Machine learning-based clinical decision support using laboratory data

Artificial intelligence (AI) and machine learning (ML) are becoming vital in laboratory medicine and the broader context of healthcare. In this review article, we summarized the development of ML models and how they contribute to clinical laboratory workflow and improve patient outcomes. The process of ML model development involves data collection, data cleansing, feature engineering, model development, and optimization. These models, once finalized, are subjected to thorough performance assessments and validations. Recently, due to the complexity inherent in model development, automated ML tools were also introduced to streamline the process, enabling non-experts to create models. Clinical Decision Support Systems (CDSS) use ML techniques on large datasets to aid healthcare professionals in test result interpretation. They are revolutionizing laboratory medicine, enabling labs to work more efficiently with less human supervision across pre-analytical, analytical, and post-analytical phases. Despite contributions of the ML tools at all analytical phases, their integration presents challenges like potential model uncertainties, black-box algorithms, and deskilling of professionals. Additionally, acquiring diverse datasets is hard, and models' complexity can limit clinical use. In conclusion, ML-based CDSS in healthcare can greatly enhance clinical decision-making. However, successful adoption demands collaboration among professionals and stakeholders, utilizing hybrid intelligence, external validation, and performance assessments.

Approaching sustainability in Laboratory Medicine

INTRODUCTION

Clinical laboratories and the total testing process are major consumers of energy, water, and hazardous chemicals, and produce significant amounts of biomedical waste. Since the processes in the clinical laboratory and the total testing process go hand in hand it mandates a holistic, and comprehensive approach towards sustainability.

CONTENT

This review article identifies the various sources and activities in Laboratory Medicine that challenge sustainability and also discusses the various approaches that can be implemented to achieve sustainability in laboratory operations to reduce the negative impact on the environment.

SUMMARY

The article highlights how the integration of technological advancements, efficient resource management, staff training and sensitization, protocol development towards sustainability, and other environmental considerations contributes significantly to a sustainable healthcare ecosystem.

OUTLOOK

Variables and resources that negatively impact the environment must be identified and addressed comprehensively to attain a long-lasting level of carbon neutrality.

The total testing process harmonization: the case study of SARS-CoV-2 serological tests

The total testing process harmonization is central to laboratory medicine, leading to the laboratory test's effectiveness. In this opinion paper the five phases of the TTP are analyzed, describing, and summarizing the critical issues that emerged in each phase of the TTP with the SARS-CoV-2 serological tests that have affected their effectiveness. Testing and screening the population was essential for defining seropositivity and, thus, driving public health policies in the management of the COVID-19 pandemic. However, the many differences in terminology, the unit of measurement, reference ranges and parameters for interpreting results make analytical results difficult to compare, leading to the general confusion that affects or completely precludes the comparability of data. Starting from these considerations related to SARS-CoV-2 serological tests, through interdisciplinary work, the authors have highlighted the most critical points and formulated proposals to make total testing process harmonization effective, positively impacting the diagnostic effectiveness of laboratory tests.

The European Register of Specialists in Clinical Chemistry and Laboratory Medicine: code of conduct, version 3 - 2023

Whilst version 2 focussed on the professional conduct expected of a Specialist in Laboratory Medicine, version 3 builds on the responsibilities for ethical conduct from point of planning to point of care. Particular responsibilities that are outlined include: - The need for evidence when planning a new service, providing assurance that a new test does not do harm - Maintaining respect for patient confidentiality, their religious/ethnic beliefs, the need for informed consent to test, agreement on retrospective use of samples as part of governance envelopes in the pre-analytical phase - Ensuring respect for patient autonomy in the response to untoward results generated in the analytical phase - Supporting the safety of patients in the post-analytical phase through knowledge-based interpretation and presentation of results - The duty of candour to disclose and respond to error across the total testing process - Leading initiatives to harmonise and standardise pre-analytical, analytical and post-analytical phases to ensure more consistent clinical decision making with utilisation of demand management to ensure more equitable access to scarce resources - Working with emerging healthcare providers beyond the laboratory to ensure consistent application of high standards of clinical care In identifying opportunities for wider contributions to resolving ethical challenges across healthcare the need is also highlighted for more external quality assurance schemes and ethics-based quality indicators that span the total testing process.

