clinical chemistry quality manual

We need to use our knowledge and common sense expanded with new skills e.g. from the humanities, management, business and change sciences in order to bring this about together with the users of the laboratory. Quality control, quality assurance and total quality management in Clinical chemistry According to ISO 9000:2005, Clause 3.2.11, quality assurance is a part of quality management, providing confidence that quality requirements will be fulfilled. Quality control is monitoring to indicate needed corrective responses. Westgard, deVerdier, Groth and Aronsson ( 6, 7 ) addressed the important problem of false rejections of measurements introducing the use of multiple control rules. Importantly the introduction of ISO 15189 ( 16 ) broadened the scope of accreditation from the measurement process itself to the interaction of the laboratory with its clients and to the total testing chain, including the pre-and postanalytical processes. This is in tune with the widely practiced and well-established approaches of total quality management systems. This development together with the responsibility of the manufacturers for the measurement systems and reagents ( 18 ) creates the environment for re-orientation of laboratories of clinical chemistry to closer co-operation with their users. Total quality management (TQM) in clinical chemistry consists of efforts to establish and maintain a climate of continued improvements in the laboratory in order to deliver high-quality services to health care. Total quality management systems come in numerous variants forwarded by different organizations but are united by the following major cornerstones: 1) customer needs define quality, 2) continuous monitoring ( 19 ), systematic analysis and improvement of crucial work processes are needed, 3) the top leadership of the laboratory is responsible for the quality and quality improvements.

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It also provides opportunity of checking whether the quality system is implemented in reality and demonstrates to the hospital administration and the clinicians that the laboratory is committed to quality. The intention of these guidelines is to describe the elements of the quality system for a large clinical laboratory, and to presentate such a system in the form of a quality manual. However, information about the minimum requirements for official recognition should be obtained from the particular accreditation or certification body concerned. Key Words: accreditation, audit, certification of quality system, good laboratory practice, quality improvement, quality management, quality manual, quality system To learn about our use of cookies and how you can manage your cookie settings, please see our Cookie Policy. By closing this message, you are consenting to our use of cookies. To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to upgrade your browser. You can download the paper by clicking the button above. Summary Working in laboratories of clinical chemistry, we risk feeling that our personal contribution to quality is small and that statistical models and manufacturers play the major roles. It is seldom sufficiently acknowledged that personal knowledge, skills and common sense are crucial for quality assurance in the interest of patients. The employees, environment and procedures inherent to the laboratory including its interactions with the clients are crucial for the overall result of the total testing chain. As the measurement systems, reagents and procedures are gradually improved, work on the preanalytical, postanalytical and clinical phases is likely to pay the most substantial dividends in accomplishing further quality improvements. This means changing attitudes and behaviour, especially of the users of the laboratory. It requires understanding people and how to engage them in joint improvement processes.

Open in a separate window Figure 1 The total testing chain in clinical chemistry involves several professionals and organizations in healthcare from the clinical decision to order a test through the pre-analytical, analytical and post-analytical phases to the value of the test result in the on-going clinical decisions and healthcare process. Uncertainty of the high-volume measurement methods in clinical chemistry has decreased substantially with the advent of highly automated measurement methods and reference measurement systems. The most substantial improvements have been accomplished in reducing the repeatability and reproducibility. Bias has also been decreased, but not to the same extent ( 28 ). The preanalytical, postanalytical and clinical phases (collectively known as extraanalytical phases ) of the testing processes have not been addressed nearly to the same extent as the analytical phase, probably because they involve multiple categories of professionals working in the clinic and are therefore outside of the boundaries of total control of the laboratory. In brief; it depends on whether the taking and handling of samples is under the auspices of the laboratory or not. Research in the fields of pre- and post-analytical factors in laboratory medicine has seen exponential growth during recent years. However, since most of the economy of the laboratory is spent in the analytical phase, it still attracts the main focus of both the diagnostic industry and healthcare. Another important reason that pre- and postanalytical factors have been studied less than analytical factors is that other research- and administrative paradigms are needed than when studying analytical factors which can and should be addressed by sound principles of e.g. metrology. Optimal pre- and post-analytical procedures are frequently known and agreed on in professional circles.

