Evaluating laboratory performance on quality indicators with the six sigma scale

Evaluation of an in-practice wet-chemistry analyzer using canine and feline serum samples

A wet-chemistry biochemical analyzer was assessed for in-practice veterinary use. Its small size may mean a cost-effective method for low-throughput in-house biochemical analyses for first-opinion practice. The objectives of our study were to determine imprecision, total observed error, and acceptability of the analyzer for measurement of common canine and feline serum analytes, and to compare clinical sample results to those from a commercial reference analyzer. Imprecision was determined by within- and between-run repeatability for canine and feline pooled samples, and manufacturer-supplied quality control material (QCM). Total observed error (TEobs) was determined for pooled samples and QCM. Performance was assessed for canine and feline pooled samples by sigma metric determination. Agreement and errors between the in-practice and reference analyzers were determined for canine and feline clinical samples by Bland–Altman and Deming regression analyses. Within- and between-run precision was high for most analytes, and TEobs(%) was mostly lower than total allowable error. Performance based on sigma metrics was good (σ > 4) for many analytes and marginal (σ > 3) for most of the remainder. Correlation between the analyzers was very high for most canine analytes and high for most feline analytes. Between-analyzer bias was generally attributed to high constant error. The in-practice analyzer showed good overall performance, with only calcium and phosphate analyses identified as significantly problematic. Agreement for most analytes was insufficient for transposition of reference intervals, and we recommend that in-practice–specific reference intervals be established in the laboratory.

Improving Hospital Laboratory Performance: Implications for Healthcare Managers

Laboratory services in healthcare delivery systems play a vital role in inpatient care. Studies have shown that laboratory data affects approximately 65% of the most critical decisions on admission, discharge, and medication. Laboratory testing accounts for approximately 10% of hospital billing. Reducing laboratory costs and improving laboratory performance would contribute to reducing total healthcare cost, which is one of the major goals for the U.S. healthcare delivery system. The objective of this paper is to review and analyze the diverse research approaches applied to improve the performance of hospital laboratories in large healthcare delivery systems. The approaches reviewed include: lean, quality control, automation, and simulation modeling. In the conclusion, future research directions are presented, which include additional methods to be investigated to further improve the performance of hospital laboratories.

Sigma metric analysis for performance of creatinine with fresh frozen serum

BACKGROUND

Six sigma provides an objective and quantitative methodology to describe the laboratory testing performance. In this study, we conducted a national trueness verification scheme with fresh frozen serum (FFS) for serum creatinine to evaluate its performance in China.

METHODS

Two different concentration levels of FFS, targeted with reference method, were sent to 98 laboratories in China. Imprecision and bias of the measurement procedure were calculated for each participant to further evaluate the sigma value. Quality goal index (QGI) analysis was used to investigate the reason of unacceptable performance for laboratories with σ < 3.

RESULTS

Our study indicated that the sample with high concentration of creatinine had preferable sigma values. For the enzymatic method, 7.0% (5/71) to 45.1% (32/71) of the laboratories need to improve their measurement procedures (σ < 3). And for the Jaffe method, the percentages were from 11.5% (3/26) to 73.1% (19/26). QGI analysis suggested that most of the laboratories (62.5% for the enzymatic method and 68.4% for the Jaffe method) should make an effort to improve the trueness (QGI > 1.2). Only 3.1-5.3% of the laboratories should improve both of the precision and trueness.

CONCLUSIONS

Sigma metric analysis of the serum creatinine assays is disappointing, which was mainly due to the unacceptable analytical bias according to the QGI analysis. Further effort is needed to enhance the trueness of the creatinine measurement.

Evaluating Laboratory Performance on Point-of-Care Glucose Testing with Six Sigma Metric for 151 Institutions in China

BACKGROUND

The aim of this study was to use Six Sigma(SM) (Motorola Trademark Holdings, Libertyville, IL) techniques to analyze the quality of point-of-care (POC) glucose testing measurements quantitatively and to provide suggestions for improvement.

MATERIALS AND METHODS

In total, 151 laboratories in China were included in this investigation in 2014. Bias and coefficient of variation were collected from an external quality assessment and an internal quality control program, respectively, for POC glucose testing organized by the National Center for Clinical Laboratories. The σ values and the Quality Goal Index were used to evaluate the performance of POC glucose meters.

RESULTS

There were 27, 30, 57, and 37 participants in the groups using Optium Xceed™ (Abbott Diabetes Care, Alameda, CA), Accu-Chek(®) Performa (Roche, Basel, Switzerland), One Touch Ultra(®) (Abbott), and "other" meters, respectively. The median of the absolute value of percentage difference varied among different lots and different groups. Among all the groups, the Abbott One Touch Ultra group had the smallest median of absolute value of percentage difference except for lot 201411, whereas the "other" group had the largest median in all five lots. More than 85% of participate laboratories satisfied the total allowable error (TEa) requirement in International Organization for Standardization standard 15197:2013, and 85.43% (129/151) of laboratories obtained intralaboratory coefficient of variations less than 1/3TEa. However, Six Sigma techniques suggested that 41.72% (63/151) to 65.56% (99/151) of the laboratories needed to improve their POC glucose testing performance, in either precision, trueness, or both.

CONCLUSIONS

Laboratories should pay more attention on the practice of POC glucose testing and take actions to improve their performance. Only in this way can POC glucose testing really function well in clinical practice.

Transplant patient classification and tacrolimus assays: more evidence of the need for assay standardization

BACKGROUND

A global tacrolimus proficiency study recently showed clinically significant variability between laboratories, the inability of a common calibrator to harmonize methods, and differences in patient classification depending on the test method. The authors evaluated (1) the effect of a change in methodology on patient classification based on tacrolimus blood concentration and (2) the ability of 2 methods to position the concentration in a given specimen within the correct range.

METHODS

A total of 839 consecutive samples were analyzed at The Rogosin Institute and New York Presbyterian Hospital for routine tacrolimus monitoring over 30 days. Concordance analysis between the methods was performed covering dosage target ranges of 8-10, 6-8, 4-6 ng/mL currently used at our center. Six Sigma Metrics were applied to statistically evaluate the discordance rate.