'Penelope test': a practical instrument for checking appropriateness of laboratory tests

In medical laboratories, the appropriateness challenge directly revolves around the laboratory test and its proper selection, data analysis, and result reporting. However, laboratories have also a role in the appropriate management of those phases of total testing process (TTP) that traditionally are not under their direct control. So that, the laboratory obligation to act along the entire TTP is now widely accepted in order to achieve better care management. Because of the large number of variables involved in the overall TTP structure, it is difficult to monitor appropriateness in real time. However, it is possible to retrospectively reconstruct the body of the clinical process involved in the management of a specific laboratory test to track key passages that may be defective or incomplete in terms of appropriateness. Here we proposed an appropriateness check-list scheme along the TTP chain to be potentially applied to any laboratory test. This scheme consists of a series of questions that healthcare professionals should answer to achieve laboratory test appropriateness. In the system, even a single lacking answer may compromise the integrity of all appropriateness evaluation process as the inability to answer may involve a significant deviation from the optimal trajectory, which compromise the test appropriateness and the quality of subsequent steps. Using two examples of the check-list application, we showed that the proposed instrument may offer an objective help to avoid inappropriate use of laboratory tests in an integrated way involving both laboratory professionals and user clinicians.

Risk assessment of the total testing process based on quality indicators with the Sigma metrics

Background Evidence-based evaluation of laboratory performances including pre-analytical, analytical and post-analytical stages of the total testing process (TTP) is crucial to ensure patients receiving safe, efficient and effective care. To conduct risk assessment, quality management tools such as Failure Mode and Effect Analysis (FMEA) and the Failure Reporting and Corrective Action System (FRACAS) were constantly used for proactive or reactive analysis, respectively. However, FMEA and FRACAS faced big challenges in determining the scoring scales and failure prioritization in the assessment of real-world cases. Here, we developed a novel strategy, by incorporating Sigma metrics into risk assessment based on quality indicators (QIs) data, to provide a more objective assessment of risks in TTP. Methods QI data was collected for 1 year and FRACAS was applied to produce the risk rating based on three variables: (1) Sigma metrics for the frequency of defects; (2) possible consequence; (3) detection method. The risk priority number (RPN) of each QI was calculated by a 5-point scale score, where a value of RPN > 50 was rated as high-risk. Results The RPNs of two QIs in post-analytical phase (TAT of Stat biochemistry analyte and Timely critical values notification) were above 50 which required rigorous monitoring and corrective actions to eliminate the high risks. Nine QIs (RPNs between 25 and 50) required further investigation and monitoring. After 3 months of corrective action the two identified high-risk processes were successfully reduced. Conclusions The strategy can be implemented to reduce identified risk and assuring patient safety.

The rise in preanalytical errors during COVID-19 pandemic

Introduction

The COVID-19 pandemic has posed several challenges to clinical laboratories across the globe. Amidst the outbreak, errors occurring in the preanalytical phase of sample collection, transport and processing, can further lead to undesirable clinical consequences. Thus, this study was designed with the following objectives: (i) to determine and compare the blood specimen rejection rate of a clinical laboratory and (ii) to characterise and compare the types of preanalytical errors between the pre-pandemic and the pandemic phases.

Materials and methods

This retrospective study was carried out in a trauma-care hospital, presently converted to COVID-19 care centre. Data was collected from (i) pre-pandemic phase: 1^st October 2019 to 23^rd March 2020 and (ii) pandemic phase: 24^th March to 31^st October 2020. Blood specimen rejection rate was calculated as the proportion of blood collection tubes with preanalytical errors out of the total number received, expressed as percentage.

Results

Total of 107,716 blood specimens were screened of which 43,396 (40.3%) were received during the pandemic. The blood specimen rejection rate during the pandemic was significantly higher than the pre-pandemic phase (3.0% versus 1.1%; P < 0.001). Clotted samples were the commonest source of preanalytical errors in both phases. There was a significant increase in the improperly labelled samples (P < 0.001) and samples with insufficient volume (P < 0.001), whereas, a significant decline in samples with inadequate sample-anticoagulant ratio and haemolysed samples (P < 0.001).

Conclusion

In the ongoing pandemic, preanalytical errors and resultant blood specimen rejection rate in the clinical laboratory have significantly increased due to changed logistics. The study highlights the need for corrective steps at various levels to reduce preanalytical errors in order to optimise patient care and resource utilisation.

The response of total testing process in clinical laboratory medicine to COVID-19 pandemic

Introduction

Following a pandemic, laboratory medicine is vulnerable to laboratory errors due to the stressful and high workloads. We aimed to examine how laboratory errors may arise from factors, e.g., flexible working order, staff displacement, changes in the number of tests, and samples will reflect on the total test process (TTP) during the pandemic period.