The well-established principles of total quality management come in handy when optimizing the total testing chain. Quality assurance must be implemented, managed and maintained by the leadership of the laboratory. Procedures, processes and systems and not people represent the major obstacles to optimal quality. When physical staircases need cleaning, an appropriate cleaning process should start at the top since dust gravitates downwards. The initial efforts made by the laboratories to acquire accreditation are commonly the most rewarding as they engage all of the employees and the whole organisation in a goal-directed and concerted effort for improvements. As the years pass by, accreditation usually becomes the primary activity of a handful of persons in the laboratory who create a bureaucracy for the purpose. Standards and accreditation are important for quality assurance but in their basic nature they strive for status quo rather than for dynamic development with the inherent risks that changes invite. The avoidance of the risks of organisational changes is fundamentally not a property of the standards themselves. Accreditation according to ISO standards, as commonly practiced today, therefore risks becoming not only an obstacle but also a real enemy of the necessary paradigm shift in laboratory medicine made possible by advances in automation and information technologies. Flexible scope of accreditation ( 17, 20 ) may represent a partial solution to this challenge, but a more radical scheme of more intensive monitoring by the accreditation authorities during periods of major transitions for accredited laboratories may be needed in order to avoid the need to abandon forma accreditation when performing major restructuring. It also holds true for the total testing process in clinical chemistry e.g. as depicted in Figure 1.

Comparisons are commonly made by stabilized samples which do not necessarily exhibit all the properties of natural patient samples. Natural patient samples are commutable ( 34 ) by definition and in practice whereas stabilized control materials may or may not be commutable. If the main purpose of a quality control system is to minimize the overall measurement uncertainty of all measurement systems and methods in an organization or geographical area, the use of fresh split patient samples is more efficient in finding clinically important bias and thereby for minimizing measurement uncertainty, especially when replicate measurements are used for minimizing random error. Open in a separate window Figure 3 External quality control (ECQ) organizations send out stabilized quality control samples which are analyzed as singletons and evaluated centrally (depicted as dotted arrows). The use of split fresh patient samples (depicted as the solid black ring) including the use of replicate measurements facilitates finding bias and thereby minimization of measurement uncertainty in an organization or a geographical area. A laboratory represented by the yellow circle may preferably serve as a mentor for a certain measurand for the other laboratories in the conglomerate of laboratories serving a certain population ( 28, 34 ). The use of fresh split patient samples for quality control makes common sense for several reasons:Split sample methods are laborious in the absence of effective computerized systems, but convenient when properly implemented ( 34, 35 ). Most laboratory organizations that introduce split sample methods prefer to continue their participation in external quality control schemes for the purpose of being able to compare their results more widely. Traceability It is comforting when other laboratories measure approximately the same measurement result for the same measurand in the same sample.

The analytical phase of the total testing chain The quality of the analytical phase of the total testing process has been and is being improved e.g. by the International Standardization Organization (ISO), e.g. through the ISO standard 17511:2003 detailing how the metrological traceability of values assigned to calibrators and control materials is established, The Joint Committee for Traceability in Laboratory Medicine (JCTLM) established in 2002 i.a. by the IFCC and the International Consortium for Harmonization of Clinical Laboratory Results (ICH-CLR) established by The American Association of Clinical Chemistry (AACC) in 2010. The Empower project ( 29 ) ( ) is a new promising and energetic newcomer in the field. Singleton measurement of control samples for quality control External quality control procedures in clinical chemistry traditionally focus on singleton- sample methods for quality control, which means that a control sample is measured only once before the result is reported. Singleton measurements are efficient for regulatory purposes since a minimum number of control samples (one) and measurements (one) are required. The drawback in some situations is that singletons are suboptimal for distinguishing between random error and bias as causes of the (total) error ( 31 ) ( Figure 2 ). Open in a separate window Figure 2 When a mean of a result is reported, the error of the mean is influenced both by bias and random error. The standard error of the mean is inversely related to the square root of the number of replicates and thus decreases quadratically with the number of replicates. As the number of replicates is increased, the contribution of the random error to the measurement error of the mean approaches zero, thereby improving the estimate of the bias. Bias is commonly estimated by participation in proficiency testing schemes (external quality control), using certified reference materials or by comparisons with reference methods ( 32, 33 ).