RESULTS

Deming regression comparing liquid chromatography-tandem mass spectrometry and immunoassay yielded y = 0.927x - 0.24; 95% confidence interval, 0.903-0.951; R = 0.875; n = 839. There were 310 pairs (37%) discordant by 1, 21 (2.5%) discordant by 2, and 4 (0.5%) discordant by 3 therapeutic ranges. Surprisingly, 40% of patient samples were discordant when therapeutic ranges were 2 ng/mL wide. This discordant rate is equivalent to 1.7 Sigma and falls far below the minimum acceptable threshold of 3 Sigma.

CONCLUSIONS

Both methods are capable of measuring tacrolimus in the clinically relevant range between 1 and 10 ng/mL, yet 40% of the samples were discordant with an unacceptable Sigma level. Standardization of tacrolimus assays will mitigate this issue.

Quality control review: implementing a scientifically based quality control system

This review focuses on statistical quality control in the context of a quality management system. It describes the use of a 'Sigma-metric' for validating the performance of a new examination procedure, developing a total quality control strategy, selecting a statistical quality control procedure and monitoring ongoing quality on the sigma scale. Acceptable method performance is a prerequisite to the design and implementation of statistical quality control procedures. Statistical quality control can only monitor performance, and when properly designed, alert analysts to the presence of additional errors that occur because of unstable performance. A new statistical quality control planning tool, called 'Westgard Sigma Rules,' provides a simple and quick way for selecting control rules and the number of control measurements needed to detect medically important errors. The concept of a quality control plan is described, along with alternative adaptations of a total quality control plan and a risk-based individualized quality control plan. Finally, the ongoing monitoring of analytic performance and test quality are discussed, including determination of measurement uncertainty from statistical quality control data collected under intermediate precision conditions and bias determined from proficiency testing/external quality assessment surveys. A new graphical tool, called the Sigma Quality Assessment Chart, is recommended for demonstrating the quality of current examination procedures on the sigma scale.

Application of sigma metrics for the assessment of quality control in clinical chemistry laboratory in Ghana: A pilot study

BACKGROUND

Sigma metrics provide a uniquely defined scale with which we can assess the performance of a laboratory. The objective of this study was to assess the internal quality control (QC) in the clinical chemistry laboratory of the University of Cape Cost Hospital (UCC) using the six sigma metrics application.

MATERIALS AND METHODS

We used commercial control serum [normal (L1) and pathological (L2)] for validation of quality control. Metabolites (glucose, urea, and creatinine), lipids [triglycerides (TG), total cholesterol, high-density lipoprotein cholesterol (HDL-C)], enzymes [alkaline phosphatase (ALP), alanine aminotransferase (AST)], electrolytes (sodium, potassium, chloride) and total protein were assessed. Between-day imprecision (CVs), inaccuracy (Bias) and sigma values were calculated for each control level.

RESULTS

Apart from sodium (2.40%, 3.83%), chloride (2.52% and 2.51%) for both L1 and L2 respectively, and glucose (4.82%), cholesterol (4.86%) for L2, CVs for all other parameters (both L1 and L2) were >5%. Four parameters (HDL-C, urea, creatinine and potassium) achieved sigma levels >1 for both controls. Chloride and sodium achieved sigma levels >1 for L1 but <1 for L2. In contrast, cholesterol, total protein and AST achieved sigma levels <1 for L1 but >1 for L2. Glucose and ALP achieved a sigma level >1 for both control levels whereas TG achieved a sigma level >2 for both control levels.

CONCLUSION

Unsatisfactory sigma levels (<3) where achieved for all parameters using both control levels, this shows instability and low consistency of results. There is the need for detailed assessment of the analytical procedures and the strengthening of the laboratory control systems in order to achieve effective six sigma levels for the laboratory.

Evaluation of sampling spacing in pharmacokinetic studies using six sigma method

Key elements of pharmacokinetics (PK) studies include both, the number of sampling points (NSP) as well as the spacing between the sampling points (SSP). Optimization of the SSP is discussed in guidelines of all key regulatory agencies (RA). Those however, provide only very general rules on how to properly distribute the NSPs in proposed PK studies. Here we demonstrate that the six sigma (SX) method can be effectively used to assess the quality of SSPs. We have tested a modified SX method analyzing 466 PK profiles from 16 studies including a total of 368 healthy volunteers. Non-compartmental modeling was used to estimate PK parameters. The arithmetic means of minimum and maximum values of SX obtained for each subject in all studies were 1.97 and 3.83, respectively. The method described here allows comparing quality of studies performed at different centers, even if they cover different chemical entities. We propose that the SX values can be used to assess quality of PK studies, what is consistent with recommendations of the RAs.

Quality indicators in the preanalytical phase of testing in a stat laboratory

OBJECTIVE

To quantify performance in the preanalytical phase in a stat laboratory using quality indicators, and compare our results with those in the literature to improve laboratory services.

METHODS

We counted the test request forms, samples, and the types of preanalytical errors that occured in a stat laboratory between January 1 and December 31, 2011. We then compared the quality-indicator scores with the quality specifications mentioned in the literature.

RESULTS

During the 1-year period, a total of 168,728 samples and 88655 requests forms were received in stat laboratory. The total number of preanalytical errors was 1457, accounting for 0.8% of the total number of samples received in a year. Of the total preanalytical errors, 46.4% were hemolysed samples (biochemistry), 43.2% were clotted samples (hematology), 6.4% were samples lost-not received in the laboratory, 2.9% samples showed an inadequate sample-anticoagulant ratio, 0.7% were requests with errors in patient identification, 0.3% were samples collected in blood collection tubes with inappropriate anticoagulant and 0.1% were requests with errors--missing test requests.

CONCLUSION

The preanalytical performance of a stat laboratory in our setting is favorable and complies with international quality specifications.

Application of Six Sigma methodology to a cataract surgery unit

PURPOSE

The article's aim is to focus on the application of Six Sigma to minimise intraoperative and post-operative complications rates in a Turkish public hospital cataract surgery unit.

DESIGN/METHODOLOGY/APPROACH

Implementing define-measure-analyse-improve and control (DMAIC) involves process mapping, fishbone diagrams and rigorous data-collection. Failure mode and effect analysis (FMEA), pareto diagrams, control charts and process capability analysis are applied to redress cataract surgery failure root causes.