Materials and methods

In 12 months, 6 months before and during the pandemic, laboratory errors were assessed via quality indicators (QIs) related to TTP phases. QIs were grouped as pre-, intra- and postanalytical. The results of QIs were expressed in defect percentages and sigma, evaluated with 3 levels of performance quality: 25^th, 50^th and 75^th percentile values.

Results

When the pre- and during pandemic periods were compared, the sigma value of the samples not received was significantly lower in pre-pandemic group than during pandemic group (4.7σ vs. 5.4σ, P = 0.003). The sigma values of samples transported inappropriately and haemolysed samples were significantly higher in pre-pandemic period than during pandemic (5.0σ vs. 4.9σ, 4.3σ vs. 4.1σ; P = 0.046 and P = 0.044, respectively). Sigma value of tests with inappropriate IQC performances was lower during pandemic compared to the pre-pandemic period (3.3σ vs. 3.2σ, P = 0.081). Sigma value of the reports delivered outside the specified time was higher during pandemic than pre-pandemic period (3.0σ vs. 3.1σ, P = 0.030).

Conclusion

In all TTP phases, some quality indicators improved while others regressed during the pandemic period. It was observed that preanalytical phase was affected more by the pandemic.

Errors within the total laboratory testing process, from test selection to medical decision-making - A review of causes, consequences, surveillance and solutions

Laboratory analyses are crucial for diagnosis, follow-up and treatment decisions. Since mistakes in every step of the total testing process may potentially affect patient safety, a broad knowledge and systematic assessment of laboratory errors is essential for future improvement. In this review, we aim to discuss the types and frequencies of potential errors in the total testing process, quality management options, as well as tentative solutions for improvement. Unlike most currently available reviews on this topic, we also include errors in test-selection, reporting and interpretation/action of test results. We believe that laboratory specialists will need to refocus on many process steps belonging to the extra-analytical phases, intensifying collaborations with clinicians and supporting test selection and interpretation. This would hopefully lead to substantial improvements in these activities, but may also bring more value to the role of laboratory specialists within the health care setting.

Preanalytical Phase Errors: Experience of a Central Laboratory

Introduction: The study intends to observe the frequency of preanalytical phase errors both inside and outside the clinical laboratory according to certain quality indicators (QIs).

Methods: The one-week observation focused on 73 nurses drawing blood from 337 patients. It was performed in two stages: the observation of blood collection up to the receipt of the samples, and the receipt of the samples up to the analytical phase. The data pertaining to the number of patients, tests, and rejection rates were obtained from the laboratory information system (LIS) for the one-week and the one-year period and compared with the observational data.

Results: The process of blood sample collection from 337 patients taken into 1347 tubes was observed. Although the majority of the nurses (78%) used safety needles, the safety mechanism was properly activated only in 38% of the interventions. Evaluation of biochemistry tubes (n=971) revealed the following: the incorrect fill volume error was 40%; the hemolysis was seen by 17%, and the clotted sample and fibrin were observed by 6%. The incorrect fill volume error was 12% and 20% in ethylenediaminetetraacetic acid (EDTA) and citrated tubes, respectively. Clotted samples and platelet clumps were seen in 1% of EDTA tubes.

Conclusion: The study confirms the relative frequency of preanalytical phase error occurring inside and outside of the laboratory.

Six Sigma revisited: We need evidence to include a 1.5 SD shift in the extraanalytical phase of the total testing process

The Six Sigma methodology has been widely implemented in industry, healthcare, and laboratory medicine since the mid-1980s. The performance of a process is evaluated by the sigma metric (SM), and 6 sigma represents world class performance, which implies that only 3.4 or less defects (or errors) per million opportunities (DPMO) are expected to occur. However, statistically, 6 sigma corresponds to 0.002 DPMO rather than 3.4 DPMO. The reason for this difference is the introduction of a 1.5 standard deviation (SD) shift to account for the random variation of the process around its target. In contrast, a 1.5 SD shift should be taken into account for normally distributed data, such as the analytical phase of the total testing process; in practice, this shift has been included in all type of calculations related to SM including non-normally distributed data. This causes great deviation of the SM from the actual level. To ensure that the SM value accurately reflects process performance, we concluded that a 1.5 SD shift should be used where it is necessary and formally appropriate. Additionally, 1.5 SD shift should not be considered as a constant parameter automatically included in all calculations related to SM.