Regulatory issues are not of primary interest in many countries, certainly in the Nordic countries where the majority of labs are accredited according to ISO 15189. The laboratory organisation that the present writer belongs to caters for all laboratory services for 0,5 million inhabitants including point-of-care measurement methods. All laboratory services (including all specialties) are covered by the same accreditation. The total outcome is king in this environment, e.g. glycaemic control in the diabetic population, glycated haemoglobin and the contribution of the laboratory organization in optimizing treatment. It is a substantial challenge keeping the total CV% for HbA1c below 3% (total CV% for in the order of 100 measurement systems) as demanded by the diabetologists. This means that the performance of a single measurement system in external quality control systems has somewhat lower priority than the contribution of that measurement system to the overall CV% of HbA1c used for the entire population. In an environment of this kind, eliminating the contribution of the poorest performing measurement system (bias and random error) becomes particularly important. The extraanalytical phases of the total testing chain Academic organizations and producers of measurement systems and reagents are already heavily involved in improving the measurement part of the total testing process. The extraanalytical phases are also in need of substantial development. Current and future efforts in harmonizing measurement results in clinical chemistry are likely to include extensive cooperation between e.g. clinically active persons, the industry, standardization organizations, professional organizations and individual laboratories.

They do also include all aspects of the process from the clinical decision to use the clinical chemistry laboratory in diagnosis through preparing the patient, taking- and transporting the samples ( 44 ), measuring the samples and reporting the results and including the interpretation of the results in the clinical ( Figure 1 ). Statistical and graphical methods are essential for quality control and for calculating measurement uncertainty in the analytical phase. Statistical methods can also be applied in the preanalytical phase, e.g. for monitoring the occurrences of different kinds of preanalytical errors ( 56 ). There are limits to the extent which uncertainty in the analytical phase can be reduced. In contrast sources of uncertainty in the preanalytical phase can be practically eliminated by optimizing practices for e.g. patient preparation, phlebotomy and sample transport. Sample transport practices can be improved by investments in e.g. vacuum tube systems or by contracting certified regional transporters of samples, regularly monitoring their performance through sensors regularly sent with the samples. It is however, even more challenging to change the behavior of nurses, doctors and others responsible for patient preparation, phlebotomy and other preanalytical procedures outside the control of the laboratory. Different circumstances and individuals may also need different means of persuasion and education in order to minimize preanalytical errors. Time is well spent listening to the opinions of the users of the laboratory in different natural situations of co-operation. Advanced change management methods may be needed to accomplish the improvements needed. Neither of these technologies are amongst tools that have as yet been widely applied in clinical chemistry. Unfortunately there is no firm evidence as to the best methods to employ for the purpose of changing practices in healthcare ( 60 ).

However, the absence of bias does not, in on its own, constitute a proof of trueness. Thus inter-laboratory comparisons by themselves do not provide traceability of the participants’ results. It is the task of the participants’ themselves task to ensure the traceability of their results ( 36, 37 ). Making sure there is traceability of measurement methods of the laboratory takes knowledge, skills and common sense of the engaged persons and makes especially good common sense when the results from the laboratory are to be used in studies involving several countries or when decision limits established in large population studies are implemented. Harmonization Only a minor portion of common methods in clinical chemistry are currently traceable. It is, however, possible to harmonize ( 38 ) the majority of all measurement methods using commutable sample materials, including patient samples ( 39, 40 ). It is not an easy undertaking, but potentially very valuable for the patients. Routine laboratories of clinical chemistry with their abundance of patient samples are in an especially favourable position to participate in harmonization projects which optimally are done in co-operation with reference laboratories and with co-operation of the producers of the relevant measurement systems and reagents ( 41 ). Clinical chemistry pioneered in establishing the theoretical framework and practical routines for single sample-based external quality control (EQC) and batch-oriented routines for internal quality control. The total error of a measurement system estimated when measuring control samples is frequently the main emphasis of laboratories despite the fact that the total error only represents in the order of 20% of the diagnostic uncertainty related to laboratory medicine ( 30 ) ( Figure 4 ).

Open in a separate window Figure 4 The diagnostic uncertainty of a measurement result in a patient sample is a property of the measurement result itself, influenced by several uncertainty components, including biological variation, preanalytical variation, analytical variation (including uncertainty of the calibration) and postanalytical variation. The total error of an external quality control sample, in contrast, is influenced by substantially fewer and smaller uncertainty components and therefore represents a property of the measurement system itself. The total error is commonly used for regulatory or accreditation purposes. Measuring the concentration of a measurand in a stabilized control sample in internal quality control or in proficiency testing involves much fewer uncertainty factors than being requested to prepare a patient, take a sample, process the sample, transport the sample, analyse the sample and interpret the results in a clinical context ( Figure 4 ). The uncertainty factors involved when measuring a stabilized control sample are mainly the sample handling and the uncertainty of the measurement system. The total error estimated from singleton measurements of control samples has been found appropriate for regulatory purposes and an extensive theoretical and practical framework has been developed around its use ( 42, 43 ). According to a recent definition total analytical error (TAE) defines the interval that contains a specified proportion (usually 95% or 99%) of the distribution of analytical measurement differences between a measurement procedure operating in its stable incontrol state and a comparative measurement procedure that is either a definitive reference method or one that is traceable to one ( 43 ). Correspondingly allowable total error (ATE) is an analytical quality requirement that sets a limit for both the imprecision (random error) and bias (systematic error) that are tolerable in a single measurement or single test result.