FINDINGS

Inefficient skills of assistant surgeons and technicians, low quality of IOLs used, wrong IOL placement, unsystematic sterilisation of surgery rooms and devices, and the unprioritising network system are found to be the critical drivers of intraoperative-operative and post-operative complications. Sigma level was increased from 2.60 to 3.75 subsequent to extensive training of assistant surgeons, ophthalmologists and technicians, better quality IOLs, systematic sterilisation and air-filtering, and the implementation of a more sophisticated network system.

PRACTICAL IMPLICATIONS

This article shows that Six Sigma measurement and process improvement can become the impetus for cataract unit staff to rethink their process and reduce malpractices. Measuring, recording and reporting data regularly helps them to continuously monitor their overall process and deliver safer treatments.

ORIGINALITY/VALUE

This is the first Six Sigma ophthalmology study in Turkey.

Measurement of improvement achieved by participation in international laboratory accreditation in sub-Saharan Africa: the Aga Khan University Hospital Nairobi experience

OBJECTIVES

As part of the ISO 15189:2007 accreditation process, the Aga Khan University Hospital Nairobi laboratory became the first internationally accredited hospital laboratory in sub-Saharan Africa outside South Africa in 2011 through the South Africa National Accreditation System.

METHODS

Seven preanalytic, 10 analytic, eight postanalytic, and five administrative performance parameters were monitored from 2009 to 2012 to measure the impact of the accreditation process.

RESULTS

Most measures in all four categories showed substantial improvement. The seven preanalytic measures all showed major improvement-between a quarter and a half sigma. Real but less dramatic improvement appeared in analytic and postanalytic measures, but greater than one sigma decrease in analytic "procedure violations" and a three-quarter sigma decrease in excessive turnaround time were noted in these categories. Administrative improvements included dramatic decreases in misdirected and missing reports and complaints.

CONCLUSIONS

This study demonstrates the correlation of the accreditation process with improvement in quality measures in a low-resource region.

Quantitative application of sigma metrics in medical biochemistry

INTRODUCTION

Laboratory errors are result of a poorly designed quality system in the laboratory. Six Sigma is an error reduction methodology that has been successfully applied at Motorola and General Electric. Sigma (σ) is the mathematical symbol for standard deviation (SD). Sigma methodology can be applied wherever an outcome of a process has to be measured. A poor outcome is counted as an error or defect. This is quantified as defects per million (DPM). A six sigma process is one in which 99.999666% of the products manufactured are statistically expected to be free of defects. Six sigma concentrates, on regulating a process to 6 SDs, represents 3.4 DPM (defects per million) opportunities. It can be inferred that as sigma increases, the consistency and steadiness of the test improves, thereby reducing the operating costs. We aimed to gauge performance of our laboratory parameters by sigma metrics.

OBJECTIVES

Evaluation of sigma metrics in interpretation of parameter performance in clinical biochemistry.

MATERIAL AND METHODS

The six month internal QC (October 2012 to march 2013) and EQAS (external quality assurance scheme) were extracted for the parameters-Glucose, Urea, Creatinine, Total Bilirubin, Total Protein, Albumin, Uric acid, Total Cholesterol, Triglycerides, Chloride, SGOT, SGPT and ALP. Coefficient of variance (CV) were calculated from internal QC for these parameters. Percentage bias for these parameters was calculated from the EQAS. Total allowable errors were followed as per Clinical Laboratory Improvement Amendments (CLIA) guidelines. Sigma metrics were calculated from CV, percentage bias and total allowable error for the above mentioned parameters.

RESULTS

For parameters - Total bilirubin, uric acid, SGOT, SGPT and ALP, the sigma values were found to be more than 6. For parameters - glucose, Creatinine, triglycerides, urea, the sigma values were found to be between 3 to 6. For parameters - total protein, albumin, cholesterol and chloride, the sigma values were found to be less than 3.

CONCLUSION

ALP was the best performer when it was gauzed on the sigma scale, with a sigma metrics value of 8.4 and chloride had the least sigma metrics value of 1.4.

Patient safety & post-analytical error

Post-analytical laboratory processes have been considered to be less prone to error than preanalytical processes because of the widespread adoption of laboratory automation and interfaced laboratory reporting. Quality monitors and controls for the post-analytical process have focused on critical result notification, meeting established turnaround time goals, and review of changed reports. The rapid increase in the adoption of electronic health records has created a new role for laboratory professionals in the management of patient test results. Laboratory professionals must interface with the clinical side of the health care team in establishing quality control for post-analytical processes, particularly in high-risk transitions of care.

Prioritizing risk analysis quality control plans based on Sigma-metrics

Six Sigma provides data-driven techniques that can enhance and improve the EP23 risk management approach for formulating quality control (QC) Plans. Risk analysis has significant drawbacks in its ability to identify and appropriately prioritize hazards and failure modes for mitigation of risks. Six Sigma quality management is inherently risk oriented on the basis of the required tolerance limits that define defective products. Six Sigma QC tools provide a quantitative assessment of method performance and an objective selection/design of statistical QC procedures. Furthermore, the observed sigma performance of a method is useful for prioritizing the need for development of QC plans.

A primer on the cost of quality for improvement of laboratory and pathology specimen processes

In today's environment, many laboratories and pathology practices are challenged to maintain or increase their quality while simultaneously lowering their overall costs. The cost of improving specimen processes is related to quality, and we demonstrate that actual costs can be reduced by designing "quality at the source" into the processes. Various costs are hidden along the total testing process, and we suggest ways to identify opportunities to reduce cost by improving quality in laboratories and pathology practices through the use of Lean, Six Sigma, and industrial engineering.

A core curriculum for clinical fellowship training in pathology informatics

Background:

In 2007, our healthcare system established a clinical fellowship program in Pathology Informatics. In 2010 a core didactic course was implemented to supplement the fellowship research and operational rotations. In 2011, the course was enhanced by a formal, structured core curriculum and reading list. We present and discuss our rationale and development process for the Core Curriculum and the role it plays in our Pathology Informatics Fellowship Training Program.

Materials and Methods:

The Core Curriculum for Pathology Informatics was developed, and is maintained, through the combined efforts of our Pathology Informatics Fellows and Faculty. The curriculum was created with a three-tiered structure, consisting of divisions, topics, and subtopics. Primary (required) and suggested readings were selected for each subtopic in the curriculum and incorporated into a curated reading list, which is reviewed and maintained on a regular basis.