Roots of the total testing process

Laboratory professionals can contribute to improvement of diagnosis in the context of the total testing process (TTP), a multidisciplinary framework complementary to the diagnostic process. While the testing process has been extensively characterized in the literature, needed is accurate identification of the source of the term "total testing process". This article clarifies first appearance of the term in the literature and supplies a formal definition.

National surveys on 15 quality indicators for the total testing process in clinical laboratories of China from 2015 to 2017

Background As effective quality management tools, quality indicators (QIs) are widely used in laboratory medicine. This study aimed to analyze the results of QIs, identify errors and provide quality specifications (QSs) based on the state-of-the-art. Methods Clinical laboratories all over China participated in the QIs survey organized by the National Health Commission of People' Republic of China from 2015 to 2017. Most of these QIs were selected from a common model of QIs (MQI) established by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC). All participants were asked to submit general information and original QIs data through a medical quality control data collection system. The results of QIs were reported in percentages and sigma, except turnaround time (TAT) which was measured in minutes. The 25th, 50th and 75th percentiles were, respectively, calculated as three levels of QSs, which were defined starting from the model proposed during the 1st Strategic Conference of the EFLM on "Defining analytical performance 15 years after the Stockholm Conference on Quality Specification in Laboratory Medicine". Results A total of 76 clinical laboratories from 25 provinces in China continuously participated in this survey and submitted complete data for all QIs from 2015 to 2017. In general, the performance of all reported QIs have improved or at least kept stable over time. Defect percentages of blood culture contamination were the largest in the pre-analytical phase. Intra-laboratory TAT was always larger than pre-examination TAT. Percentage of tests covered by inter-laboratory comparison was relatively low than others in the intra-analytical phase. The performances of critical values notification and timely critical values notification were the best with 6.0σ. The median sigma level of incorrect laboratory reports varied from 5.5σ to 5.7σ. Conclusions QSs of QIs provide useful guidance for laboratories to improve testing quality. Laboratories should take continuous quality improvement measures in all phases of total testing process to ensure safe and effective tests.

Terminology, units and reporting - how harmonized do we need to be?

Harmonization initiatives in laboratory medicine seek to eliminate or reduce illogical variations in service to patients, clinicians and other healthcare professionals. Significant effort will be required to achieve consistent application of terminology, units and reporting across laboratory testing providers. Current variations in practice for nomenclature, reference intervals, flagging, units, standardization and traceability between analytical methods, and presentation of cumulative result data are inefficient and inconvenient, or worse yet, patient safety risks. All aspects of laboratory service across the "total testing process" ultimately depend on concise, reliable communication. Clinical terminologies (e.g. SNOMED-CT, LOINC, IFCC/IUPAC NPU) provide a mechanism to correctly identify an analyte or panel of tests within a request for testing and communicate the results back to the clinician or electronic health record (EHR). Electronic systems for requesting and reporting laboratory testing are said to be interoperable when reliable connection and communication of content occur. Modern electronic reports and EHRs will provide greater flexibility and functionality, but also require effective guidelines or standards to ensure consistent representation of laboratory data. Programs to harmonize service in these areas require ongoing local, national and international efforts and should incorporate stakeholders from laboratories, medical staff, information technology and informatics specialists, patient representatives and government. The process of identifying harmonized best practice, then ensuring uptake across many laboratory testing providers, is generally iterative rather than "one off". New opportunities for additional harmonization will be generated as analytical performance, standardization and traceability, and diagnosis and treatment continue to evolve.

Irregular analytical errors in diagnostic testing - a novel concept

BACKGROUND

In laboratory medicine, routine periodic analyses for internal and external quality control measurements interpreted by statistical methods are mandatory for batch clearance. Data analysis of these process-oriented measurements allows for insight into random analytical variation and systematic calibration bias over time. However, in such a setting, any individual sample is not under individual quality control. The quality control measurements act only at the batch level. Quantitative or qualitative data derived for many effects and interferences associated with an individual diagnostic sample can compromise any analyte. It is obvious that a process for a quality-control-sample-based approach of quality assurance is not sensitive to such errors.

CONTENT

To address the potential causes and nature of such analytical interference in individual samples more systematically, we suggest the introduction of a new term called the irregular (individual) analytical error. Practically, this term can be applied in any analytical assay that is traceable to a reference measurement system. For an individual sample an irregular analytical error is defined as an inaccuracy (which is the deviation from a reference measurement procedure result) of a test result that is so high it cannot be explained by measurement uncertainty of the utilized routine assay operating within the accepted limitations of the associated process quality control measurements.