Studies investigating the components of tailoring (identification of the most important determinants, selecting interventions to address the determinants) are especially lacking. Eliminating preanalytical errors deserve to rank highest on the list of priorities when attempting to continue to reduce diagnostic uncertainty. Structured and persistent work in this area means that personnel from the laboratory need to allocate sufficient time and efforts to this purpose. The fact that laboratories are seldom reimbursed for work in the preanalytical field, commonly means that sufficient emphasis and time is not allocated. There are several valuable current developments for defining analytical quality specifications ( 64 ) and overall diagnostic uncertainty (the combined uncertainty of all uncertainty components involved when using the laboratory to support diagnosis). However, increased emphasis on changing behaviours in the preanalytical field promise to be even more important than developing methods for adding uncertainties arising in the preanalytical phase to the overall diagnostic uncertainty of laboratory results. Postanalytical factors Co-operation with clinical disciplines on Health Technology Assessment (HTA), evidence- based medicine (EBM), guidelines etc.Hopefully this and other factors striving for excellence in healthcare can lead to projects aiming for harmonization and improvements of practice especially in the pre-and postanalytical parts of the total testing process. Important steps can be taken through many channels to improve the clinical use- and value of diagnostic procedures available through clinical chemistry. The laboratory and the clinicians are increasingly making co-operative projects in diagnostic guidelines and in the implementation of these guidelines. I personally believe joint projects of this kind may serve to facilitate other projects in the pre-and postanalytical areas ( 65 ).

Motivation, knowledge and common sense Laboratory medicine performs a highly practical high-volume production, but its cornerstone is intellectual. Motivation is the mother of all intellectual pursuits. All measures that increase the motivation of the employed in the laboratory contribute to the overall quality of the services. The most important factor for creating and maintaining motivation is the intellectual and organisational environment of the laboratory. Active participation in research projects, organisational and quality improvement projects is motivational. Collaborative projects directly aimed at improving the quality of the services to the patients have especially strong motivational effects when done in collaboration with workers in other areas of healthcare. Research projects in the basic sciences are also important as they bring and maintain knowledge in scientific philosophy and methods, thereby increasing understanding of the meaning and proper interpretation of data. It is a substantial challenge to maintain motivation throughout extended periods of time especially since demands for the reduction of costs and the number of workers are of regular occurrence. It is therefore important to regularly lift the focus from the mundane challenges of the laboratory and all its employees to the needs of the patients. External inspections of the quality assurance of the laboratory e.g. as part of ISO 15189 accreditation serves an important role in this context as it renews important commitments and focus on purpose. Common sense is especially important in the extraanalytical phases of the testing chain. Uncertainties in the preanalytical, postanalytical and clinical phases of the testing chain may be partially estimated as type A uncertainties ( 66 ) by calculating coefficients of variation.

In contrast to imprecision in the analytical phase which cannot be eliminated the goal should be to eliminate uncertainty components in the extraanalytical phases, in order to as much as possible eliminate their contribution to the overall diagnostic uncertainty ( Figure 4 ). This is a lofty but not an unrealistic goal. As a matter of fact, any improvements in phlebotomy practices, sample treatment, sample transport, interpretation of the results in clinical and biologic variation contexts will decrease the contributions of the extraanalytical phases to the overall diagnostic uncertainty. Such crucial improvements will not happen by themselves. Conclusion Clinical chemistry is in the process of paradigm shift from a primary focus on optimizing the measurement methods themselves to more intense collaboration with persons engaged in clinical work in order to reduce preanalytical, postanalytical and clinical uncertainties thereby improving the clinical use of laboratory methods. Manufacturers of measurement systems and reagents now shoulder the main responsibilities for the analytical process leaving time for optimizing preanalytical, postanalytical and clinical processes demanded e.g. by the accreditation standard ISO 15189. In order to shoulder these added responsibilities clinical chemistry needs to use its abundant common sense and learn from the humanities and from management-, business- and change sciences how to proceed in the interest of patients. Conflict of interest statement The authors stated that they have no conflicts of interest regarding the publication of this article References 1. Shewhart WA. Economic control of quality of manufactured product. The use of control charts in the clinical laboratory. Combined Shewhart-cusum control chart for improved quality control in clinical chemistry. Performance characteristics of rules for internal quality control: probabilities for false rejection and error detection. Ehrmeyer SS, Laessig RH.