Results:

Our Core Curriculum is composed of four major divisions, 22 topics, and 92 subtopics that cover the wide breadth of Pathology Informatics. The four major divisions include: (1) Information Fundamentals, (2) Information Systems, (3) Workflow and Process, and (4) Governance and Management. A detailed, comprehensive reading list for the curriculum is presented in the Appendix to the manuscript and contains 570 total readings (current as of March 2012).

Discussion:

The adoption of a formal, core curriculum in a Pathology Informatics fellowship has significant impacts on both fellowship training and the general field of Pathology Informatics itself. For a fellowship, a core curriculum defines a basic, common scope of knowledge that the fellowship expects all of its graduates will know, while at the same time enhancing and broadening the traditional fellowship experience of research and operational rotations. For the field of Pathology Informatics itself, a core curriculum defines to the outside world, including departments, companies, and health systems considering hiring a pathology informatician, the core knowledge set expected of a person trained in the field and, more fundamentally, it helps to define the scope of the field within Pathology and healthcare in general.

Managing the pre- and post-analytical phases of the total testing process

For many years, the clinical laboratory's focus on analytical quality has resulted in an error rate of 4-5 sigma, which surpasses most other areas in healthcare. However, greater appreciation of the prevalence of errors in the pre- and post-analytical phases and their potential for patient harm has led to increasing requirements for laboratories to take greater responsibility for activities outside their immediate control. Accreditation bodies such as the Joint Commission International (JCI) and the College of American Pathologists (CAP) now require clear and effective procedures for patient/sample identification and communication of critical results. There are a variety of free on-line resources available to aid in managing the extra-analytical phase and the recent publication of quality indicators and proposed performance levels by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) working group on laboratory errors and patient safety provides particularly useful benchmarking data. Managing the extra-laboratory phase of the total testing cycle is the next challenge for laboratory medicine. By building on its existing quality management expertise, quantitative scientific background and familiarity with information technology, the clinical laboratory is well suited to play a greater role in reducing errors and improving patient safety outside the confines of the laboratory.

Clinical quality indicators in laboratory medicine

Clinical laboratories have an important role in improving patient care. The past decades have seen enormous changes with unpredictable improvements in analytical performance, range of tests and capacity to manage large volumes of work. At the same time, there has been a dramatic fall in the rate of laboratory errors. However, there is now a growing awareness that the testing process includes the time before samples reach the laboratory and after reports have been printed and that these areas need to be included in the quality assessment of the total testing process. Laboratory quality should include a focus on patient safety and clinical effectiveness. Services should be patient-centred, timely, efficient and equitable, and finally, should be moulded to ensure optimal outcomes. There is a need to define quality indicators that will ensure there is appropriate choice and selection of tests, use of the appropriate assay standardization and the correct interpretation of the assay results at the appropriate time. These are the areas in which a quality laboratory can, and should, now involve itself.

Application of sigma metrics for the assessment of quality assurance in clinical biochemistry laboratory in India: a pilot study

Ensuring quality of laboratory services is the need of the hour in the field of health care. Keeping in mind the revolution ushered by six sigma concept in corporate world, health care sector may reap the benefits of the same. Six sigma provides a general methodology to describe performance on sigma scale. We aimed to gauge our laboratory performance by sigma metrics. Internal quality control (QC) data was analyzed retrospectively over a period of 6 months from July 2009 to December 2009. Laboratory mean, standard deviation and coefficient of variation were calculated for all the parameters. Sigma was calculated for both the levels of internal QC. Satisfactory sigma values (>6) were elicited for creatinine, triglycerides, SGOT, CPK-Total and Amylase. Blood urea performed poorly on the sigma scale with sigma <3. The findings of our exercise emphasize the need for detailed evaluation and adoption of ameliorative measures in order to effectuate six sigma standards for all the analytical processes.

Roots, development and future directions of laboratory medicine

Laboratory medicine has evolved from basic scientific observation and good experimental practice, with a strong emphasis on establishing the mechanisms of disease processes, linked with biomarker discovery, and development of analytical technologies. That evolution is set to move on apace with the mapping of the human genome. However, laboratory medicine is not solely based on robust basic science, but also on the translation of that knowledge into establishing the clinical utility of a marker, translation into evidence of the impact on health outcomes, as well as transformational change to integrate this new knowledge into the delivery of better care for patients. This translational research and the focus on transformational change are crucial in demonstrating value-for-money in the laboratory medicine service.

The pathology informatics curriculum wiki: Harnessing the power of user-generated content

BACKGROUND

The need for informatics training as part of pathology training has never been so critical, but pathology informatics is a wide and complex field and very few programs currently have the resources to provide comprehensive educational pathology informatics experiences to their residents. In this article, we present the "pathology informatics curriculum wiki", an open, on-line wiki that indexes the pathology informatics content in a larger public wiki, Wikipedia, (and other online content) and organizes it into educational modules based on the 2003 standard curriculum approved by the Association for Pathology Informatics (API).

METHODS AND RESULTS

In addition to implementing the curriculum wiki at http://pathinformatics.wikispaces.com, we have evaluated pathology informatics content in Wikipedia. Of the 199 non-duplicate terms in the API curriculum, 90% have at least one associated Wikipedia article. Furthermore, evaluation of articles on a five-point Likert scale showed high scores for comprehensiveness (4.05), quality (4.08), currency (4.18), and utility for the beginner (3.85) and advanced (3.93) learners. These results are compelling and support the thesis that Wikipedia articles can be used as the foundation for a basic curriculum in pathology informatics.

CONCLUSIONS

The pathology informatics community now has the infrastructure needed to collaboratively and openly create, maintain and distribute the pathology informatics content worldwide (Wikipedia) and also the environment (the curriculum wiki) to draw upon its own resources to index and organize this content as a sustainable basic pathology informatics educational resource. The remaining challenges are numerous, but largest by far will be to convince the pathologists to take the time and effort required to build pathology informatics content in Wikipedia and to index and organize this content for education in the curriculum wiki.

A Six Sigma approach to the rate and clinical effect of registration errors in a laboratory

Background

Laboratory errors made during the pre-analytical phase can have an impact on clinical care. Quality management tools such as Six Sigma may help improve error rates.

Aim

To use elements of a Six Sigma model to establish the error rate of test registration onto the laboratory information system (LIS), and to deduce the potential clinical impact of these errors.

Methods

In this retrospective study, test request forms were compared with the tests registered onto the LIS, and all errors were noted before being rectified. The error rate was calculated. The corresponding patient records were then examined to determine the actual outcome, and to deduce the potential clinical impact of the registration errors.

