drug (pradaxa). The sample preparation was done using methanol as a protein precipitant and the separation was achieved using an ACQUITY UPLC BEH C18 column (2.1 × 50 mm, 1.7 µm). The elution was isocratically conducted using 10 mM ammonium formate:methanol (72:28, v/v) as a mobile phase and the flow rate was 0.25 mL/min. Multiple reaction monitoring and positive electrospray ionization were used. The determination was performed within 1 min, and the calibration growth curve was established over a range of 1.19-475 ng/mL using DAB-d3 as a tagged internal standard. Bioequivalence research was validated following the US Food and Drug Administration (US FDA) guidelines for bioanalytical procedures and acceptable outcomes were achieved. The outcomes for okanadab and pradaxa did not differ significantly.

Decreasing boarders in the emergency department by reducing clerical work in the discharge process of in-hospital patients in Brazil - an interrupted time-series analysis.

BACKGROUND: Emergency Department (ED) boarding is related to in-hospital patients' discharge since no beds will be available for receiving ED patients if there is a delay for patients in the yard leaving the hospital. New techniques implemented in hospital institutions, such as digital signatures to facilitate clerical work improve these processes. We evaluated the impact of expediting patients' discharge after medical orders with the number of patients with an unplanned hospital admission from the Hospital Out Clinic directed to ED for waiting for an available bed in a public tertiary hospital in Brazil. METHODS: We conducted a quasi-experimental study before and after an intervention. It consisted of an encrypted digital signature to reduce clerical work and expedite the patient's release from the institution after medical discharge. We used an interrupted time-series analysis based on administrative data (number of hospital discharges, bed turnover, the time between medical discharge, and the time the patient effectively left the hospital) from 2011 to 2020. RESULTS: We enrolled 210,496 patients admitted to the hospital from January 2011 to December 2020. Of those, 69,897(33%) composed the group after the intervention. There was no difference between the groups' gender, age distribution, the proportion of surgical patients, or in-hospital stay (≤ 7 or > 7 days). The interrupted time series analysis for the time from medical order to effectively hospital discharge showed an immediate change in level (Coefficient ß2 -3.6 h-95% confidence interval -3.9;-3.4), but no a difference in the slope of the behavior of the post-intervention curve (ß3 0.0005 coefficient-95% confidence interval -0.0040;0.0050). For the number of patients directed to ED, we observed no immediate change in level (Coefficient ß2 -0.84 patients-95% confidence interval -0.33;0.16), but a difference in the slope of the behavior of the post-intervention curve (ß3 0.0005 coefficient-95% confidence interval -0.0040;0.0050). CONCLUSION: Reducing clerical work and expediting patient discharge was associated with decreased potential boarders to ED.

Lean six sigma and stroke in rural hospital - The case of Baruch Padeh Medical Center.

PURPOSE: This case study aims to demonstrate the strengths of the Lean Six Sigma (LSS) methodology to improve the acute ischemic stroke (AIS) treatment rates and reduce process lead time at Baruch Padeh Medical Center (BPMC), a rural hospital in the Galilee region of Northern Israel. The LSS project redefined the BPMC stroke care pathway and increased its efficacy. DESIGN/METHODOLOGY/APPROACH: The LSS methodology was implemented in September 2017 by integrating lean principles and the Six Sigma DMAIC (Define-Measure-Analyze-Improve-Control). Existing procedures, field observation, ad hoc measurement and in-depth interviews were utilized, and the GEMBA method was implemented to identify root cause and improve actions optimizing the stroke pathway. FINDINGS: The presented case shows the usefulness of the LSS methodology in improving quality performance in a rural hospital. The intervention allowed the BPMC to improve the intravenous tissue plasminogen activator (IV-tPA) administration rate (+15.2%), reducing the process lead time. The lead time of door-to-computer tomography decreased from 52 to 26 min, and the door-to-needle time decreased from 94 to 75 min. ORIGINALITY/VALUE: The present case study shows the implementation of the LSS methodology aimed to improve the IV-tPA administration rate and reduce the stroke pathway lead time in a rural hospital. The case demonstrates the potential for the LSS methodology to support the AIS pathway optimization and represents a guide for healthcare organizations located in rural areas.

Six Sigma in surgery: how to create a safer culture in the operating theatre using innovative technology.

Safe delivery of patient care in the operating theatre is complex and co-dependent of many individual, organisational, and environmental factors, including patient, task and technology, individual, and human factors. The Six Sigma approach aims to implement a data-driven strategy to reduce variability and consequently improve safety. Analytical data platforms such as a Black Box ought to be embraced to support process optimisation and ultimately create a higher level of Six Sigma safety performance of the operating theatre team.

Practical application of Westgard Sigma rules with run size in analytical biochemistry processes in clinical settings.