Has compliance with CLIA requirements really improved quality in US clinical laboratories. Plebani M, Sciacovelli L, Chiozza ML, Panteghini M. Once upon a time: a tale of ISO 15189 accreditation. Plebani M, Sciacovelli L, Aita A, Padoan A, Chiozza ML. Quality indicators to detect pre-analytical errors in laboratory testing. Plebani M, Astion ML, Barth JH, Chen W, de Oliveira Galoro CA, Escuer MI. et al. Harmonization of quality indicators in laboratory medicine. A preliminary consensus. Plebani M, Sciacovelli L, Marinova M, Marcuccitti J, Chiozza ML. Quality indicators in laboratory medicine: A fundamental tool for quality and patient safety. Sciacovelli L, O’Kane M, Skaik YA, Caciagli P, Pellegrini C, Da Rin G. et al. Quality Indicators in Laboratory Medicine: from theory to practice. Theodorsson E, Magnusson B, Leito I. Bias in clinical chemistry. De Grande LA, Goossens K, Van Uytfanghe K, Stockl D, Thienpont LM. Bonini P, Plebani M, Ceriotti F, Rubboli F. Errors in laboratory medicine. On the use of total error and uncertainty in clinical chemistry. Thienpont LM. Quality specifications for reference methods. Theodorsson E. Validation and verification of measurement methods in clinical chemistry. Braga F, Infusino I, Panteghini M. Role and responsibilities of laboratory medicine specialists in the verification of metrological traceability of in vitro medical diagnostics. De Bievre P. Do interlaboratory comparisons provide traceability. Greg Miller W, Myers GL, Lou Gantzer M, Kahn SE, Schonbrunner ER, Thienpont LM. et al. Roadmap for harmonization of clinical laboratory measurement procedures. Thienpont LM, Van Uytfanghe K, De Leenheer AP. Reference measurement systems in clinical chemistry. Stepman HC, Tiikkainen U, Stockl D, Vesper HW, Edwards SH, Laitinen H. et al. Measurements for 8 common analytes in native sera identify inadequate standardization among 6 routine laboratory assays. Westgard JO, Westgard SA.

Quality control review: implementing a scientifically based quality control system. Westgard JO. Useful measures and models for analytical quality management in medical laboratories. Truchaud A, Le Neel T, Brochard H, Malvaux S, Moyon M, Cazaubiel M. New tools for laboratory design and management. Statland BE, Bokelund H, Winkel P. Factors contributing to intra-individual variation of serum constituents. 4. Effects of posture and torniquet application on variation of serum constituents in healthy subjects. Statland BE, Winkel P. Effects of preanalytical factors on the intraindividual variation of a nalytes in the blood of healthy subjects: consideration of preparation of the subject and time of venipuncture. Lippi G, Banfi G, Church S, Cornes M, De Carli G, Grankvist K. et al. Preanalytical quality improvement. Lippi G, Becan-McBride K, Behulova D, Bowen RA, Church S, Delanghe J. et al. Preanalytical quality improvement: in quality we trust. Lippi G, Chance JJ, Church S, Dazzi P, Fontana R, Giavarina D. et al. Preanalytical quality improvement: from dream to reality. Lippi G, Simundic AM, Plebani M. Phlebotomy, stat testing and laboratory organization: an intriguing relationship. Lima-Oliveira G, Lippi G, Luca Salvagno G, Picheth G, Cesare Guidi G. Laboratory diagnostics and quality of blood collection. Plebani M, Sciacovelli L, Aita A, Chiozza ML. Harmonization of pre-analytical quality indicators. Corbin JM, Strauss AL. Denzin NK, Lincoln YS. Baker R, Camosso-Stefinovic J, Gillies C, Shaw EJ, Cheater F, Flottorp S. et al. Tailored interventions to address determinants of practice. Fearing G, Barwick M, Kimber M. Clinical transformation: Manager’s perspectives on implementation of evidence-based practice. Bernhardsson S, Larsson ME, Eggertsen R, Olsen MF, Johansson K, Nilsen P. et al.