Results

Of the 47 543 tests requested, 72 errors were noted, resulting in an error rate of 0.151%, equating to a sigma score of 4.46. The patient records reviewed indicated that these errors could, in various ways, have impacted on clinical care.

Conclusion

This study highlights the clinical effect of errors made during the pre-analytical phase of the laboratory testing process. Reduction of errors may be achieved through implementation of a Six Sigma programme.

The applicability of Lean and Six Sigma techniques to clinical and translational research

BACKGROUND

Lean and Six Sigma are business management strategies commonly used in production industries to improve process efficiency and quality. During the past decade, these process improvement techniques increasingly have been applied outside the manufacturing sector, for example, in health care and in software development. This article concerns the potential use of Lean and Six Sigma in improving the processes involved in clinical and translational research. Improving quality, avoiding delays and errors, and speeding up the time to implementation of biomedical discoveries are prime objectives of the National Institutes of Health (NIH) Roadmap for Medical Research and the NIH's Clinical and Translational Science Award program.

METHODS

This article presents a description of the main principles, practices, and methods used in Lean and Six Sigma. Available literature involving applications of Lean and Six Sigma to health care, laboratory science, and clinical and translational research is reviewed. Specific issues concerning the use of these techniques in different phases of translational research are identified.

RESULTS

Examples of Lean and Six Sigma applications that are being planned at a current Clinical and Translational Science Award site are provided, which could potentially be replicated elsewhere. We describe how different process improvement approaches are best adapted for particular translational research phases.

CONCLUSIONS

Lean and Six Sigma process improvement methods are well suited to help achieve NIH's goal of making clinical and translational research more efficient and cost-effective, enhancing the quality of the research, and facilitating the successful adoption of biomedical research findings into practice.

Applicability and potential benefits of benchmarking in Brazilian clinical laboratory services

Purpose

The purpose of this paper is to test the applicability and benefits of benchmarking as a tool for quality analysis in Brazilian laboratory medical services.

Design/methodology/approach

A primary observational study is performed in eight hospital laboratories by tracking the receipt, analysis and return to participants of monitoring reports relating to several quality indicators for the years 2005 and 2006. Whenever possible, the paper applies 6σ criteria as an independent assessment of process quality.

Findings

Data obtained for the eight laboratories showed a monthly average (±SD) of 178,579 (±153,670) tests performed per laboratory, with 40,256 (±44,858) requisitions and 4.77 (±1.33) tests per requisition. Overall, productivity was 7.35 (±2.46) tests per man‐hour of work (MHW), increasing to 15.36 (±6.00) when considering only the analytical sector staff. An average of 1.63 (±1.14) lost hours per hundred MHW were reported (level 3.6σ), with 3.86 (±5.10) accidents at work reported (AWR) per hundred thousand MHW (level 5.5σ) and 4.22 (±2.61) redraws per thousand requisitions attended (level 4.1σ). The turn‐around‐times were 2.25 (±0.98), 3.29 (±2.12) and 8.54 (±3.25) hours for glucose level, haemogram and human immunodeficiency virus serology, respectively.

Practical implications

Benchmarking proved to be a useful and feasible tool for quality management in Brazilian clinical laboratories, particularly when associated with independent tools for evaluating the quality of laboratorial processes.

Originality/value

This is the first Brazilian study reporting that benchmarking provides useful information on the performance of different clinical laboratory processes and, therefore, could become an important tool for laboratory management.

Feasibility of Biological Specimen Collection for the Canadian Longitudinal Study on Aging (CLSA) Biorepository

La collecte de spécimens biologiques est une partie intégrale de beaucoup d’études épidémiologiques longitudinales. Il est important d’obtenir un haut taux de satisfaction de la part des participants pour que leur participation soit continue et pour assurer une qualité élevée des échantillons pour avoir des mesures précises pour les biomarqueurs. Nous avons réalisé une étude pour évaluer ces questions sur la collecte d’échantillons proposée pour l’Étude longitudinale canadienne sur le vieillissement (ÉLCV). Parmi les 85 participants recrutés, 65 ont été dirigés vers un laboratoire d’hôpital ou un laboratoire privé. Environ 100 mL de sang et un prélèvement aléatoire d’urine ont été collectés pour chaque participant, pour un total de 2 108 aliquots d’échantillon. Les niveaux de qualité ont été atteints pour plus de 90 % des échantillons et étaient semblables pour les échantillons collectés dans les deux laboratoires. Plus de 90 % des participants ont exprimé que leur satisfaction par rapport à la collecte était bonne ou excellente, et 84 % serait prêts à répéter la collecte dans un à trois ans.

[Reducing patient waiting time for the outpatient phlebotomy service using six sigma]

BACKGROUND

One of the challenging issues of the outpatient phlebotomy services at most hospitals is that patients have a long wait. The outpatient phlebotomy team of Kyungpook National University Hospital applied six sigma breakthrough methodologies to reduce the patient waiting time.

METHODS

The DMAIC (Define, Measure, Analyze, Improve, and Control) model was employed to approach the project. Two hundred patients visiting the outpatient phlebotomy section were asked to answer the questionnaires at inception of the study to ascertain root causes. After correction, we surveyed 285 patients for same questionnaires again to follow-up the effects.

RESULTS

A defect was defined as extending patient waiting time so long and at the beginning of the project, the performance level was 2.61 sigma. Using fishbone diagram, all the possible reasons for extending patient waiting time were captured, and among them, 16 causes were proven to be statistically significant. Improvement plans including a new receptionist, automatic specimen transport system, and adding one phlebotomist were put into practice. As a result, the number of patients waited more than 5 min significantly decreased, and the performance level reached 3.0 sigma in December 2007 and finally 3.35 sigma in July 2008.

CONCLUSIONS

Applying the six sigma, the performance level of waiting times for blood drawing exceeding five minutes were improved from 2.61 sigma to 3.35 sigma.

The role of laboratory information systems in healthcare quality improvement

PURPOSE

The purpose of this study was to evaluate the status of US hospital Laboratory Information Systems. Laboratory Information Systems are critical to high quality healthcare service provision. Data show that the need for these systems is growing to meet accompanying technological and workload demands. Additionally, laboratory tests provide the majority of information for clinical decision-making. Laboratory processes automation, including patient result verification, has greatly improved laboratory test throughput while decreasing turn-around-times, enabling critical results to reach physicians rapidly for improved clinical outcomes.