SUMMARY

The deviation can be defined as the linear combination of the process measurement uncertainty and the method bias for the reference measurement system. Such errors should be coined irregular analytical errors of the individual sample. The measurement result is compromised either by an irregular effect associated with the individual composition (matrix) of the sample or an individual single sample associated processing error in the analytical process.

OUTLOOK

Currently, the availability of reference measurement procedures is still highly limited, but LC-isotope-dilution mass spectrometry methods are increasingly used for pre-market validation of routine diagnostic assays (these tests also involve substantial sets of clinical validation samples). Based on this definition/terminology, we list recognized causes of irregular analytical error as a risk catalog for clinical chemistry in this article. These issues include reproducible individual analytical errors (e.g. caused by anti-reagent antibodies) and non-reproducible, sporadic errors (e.g. errors due to incorrect pipetting volume due to air bubbles in a sample), which can both lead to inaccurate results and risks for patients.

Defining a roadmap for harmonizing quality indicators in Laboratory Medicine: a consensus statement on behalf of the IFCC Working Group "Laboratory Error and Patient Safety" and EFLM Task and Finish Group "Performance specifications for the extra-analytical phases"

The improving quality of laboratory testing requires a deep understanding of the many vulnerable steps involved in the total examination process (TEP), along with the identification of a hierarchy of risks and challenges that need to be addressed. From this perspective, the Working Group "Laboratory Errors and Patient Safety" (WG-LEPS) of International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) is focusing its activity on implementation of an efficient tool for obtaining meaningful information on the risk of errors developing throughout the TEP, and for establishing reliable information about error frequencies and their distribution. More recently, the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) has created the Task and Finish Group "Performance specifications for the extra-analytical phases" (TFG-PSEP) for defining performance specifications for extra-analytical phases. Both the IFCC and EFLM groups are working to provide laboratories with a system to evaluate their performances and recognize the critical aspects where improvement actions are needed. A Consensus Conference was organized in Padova, Italy, in 2016 in order to bring together all the experts and interested parties to achieve a consensus for effective harmonization of quality indicators (QIs). A general agreement was achieved and the main outcomes have been the release of a new version of model of quality indicators (MQI), the approval of a criterion for establishing performance specifications and the definition of the type of information that should be provided within the report to the clinical laboratories participating to the QIs project.

Advantages and Challenges of Dried Blood Spot Analysis by Mass Spectrometry Across the Total Testing Process

INTRODUCTION

Through the introduction of advanced analytical techniques and improved throughput, the scope of dried blood spot testing utilising mass spectrometric methods, has broadly expanded. Clinicians and researchers have become very enthusiastic about the potential applications of dried blood spot based mass spectrometric applications. Analysts on the other hand face challenges of sensitivity, reproducibility and overall accuracy of dried blood spot quantification. In this review, we aim to bring together these two facets to discuss the advantages and current challenges of non-newborn screening applications of dried blood spot quantification by mass spectrometry.

METHODS

To address these aims we performed a key word search of the PubMed and MEDLINE online databases in conjunction with individual manual searches to gather information. Keywords for the initial search included; "blood spot" and "mass spectrometry"; while excluding "newborn"; and "neonate". In addition, databases were restricted to English language and human specific. There was no time period limit applied.

RESULTS

As a result of these selection criteria, 194 references were identified for review. For presentation, this information is divided into: 1) clinical applications; and 2) analytical considerations across the total testing process; being pre-analytical, analytical and post-analytical considerations.

CONCLUSIONS

DBS analysis using MS applications is now broadly applied, with drug monitoring for both therapeutic and toxicological analysis being the most extensively reported. Several parameters can affect the accuracy of DBS measurement and further bridge experiments are required to develop adjustment rules for comparability between dried blood spot measures and the equivalent serum/plasma values. Likewise, the establishment of independent reference intervals for dried blood spot sample matrix is required.

