Daria Pašalić
Department of Medical Chemistry, Biochemistry and Clinical Chemistry
Zagreb University School of Medicine
Šalata ul 2.
10 000 Zagreb, Croatia
Phone +385 (1) 4590 205; +385 (1) 4566 940
E-mail: dariapasalic [at] gmail [dot] com

Useful links


Harmonisation of reference ranges


Annette Thomas. Harmonisation of reference ranges. Biochemia Medica 2015;25(Suppl 1):S49-S51.

Consultant Clinical Biochemist, Director of Weqas, Cardiff, UK


In 2010, the Welsh Government provided funding for a multimillion pound initiative to provide a single Laboratory Information System (LIMS) across the country. NHS Wales at that time had 18 Hospital Laboratories using 8 different IT systems and undertaking more than 21 million diagnostic tests each year with demand continuing to rise. The new LIMS was part of the drive to modernize pathology services across Wales, to provide a networked national system that would improve quality and efficiency, standardize practice and improve governance. Integration of the single LIMS with patients’ medical records would allow tests results to be shared and viewed, regardless of where the patient received care, or where the test was undertaken. This provided a huge challenge to the Pathology Laboratories to agree on a standardised configuration of the LIMS prior to its implementation in 2012. For Biochemistry this agreement was required for over 300 tests. To achieve this a Standardization group was established with representation from each of the Health Boards with the aim to agree on: test/profile names, codes, units, reference and alert ranges, testing strategies, and minimum repeat requesting intervals. The process used by Pathology Harmony UK was adopted. The agreed ranges were derived by surveys of ranges in current use and basing a judgement of the most appropriate as a consensus weighted by evidence based literature review. Where consensus was not appropriate, analytical platform or method specific reference ranges were developed. These were derived from manufacturer’s kit inserts, or, where these were unreliable, from literature based evidence. Pathology Harmony UK ranges and units were used for serum sodium, potassium, urea, chloride, bicarbonate, phosphate, magnesium, albumin, total protein, bilirubin, urate, osmolality, carbamazepine, phenobarbitone, phenytoin, theophylline, and lithium. For alkaline phosphatase, it was agreed that all laboratories would use the IFCC method, for creatine kinase a common range for white Caucasians only was agreed, platform specific ranges were developed for the remaining enzymes. Adjusted calcium equations were derived for each platform to provide normalised mean calcium of 2.4 mmol/L. Platform specific reference ranges were developed for serum ACE, calcium, bilirubin conjugate, lactate and the majority of the immunoassay methods. Supporting evidence were provided by External Quality Assessment organisations, Professional bodies, Advice from Clinicians, National Laboratory of Medicine Catalogue Editorial Principles, All Wales Clinical Biochemistry Audit Group, NICE guidance, National Service Frameworks and peer-reviewed journals.

e-mail: annette [at] weqas [dot] com



Analytical quality based on risk assessment


Adriana Unić. Analytical quality based on risk assessment.Biochemia Medica 2015;25(Suppl 1):S51-S52.

Clinical department of laboratory diagnostics, University hospital Dubrava, Zagreb, Croatia


Laboratory test results have major impact on clinical decision-making and thus influence the patient outcome. Therefore it is the responsibility of each laboratory to ensure accurate and reliable test results.

In the area of analytical quality there are several quality strategies available in order to reduce risk in method failure. First of all it is an internal quality control.

Internal quality control in the clinical laboratory is the process used to monitor and evaluate results of control samples. Quality control material should approximate the same matrix as patient specimens and should be treated in the exact same manner. Furthermore, the use of statistical methods allows us to establish a significant change in the method performance and thus prevent the false results.

Internal quality control strategy is still largely based on the requirements of the regulatory authorities and in most cases implies a quality control run at least once a day at two concentration levels. However, it is clear that the internal quality control strategy cannot be universal for all methods in the laboratory.

Therefore, new laboratory guidelines recommend implementation of individual internal quality control strategy based on risk assessment. Implementation plan should identify the control samples, specify their frequency, corrective actions and possible errors. Implementation of individual quality control strategy requires: information about the testing procedure; risk assessment analysis; developing of quality control plan to mitigate risk; implementation, monitoring and updating of the plan.

Study of specifications obtained by the method analytical validation is the first step in implementation of individual internal quality control strategy. The laboratory has to verify the verification procedure obtained by the manufacturer and thus ensure that the test procedure is suitable for its intended use. Setting the acceptance criteria is the most important strategy in order to reduce possible errors. When we determine that the test procedure is suitable, implementation of internal quality control strategy is the next step. The decision on acceptance or rejection of the results of internal quality control measurement is a key process in order to ensure the quality of test results. Internal quality control measurement frequency, the number of required control samples and eligibility of results can be defined using the Six Sigma quality system. Sigma value is accepted as a universal measure of quality and can be used to assess the analytical performance of the laboratory process. The number of false results per million is a measure of the analytical quality of laboratory process. Quality strategy, based on the Sigma value, recommend the carefully design of internal quality control strategy in order to detect cause and reduce the number of unreliable test results. After defining the strategy, monitoring and analysis of performance, identification of false results and possible improvements , laboratory have to evaluate the rate of false results in order to quantify their frequency then use the Sigma quality system in order to assess the risk of false patient results.

Only carefully designed internal quality control strategy can ensure the accurate and reliable test results.

e-mail: adrianaunic [at] gmail [dot] com



Uncertainty of measurement


Ivana Ćelap. Uncertainty of measurement.Biochemia Medica 2015;25(Suppl 1): S53-S54.

University Department of Chemistry, Sestre Milosrdnice University Hospital, Zagreb, Croatia


The need for comparability of the laboratory test results created the need for the calculation of the uncertainty of measurement. According EN ISO 15189 (3.17.), “uncertainty of measurement is a parameter associated with the result of a measurement, that characterises the dispersion of the values that could reasonably be attributed to the measurand.” Respectively, uncertainty of measurement gives us information on the range of values where the result can be found with the same probability. The uncertainty of measurement is not an indicator of the measuring system error but the variability of measuring conditions over time. Therefore, it is a property of the result of measurement.

Many international institutes for standards have published the guidelines which in details describe sources of measurement uncertainty as well as different approaches for calculation of the uncertainty of measurement. However, there is controversy which sources of variability have to be included in uncertainty budget and which ones could be omitted. Further, expressing of the uncertainty depends on the laboratory test and/or concentration of the measurand.

In laboratory process, source of uncertainty is every component of the process which contributes to uncertainty and could be found in preanalytical, analytical and postanalytical phase. Since the sources of uncertainty in preanalytical and postanalytical phase could not be quantified, calculation of the uncertainty of measurement can be made only for analytical phase.

Every source of uncertainty has to be expressed as standard uncertainty and contributes to combined standard uncertainty with the other standard uncertainties in the specific measurement. Combined standard uncertainty of measurement multiplied with the coverage factor (k), k=2, is termed expanded uncertainty and covers 95% results of measurement.

Uncertainty of measurement information could be used for i.e. estimation of differences between two measurements and/or estimation of quality specifications set up.

Uncertainty of measurement information still is not a part of laboratory report but must be available to clients of the accredited laboratories.

When interpreting laboratory test results near diagnostic cut-off or near limits of reference interval, one should bear in mind information on uncertainty of measurement.

Sources of uncertainty, approaches in establishing the uncertainty budget, calculation of uncertainty of measurement and the use of the obtained data for different laboratory tests will be presented.

e-mail: ivana [dot] celap [at] gmail [dot] com