DESIGN/METHODOLOGY/APPROACH

Data were drawn from the 2007 Healthcare Information and Management Systems Society (HIMSS) Analytics Database, which includes over 5,000 US healthcare organizations and provides extensive data on the hardware, software, and information technology infrastructure within healthcare organizations.

FINDINGS

US hospitals are actively involved in laboratory systems planning to improve health service quality. Specifically, data show 76 new laboratory information systems are currently being installed in 2007 with another 399 under contract for future installation. As a result, increasing investment in laboratory information systems is providing state-of-the-art clinical laboratory support, which enhances clinical care processes and improves quality. These state-of-the-art Laboratory Information Systems, when linked with other clinical information systems such as Computerized Physician Order Entry and Electronic Medical Record, will support further healthcare quality improvement.

ORIGINALITY/VALUE

This article includes the most current information available on the US hospital laboratory information system applications.

Quality and timeliness in medical laboratory testing

In terms of testing, modern laboratory medicine can be divided into centralized testing in central laboratories and point-of-care testing (POCT). Centralized laboratory medicine offers high-quality results, as guaranteed by the use of quality management programs and the excellence of the staff. POCT is performed by clinical staff, and so such testing has moved back closer to the patient. POCT has the advantage of shortening the turnaround time, which potentially benefits the patient. However, the clinical laboratory testing expertise of clinical staff is limited. Consequently, when deciding which components of laboratory testing must be conducted in central laboratories and which components as POCT (in relation to quality and timeliness), it will be medical necessity, medical utility, technological capabilities and costs that will have to be ascertained. Provided adequate quality can be guaranteed, POCT is preferable, considering its timeliness, when testing vital parameters. It is also preferred when the central laboratory cannot guarantee the delivery of results of short turn-around-time (STAT) markers within 60 or (even better) 30 min. POCT should not replace centralized medical laboratory testing in general, but it should be used in cases where positive effects on patient care have been clearly demonstrated.

Quality Control Validation, Application of Sigma Metrics, and Performance Comparison between Two Biochemistry Analyzers in a Commercial Veterinary Laboratory

A review of the literature pertinent to interpretation of biochemistry data and quality control (QC) and proficiency testing data from 2 biochemistry analyzers was used to determine clinical quality requirements for biochemistry assays, characterize the performance of and calculate sigma metrics for the analytes run on the 2 analyzers, and perform QC validation in order to determine the needs for statistical QC for each analyzer. Quality requirements suitable for the analytes based on the needs of the authors' laboratory are presented. These requirements may or may not be appropriate for other laboratories, depending on the needs of the clients, species, and equipment performance capability. The majority of the analytes were easily controlled using the 13s control rule, with a sigma metric approaching or exceeding 6 and with a high probability of error detection and a low probability of false rejection. Some analytes could not be controlled using the 13s rule, and additional control rules with a greater number of control data points were required. There were differences between performances of the 2 analyzers. The findings in the present study emphasize the need for QC specific for the analyte and the clinical decision level and the need for separate QC validation on every instrument.

Laboratory quality management: a roadmap

Laboratories in the United States are subject to so many national, state, and local requirements that it is very complicated to track compliance with every individual organization's listed requirements. What is needed is a roadmap for quality that ensures that each laboratory makes its best contribution to patient care and safety while continually meeting all requirements. This article presents such a roadmap for laboratory quality management that is based on the many and various published laboratory regulations, standards, and accreditation requirements. This model also clearly illustrates the important relationship between quality activities that should be designed and supported by laboratory management and the technical activities that produce laboratory results for patient care.

Primena »Six Sigma« U Kontroli Kvaliteta Zdravstvenih Laboratorija

Cilj svakog postupka ili proizvodnog sistema je dobijanje dobrog proizvoda. Većina metoda kontrole kvaliteta je inicijalno razvijena da pomogne industrijsku proizvodnju. Ovo ne predstavlja iznenađenje s obzirom da masovna proizvodnja tipično zahteva mnogo ponavljanja koje uključuju kontrolisani redosled operacija. Nisu svi prilazi kontroli kvaliteta podjednako efikasni. Neusaglašenosti koje postoje u laboratorijskom određivanju su u osnovi uzrokovane kako prekomernim varijacijama u procesu, tako i greškama. Ključni nedostatak u primeni metoda statističke kontrole kvaliteta ležKi u činjenici da su neefikasne u detekciji i kontroli grešaka, a one danas predstavljaju najdominatniji uzrok neusaglašenosti većine organizacionih procesa. Statističkom kontrolom kvaliteta mogu efikasno da se kontrolišu varijacije u procesu, ali ne mogu da se detektuju ili spreče greške. »Six Sigma« pripada statističkoj kontroli kvaliteta koja pružKa novu metodologiju za merenje karakteristika procesa, a takođe usavršava prethodne metodologije čime dolazi do unapređenja procesa. MenadžKment zasnovan na »Six Sigma« kvalitetu polako ulazi u zdravstvene organizacije pri čemu nudi realnu nadu za unapređenje razmišljanja i procesa menadžKmenta kvaliteta. Jedan od razloga je što se »Six Sigma« fokusira na defekte koji za uzvrat zahtevaju da ciljevi za dobar kvalitet budu definisani. »Six Sigma» pružKa univerzalnu metodologiju kojom se meri kvalitet time što se broje defektni proizvodi, pri čemu se određuje stopa defektnih proizvoda kao »defekti na milion» (»defects per million» ili »DPM»), a koji se zatim konvertuju u »Sigma metriku» uz korišćenje standradnih tabela koje su dostupne u svakom tekstu vezanom za »Six Sigma». »Sigma metrikom» se »Six Sigma» pojednostavljuje i dobija univerzalni »reper» koji govori o karakteristikama procesa. Na ovaj način svi procesi mogu da se okarakterišu na »Sigma skali.« Tipično se vrednosti nalaze između 2 i 6, pri čemu je cilj postizanje »svets- ke klase kvaliteta» koja iznosi 6. Na osnovu podataka koji potiču iz stvarnog sveta zdravstvenih laboratorija očigledno se možKe zaključiti da je izvođenje operacija na današnjim instrumentima dobro. Nova generacija kliničkih analizatora je postigla jako visoku «Sigma metriku«. Korisnici zdravstvene zaštite mogu da užKivaju u novoj eri napretka sa instrumentima i metodama nivoa 6 Sigma ili višim.