Appropriateness of diagnostics tests

The evolution of the concept of 'appropriateness', in the three past decades, from 'no harm' and 'no waste' to 'medical decision-making' and 'determining outcomes' highlights two main points: its foundation is evidence-based medicine, and it is a quality of every phase of the total testing process, not only for the selection of tests. Nevertheless, appropriateness in Laboratory Hematology, as well as in Laboratory Medicine, is an elusive concept: 'Appropriateness' interplays with 'patient's safety', 'healthcare costs', 'clinical decision-making', and 'effectiveness', and the criteria for appropriateness, mainly adherence to clinical guidelines, are often not evidence-based and not always consensus-based. Moreover, practising appropriateness is a complex issue because of the ambiguity of the criteria and targets, the never-ending work of implementing guidelines and their audit, and the uniqueness of the clinical situation of the individual patient. Authors agree on some practical rules: establishing a multidisciplinary and multiprofessional team, choosing carefully clinical targets, finding or building evidences, sharing guidelines with clinicians, choosing adequate tools for changing, working hard on implementation, identifying the 'right' laboratory methods and processes, checking progress indefinitely, providing information, interpretations, and consultations, and promoting feedback and audits. The success depends on the 'right' combination of educational, operative, and reinforcing interventions. Competences in organization, in implementation science, and in interpersonal relationship management are essential as well as knowledge and experience in Hematology, not only in Laboratory Hematology.

Harmonization Initiatives in Europe

INTRODUCTION

Modern medicine is more and more based on protocols and guidelines; clinical laboratory data play very often a relevant role in these documents and for this reason the need for their harmonization is increasing. To achieve harmonized results the harmonization process must not be limited to only the analytical part, but has to include the pre- and the post-analytical phases.

RESULTS

To fulfill this need the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) has started several initiatives. A Working Group on harmonization of the total testing process (WG-H) has been created with the aims of: 1) surveying and summarizing national European and pan European harmonization initiatives; 2) promoting and coordinating the dissemination of especially promising harmonization initiatives among the EFLM member societies; and 3) taking initiatives to harmonize nomenclature, units and reference intervals at a European level. The activity of the WG started this year with a questionnaire targeted at surveying the status of various harmonization activities, especially those in the pre- and post-analytical phase categories, among the European laboratory medicine societies.

CONCLUSIONS

Based on the results of the questionnaire, some activities promoting the dissemination of best practice in blood sampling, sample storage and transportation, in collaboration with WG on the pre-analytical phase, will be promoted, and initiatives to spread to all the European countries the use of SI units in reporting, will be undertaken. Moreover, EFLM has created a Task and Finish Group on standardization of the color coding for blood collection tube closures that is actively working to accomplish this difficult task through collaboration with manufacturers.

Harmonization of Clinical Laboratory Test Results

Clinical laboratory testing is now a global activity with laboratories no longer working in isolation but as regional and national networks, and often at international levels. We now have all of the electronic gadgetry via internet technology at our fingertips to rapidly and accurately measure and report on laboratory testing but are our test results harmonized?

Harmonization of Clinical Laboratory Information - Current and Future Strategies

According to a patient-centered viewpoint, the meaning of harmonization in the context of laboratory medicine is that the information should be comparable irrespective of the measurement procedure used and where and/or when a measurement is made. Harmonization represents a fundamental aspect of quality in laboratory medicine as its ultimate goal is to improve patient outcomes through the provision of an accurate and actionable laboratory information. Although the initial focus has to a large extent been to harmonize and standardize analytical processes and methods, the scope of harmonization goes beyond to include all other aspects of the total testing process (TTP), such as terminology and units, report formats, reference intervals and decision limits, as well as tests and test profiles request and criteria for interpretation. Two major progresses have been made in the area of harmonization in laboratory medicine: first, the awareness that harmonization should take into consideration not only the analytical phase but all steps of the TTP, thus dealing with the request, the sample, the measurement, and the report. Second, as the processes required to achieve harmonization are complicated, a systematic approach is needed. The International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) has played a fundamental and successful role in the development of standardized and harmonized assays, and now it should continue to work in the field through the collaboration and cooperation with many other stakeholders.

Pre and Post Examination Aspects

After a long-standing tradition of analytical quality and analytical quality control programs, most medical laboratories that are aware of the need for total quality management, are experiencing new systems designed to assure quality throughout the entire total testing process, from the pre-analytical to the post-analytical steps. The availability of a new International Standard, ISO 15189:2003, specifically developed and designed to satisfy the requirements for quality management and competence in medical laboratories, should promote the harmonization of accreditation programs at an international level, and implementation of an effective quality system at a local level. The importance of the pre- and post-analytical phases are well recognized in the new International Standard and, therefore, efforts to comply with this standard might assure an approach that safeguards and continuously improves total quality in medical laboratories.