BACKGROUND: The performance of 18 routine chemical detection methods was evaluated by the sigma (σ) metric, and Westgard Sigma rules with run size were used to establish internal quality control (IQC) standards to reduce patient risks. MATERIALS AND METHODS: External quality assessment (EQA) and internal quality control data from 18 assays in a biochemical laboratory were collected from January to June 2020. The sigma values of each assay were calculated, based on the bias, total error allowable, and coefficient of variation, appropriate quality control rules were selected. According to the quality goal index, the main causes of poor performance were determined to guide quality improvement. RESULTS: At IQC material level 1, seven of the 18 assays achieved five sigma (excellent), and five assays (UA, Crea, AMY, TC and Na) showed world-class performance. At IQC material level 2, 14 of the 18 assays achieved 5 sigma (excellent), and thirteen assays (UA, ALT, CK, Crea, AMY, K, AST, ALP, Na, LDH, Mg, TC and GGT) showed world-class performance. The quality goal index (QGI) was calculated for items with analysis performance <5 sigma, and the main causes of poor performance were determined to guide quality improvement. CONCLUSIONS: Westgard sigma rules with run size are an effective tool for evaluating the performance of biochemical assays. These rules can be used to more simply and intuitively select the quality control strategy of related items and reduce the risk to patients.

Application of a six sigma model to evaluate the analytical performance of urinary biochemical analytes and design a risk-based statistical quality control strategy for these assays: A multicenter study.

BACKGROUND: The six sigma model has been widely used in clinical laboratory quality management. In this study, we first applied the six sigma model to (a) evaluate the analytical performance of urinary biochemical analytes across five laboratories, (b) design risk-based statistical quality control (SQC) strategies, and (c) formulate improvement measures for each of the analytes when needed. METHODS: Internal quality control (IQC) and external quality assessment (EQA) data for urinary biochemical analytes were collected from five laboratories, and the sigma value of each analyte was calculated based on coefficients of variation, bias, and total allowable error (TEa). Normalized sigma method decision charts for these urinary biochemical analytes were then generated. Risk-based SQC strategies and improvement measures were formulated for each laboratory according to the flowchart of Westgard sigma rules, including run sizes and the quality goal index (QGI). RESULTS: Sigma values of urinary biochemical analytes were significantly different at different quality control levels. Although identical detection platforms with matching reagents were used, differences in these analytes were also observed between laboratories. Risk-based SQC strategies for urinary biochemical analytes were formulated based on the flowchart of Westgard sigma rules, including run size and analytical performance. Appropriate improvement measures were implemented for urinary biochemical analytes with analytical performance lower than six sigma according to the QGI calculation. CONCLUSIONS: In multilocation laboratory systems, a six sigma model is an excellent quality management tool and can quantitatively evaluate analytical performance and guide risk-based SQC strategy development and improvement measure implementation.

Using Lean Six Sigma techniques to improve efficiency in outpatient ophthalmology clinics.

BACKGROUND: Increasing patient numbers, complexity of patient management, and healthcare resource limitations have resulted in prolonged patient wait times, decreased quality of service, and decreased patient satisfaction in many outpatient services worldwide. This study investigated the impact of Lean Six Sigma, a service improvement methodology originally from manufacturing, in reducing patient wait times and increasing service capacity in a publicly-funded, tertiary referral outpatient ophthalmology clinic. METHODS: This quality improvement study compared results from two five-months audits of operational data pre- and post-implementation of Lean Six Sigma. A baseline audit was conducted to determine duration and variability of patient in-clinic time and number of patients seen per clinic session. Staff interviews and a time-in-motion study were conducted to identify issues reducing clinic service efficiency. Solutions were developed to address these root causes including: clinic schedule amendments, creation of dedicated postoperative clinics, and clear documentation templates. A post-implementation audit was conducted, and the results compared with baseline audit data. Significant differences in patient in-clinic time pre- and post-solution implementation were assessed using Mann-Whitney test. Differences in variability of patient in-clinic times were assessed using Brown-Forsythe test. Differences in numbers of patients seen per clinic session were assessed using Student's t-test. RESULTS: During the baseline audit period, 19.4 patients were seen per 240-minute clinic session. Median patient in-clinic time was 131 minutes with an interquartile range of 133 minutes (84-217 minutes, quartile 1- quartile 3). Targeted low/negligible cost solutions were implemented to reduce in-clinic times. During the post-implementation audit period, the number of patients seen per session increased 9% to 21.1 (p = 0.016). There was significant reduction in duration (p < 0.001) and variability (p < 0.001) of patient in-clinic time (median 107 minutes, interquartile range 91 minutes [71-162 minutes]). CONCLUSIONS: Lean Six Sigma techniques may be used to reduce duration and variability of patient in-clinic time and increase service capacity in outpatient ophthalmology clinics without additional resource input.