Results of a Proposed Breath Alcohol Proficiency Test Program

Although proficiency test programs have long been used in both clinical and forensic laboratories, they have not found uniform application in forensic breath alcohol programs. An initial effort to develop a proficiency test program appropriate to forensic breath alcohol analysis is described herein. A total of 11 jurisdictions participated in which 27 modern instruments were evaluated. Five wet bath simulator solutions with ethanol vapor concentrations ranging from 0.0254 to 0.2659 g/210 L were sent to participating programs, instructing them to perform n = 10 measurements on each solution using the same instrument. Four of the solutions contained ethanol only and one contained ethanol mixed with acetone. The systematic errors for all instruments ranged from -11.3% to +11.4% while the coefficient of variations ranged from zero to 6.1%. A components-of-variance analysis revealed at least 79% of the total variance as being due to the between-instrument component for all concentrations. Improving proficiency test program development should consider: (1) clear protocol instructions, (2) frequency of proficiency testing, (3) use lower concentrations for determining limits-of-detection and -quantitation, etc. Despite the lack of a biological component, proficiency test participation should enhance the credibility of forensic breath test programs.

Pathology and patient safety: the critical role of pathology informatics in error reduction and quality initiatives

Understanding the role of pathology informatics in patient safety entails an introduction to terminology and projects that have represented efforts to date in this area. The authors provide a short alphabetized introduction to several "buzzwords" and terms related to tools and processes that are used by health care research experts and workers involved in patient safety initiatives. The authors also include short descriptions of key health care research and patient safety projects that are relevant to pathology. They aim to highlight the areas where pathology informatics in all of its flavors (production systems provided by vendors as well as research and development efforts) can play a role in promoting patient safety.

Medical errors: impact on clinical laboratories and other critical areas

The Institute of Medicine (IOM) report (1999) stated that the prevalence of medical errors is high in today's health care system. Some specialties in health care are more risky than others. A varying blunder/error rate of 0.1-9.3% in clinical diagnostic laboratories has been reported in the literature. Many of these errors occur in the preanalytical and postanalytical phases of testing. It has been suggested that the errors occurring in clinical diagnostic laboratories are smaller in number than those occurring elsewhere in a hospital setting. However, given the quantum of laboratory tests used in health care, even this small rate may reflect a large number of errors. The surgical specialties, emergency rooms, and intensive care units have been previously identified as areas of risk for patient safety. Though the nature of work in these specialties and their interdependence on clinical diagnostic laboratories presents abundant opportunities for error-generating behavior, many of these errors may be preventable. Appropriate attention to system factors involved in these errors and designing intelligent system approaches may help control and eliminate many of these errors in health care.

An Improved Failure Mode Effects Analysis for Hospitals

Objective.—To review the Failure Mode Effects Analysis (FMEA) process recommended by the Joint Commission on Accreditation of Health Organizations and to review alternatives. This reliability engineering tool may be unfamiliar to hospital personnel.

Data Sources.—Joint Commission on Accreditation of Health Organizations recommendations, Mil-Std-1629A, and other articles about FMEA were used.

Study Selection.—The articles were selected by a literature search that included Web site–accessible material.

Data Extraction.—All articles found were used.

Data Synthesis.—The results are based on the articles cited and the author's experience in conducting FMEAs in the medical diagnostics industry.

Conclusions.—Fault trees and a list of quality system essentials are recommended additions to the FMEA process to help identify failure mode effects and causes. Neglecting mitigations for failure modes that have never occurred is a possible danger when too much emphasis is placed on improving risk priority numbers. A modified Pareto, not based on the risk priority number, is recommended when there are qualitatively different failure mode effects with different severities. Performing a FMEA that both meets accreditation requirements and reduces the risk of medical errors is an attainable goal, but it may require a different focus.

Laboratory quality control: using patient data to assess analytical performance

Quality control plays a vital role helping to ensure the reliability of laboratory test results. The application of statistical quality control has been a component of laboratory medicine for approximately 50 years. Many of the control rules based on the early applications of statistical quality control have remained essentially unchanged since their initial introduction. Optimization of quality control rules can vary depending on the application for which a test is to be used. This review explores the various applications of laboratory quality control procedures and their role in identifying laboratory error. The ubiquitous use of computers in today's laboratories has enabled the development of more sophisticated means of assessing laboratory quality. The use of the Six Sigma technique and its adoption by the laboratory community is one example. Other examples include the use of patient-derived quality control procedures as a means of assessing laboratory performance. Early examples of these types of applications include use of Bull's algorithm, anion gap measurements, and delta checking. More recent applications include the correlation of laboratory test results, the average of normals procedure, and the Bhattacharya method.

Practice patterns of testing waived under the clinical laboratory improvement amendments

OBJECTIVES

To determine operational practices in laboratories operating under a Certificate of Wavier (waived laboratories), or equivalent, under the Clinical Laboratory Improvements Amendments (CLIA) of 1988 when performing tests designated as having an insignificant risk of an erroneous result (ie, waived tests).

METHODS

Waived laboratories that were part of the Centers for Disease Control and Prevention Laboratory Sentinel Monitoring Network project in the states of Arkansas, New York, and Washington were surveyed about their quality control (QC) and quality assurances (QA) practices when performing waived testing. Arkansas and Washington sent out similar questionnaires, whereas on-site surveys were conducted in New York. The survey in Arkansas and Washington also included nonwaived laboratories. The New York visits were designed to pilot test a regulatory inspection program for limited testing sites, which, in New York, are roughly equivalent to laboratories operating under a CLIA Certificate of Wavier and/or Provider-Performed Microscopy but are generally not located in physicians' offices. Laboratories visited in New York were selected from a list of limited testing sites and were representative of that population.

RESULTS

Arkansas received responses from 211 facilities (37% response rate), of which 38% had Certificates of Waiver. Washington received responses from 190 waived laboratories (71% response rate) and from 116 nonwaived laboratories (32% response rate). In New York, 607 of the 2751 limited testing laboratories were visited. Reporting laboratories in all 3 states most frequently performed testing for glucose, urinalysis, urine human chorionic gonadotropin, occult blood, and group A Streptococcus antigen, although other waived tests were performed less frequently. Washington found that 57% of waived laboratories followed manufacturers' QC requirements. Arkansas found that 58% of laboratories doing waived tests that required liquid controls performed these controls, and 59% performing waived testing requiring electronic controls used these controls. In New York, 68% of the laboratories complied with the manufacturer's QC requirements for a variety of tests. Being accredited by an external organization or affiliated with a more complex laboratory improved compliance. Nonwaived laboratories in Washington and Arkansas complied with manufacturer's instructions at a higher rate than did waived laboratories. Similar deficiencies in following CLIA requirements were found in other areas of laboratory operation.

CONCLUSIONS

Just more than half of waived laboratories in 3 diverse states follow manufacturer's instructions for recommended QC and QA. These instructions help ensure that the test will produce results that have an insignificant chance of an error. Although we did not study the impact of this and other findings on patient care, the results show that imposing good laboratory practices by regulation alone was insufficient to ensure quality laboratory results in any location evaluated. A system that can continually provide accessible education on laboratory practices, coupled with new thoughts on the regulatory environment, is in order.

Q-tracks: a College of American Pathologists program of continuous laboratory monitoring and longitudinal tracking

CONTEXT

Continuous monitoring of key laboratory indicators of quality by hundreds of laboratories in a standardized measurement program affords an opportunity to document the influence of longitudinal tracking on performance improvement by participants focused on that outcome.

OBJECTIVE

To describe the results of the first 2 years of participation in a unique continuous performance assessment program for pathology and laboratory medicine.

DESIGN

Participants in any of 6 modules in the 1999 and 2000 College of American Pathologists (CAP) Q-Tracks program collected data according to defined methods and sampling intervals on standardized input forms. Data were submitted quarterly to CAP for statistical analysis. Interinstitutional comparison reports returned in 6 weeks provided each laboratory with its performance profile of key indicators and its percentile ranking compared with all participants in that quarter. This also included longitudinal comparisons of performance during previous cumulative quarters. Control charts graphically displayed data with flags identifying performance points that were out of statistical control.

SETTING

Hospital-based laboratories in the United States (98%), Canada, and Australia.

PARTICIPANTS

Voluntary subscriber laboratories in the CAP Q-Tracks performance measurement program: roughly 70% from hospitals of 300 occupied beds or fewer, 65% from private, nonprofit institutions, slightly more than half located in cities, one third from teaching hospitals, and 20% with pathology residency training programs.

MAIN OUTCOME MEASURES

Each module measured several major and additional minor quality indicators and unbenchmarked individualized data for internal use.

RESULTS

Participants in 4 of 6 Q-Tracks continuous monitors demonstrated statistically significant performance improvement trends in 1999 and 2000, which were most marked for laboratories that continued participation throughout both years. These monitors were wristband patient identification, laboratory specimen acceptability, blood product wastage, and intraoperative frozen section consultation.

CONCLUSIONS

Key continuous indicators chosen on the basis of a decade's experience in the CAP Q-Probes quality improvement program are useful measurement and benchmarking tools for laboratories to improve performance. In general, measures in which there is a broad range of demonstrable performance initially are most optimal for subsequent improvement using continuous monitoring. These studies have shown that quality is not static, but rather is a moving benchmark of performance as seen in the redefinition of benchmarks over time by participants in the first 2 years of the CAP Q-Tracks program.

Continuous wristband monitoring over 2 years decreases identification errors: a College of American Pathologists Q-Tracks Study

CONTEXT

Identification of patients is one of the first steps in ensuring the accuracy of laboratory results. In the United States, hospitalized patients wear wristbands to aid in their identification, but wristbands errors are frequently found.

OBJECTIVE

To investigate if continuous monitoring of wristband errors by participants of the College of American Pathologists (CAP) Q-Tracks program results in lower wristband error rates.

SETTING

A total of 217 institutions voluntarily participating in the CAP Q-Tracks interlaboratory quality improvement program in 1999 and 2000.

DESIGN

Participants completed a demographic form, answered a questionnaire, collected wristband data, and at the end of the year, best and most improved performers answered another questionnaire seeking suggestions for improvement. Each institution's phlebotomists inspected wristbands for errors before performing phlebotomy and recorded the number of patients with wristband errors. On a monthly basis, participants submitted data to the CAP for data processing, and at the end of each quarter, participants received summarized comparisons. At the end of each year, participants also received a critique of the results along with suggestions for improvement.

MAIN OUTCOME MEASURES

The percentage of wristband errors by quarter, types of wristband errors, and suggestions for improvement.

RESULTS

During 2 years, 1 757 730 wristbands were examined, and 45 197 wristband errors were found. The participants' mean wristband error rate for the first quarter in 1999 was 7.40%; by the eighth quarter, the mean wristband error rate had fallen to 3.05% (P <.001). Continuous improvement occurred in each quarter for participants in the 1999 and 2000 program and in 7 of 8 quarters for those who participated in both 1999 and 2000. Missing wristbands accounted for 71.6% of wristband errors, and best performers usually had wristband error rates under 1.0%. The suggestion for improvement provided by the largest number of best and most improved performers was that phlebotomists should refuse to perform phlebotomy on a patient when a wristband error is detected.

CONCLUSIONS

The wristband error rate decreased markedly when this rate was monitored continuously using the CAP Q-Tracks program. The Q-Tracks program provides a useful tool for improving the quality of services in anatomic pathology and laboratory medicine.

Improved allocation of costs through analysis of variation in data: planning of laboratory studies

BACKGROUND

When developing a new laboratory test for study of human diseases, it is important to identify and control internal and external sources of variation that affect test results. It is also imperative that the precision of the test not only meets pre-established requirements and not exceed allowable total error, but also that these objectives are reached without undue expenditure of either time or financial resources.

METHODS

This study applies statistical principles in designing a cost-effective experimental approach for determining the analytical precision of a new test. This approach applies the statistical concept of variance components to the problem of balancing a pre-established level of analytical precision against expenses incurred in achieving this precision.

RESULTS

We demonstrated (1) estimation of variance components, (2) use of these estimates for improving allocation of costs within the experiment, and (3) use of these estimates for determining the optimal number of replicate measurements.

CONCLUSIONS

Although elimination of all sources of variation that can affect laboratory test results is unlikely, the application of analysis of variance (ANOVA) statistical techniques can lead to a cost-effective allocation of resources for estimating the precision of a laboratory test.