Refik Saydam Hygiene Center quality management model (original) (raw)
Related papers
2017
OBJECTIVE To estimate relative expanded uncertainty measurement of routine clinical chemistry analytes for international organisation for standardisation 15189 accreditation. METHODS This cross-sectional study was conducted at Dow International Medical College, Karachi, from September 2013 to May 2014. During the process of international organisation for standardisation 15189 accreditation, measurement uncertainty was estimated for 13 clinical chemistry analytes using top-down approach. Relative combined uncertainty of each analyte was calculated by combining uncertainties of imprecision, bias and calibrators. Results of estimated imprecision, bias and expanded uncertainties were observed for allowable imprecision, bias and total analytical error for the respective analyte.. RESULTS Uncertainties of imprecision were found within acceptable limits for all analytes except total protein (2.4% vs. 1.3%). Uncertainties of bias of all analytes were found within allowable limits. Relative ...
COURSE NOTES A model for calculating measurement uncertainty in medical laboratories
Revista Român de Medicin de …, 2010
Introduction: All medical laboratories that require recognition for competency assessment have to estimate the uncertainty of measurement of assay test results "where relevant and possible" (ISO 15189:2007 Medical laboratories-Particular requirements for quality and competence). The repeated quantitative examination of an analyte with the same method will offer more or less different results. This is happening because the outcome of an assay depends not only upon the analyte itself, but also upon few error factors that could yield doubts about the obtained result. The mathematical, quantitative expression of this doubt is known as uncertainty of measurement (UM). Methods: It is the responsibility of each medical laboratory to identify all error sources that can be quantified and converted in standard deviations that could be used to estimate the type A or B of uncertainty. In the case of Romanian medical laboratories, the European Accreditation (EA) accepted as reference documents for UM estimation the Guide to the Expression of Uncertainty in Measurement (GUM) and Romanian Standard SR ENV 13005. Discussion and conclusion: In this paper, authors present and discuss the modalities of UM estimation in two different situations: when the used reference materials (calibrators) are or are not traceable to certified reference materials (CRM). Complete and informative UM reporting can only lead to better decisions in healthcare.
Selcuk Tip Dergisi, 2021
Amaç: Laboratuvar testleri, klinik açıdan tanısal karar vermenin önemli bir parçasıdır. Bu nedenle ölçüm belirsizliği laboratuvar sonuçlarının doğruluğu bağlamında ön plana çıkmaktadır. Bu çalışmada, 29 rutin biyokimya analitinin ölçüm belirsizliği araştırılarak farklı kalite hedefleri ve sonuçları değerlendirildi. Gereçler ve Yöntem: Çalışmada Mindray BS-800 otoanalizörü ile Ekim 2020 Nisan 2021 tarihleri arasında çalışılan 29 analitin ölçüm belirsizliği analiz edilmiş ve ISO/TS 20914 Kılavuzuna göre değerlendirilmiştir. Ölçülen değerlerin tanımlanması, ölçümü etkileyen faktörlerin belirlenmesi, metot ölçüm belirsizliği, kalibrasyon belirsizliği, kalite kontrol verilerinden oluşan dış belirsizlik ve ölçüm belirsizlikleri belirlenmiştir. Ayrıca kalite kontrol verilerinden oluşan eksternal belirsizlik ve ölçüm belirsizlikleri de ölçülmüştür. Bulgular: Ölçülen analitlerden trigliserit, demir, fosfor, GGT, kreatin kinaz, ürik asit, lipaz ve CRP’ nin her iki seviyede EFLM ve Ricos topla...
IMPLEMENTATION OF A MEASUREMENT UNCERTAINTY GUIDELINE FOR ISO/IEC 17025 LABORATORY ASSESSORS
This paper presents the implementation of a measurement uncertainty assessment guideline applicable to laboratory assessors. Measurement uncertainty is a relevant subject for all laboratories as well as for accreditation bodies since it consists in an elementary requirement for ISO/IEC 17025 accreditation. Therefore, it is crucial to assure that all technical assessors have an adequate level of knowledge about measurement uncertainty and know how to proper assess it. Researching the literature, it is possible to observe that all measurement uncertainty guidelines are focused on the laboratory perspective, to help them implement GUM's concepts. This work, on the other hand, was focused on the implementation of a new measurement uncertainty guideline intended exclusively to help laboratory assessors improve their knowledge about this subject and better prepare them to carry out laboratory assessments. The guideline was implemented in Rede Metrológica RS (RMRS), a regional accreditation body from southern Brazil. Simultaneously to this measurement uncertainty assessment guideline, it was also prepared a measurement uncertainty check-list to help assessors conduct their laboratory assessments. As a result, an improvement on the level of knowledge about measurement uncertainty was observed among RMRS assessors. The improvement was possible to verify through the application of written exams about measurement uncertainty, before and after the training on the new guideline. Exams showed the improvement of assessors' knowledge, demonstrating the relevance of this innovative work.
Clinical Biochemistry, 2018
Background: Measurement uncertainty (MU) estimation has been introduced by ISO 15189 for the accreditation of clinical laboratories. Although MU reporting is not required, its inclusion in medical reports is of potential assistance to physicians in results interpretation. Methods: MU reporting was evaluated with respect to different test purposes, namely comparison with reference intervals (RI), patient monitoring or comparison with clinical decision limits. Clinical Biochemistry, Hematology, Coagulation and Clinical Immunology measurands were used as examples. Assuming Gaussian RI distribution, the probability of retesting due to MU was determined by simulations. Significant MU variations were compared against the reference change value (RCV) and clinical decision limits. Results: Three potential scenarios emerged for RI. For 12 measurands, depending on the MU interval, a potential change in results interpretation was found only for Sodium and S-Protein. On considering only the results within RI, simulations confirmed that up to 8.6% of MU intervals encompassed the RI limits, thus potentially leading to retesting. For tests used in patient monitoring, significant MU variations were comparable to those calculated by RCV, with the exception of CEA. For tests results evaluated with respect to clinical decision limits, on including MU, the clinical interpretation may be improved (e.g. for tPSA). Conclusion: The findings made in the present study, which considers real MU data and hypothetical results obtained for a series of measurands, support the concept that MU may aid the physician's interpretation thus ensuring reliable clinical decision making.
Scandinavian Journal of Clinical & Laboratory Investigation, 2012
Healthcare laboratories are increasingly joining into larger laboratory organizations encompassing several physical laboratories. This caters for important new opportunities for re-defining the concept of a 'laboratory' to encompass all laboratories and measurement methods measuring the same measurand for a population of patients. in order to make measurement results, comparable bias should be minimized or eliminated and measurement uncertainty properly evaluated for all methods used for a particular patient population. The measurement as well as diagnostic uncertainty can be evaluated from internal and external quality control results using guM principles. in this paper the uncertainty evaluations are described in detail using only two main components, within-laboratory reproducibility and uncertainty of the bias component according to a nordtest guideline. The evaluation is exemplified for the determination of creatinine in serum for a conglomerate of laboratories both expressed in absolute units (mmol/l) and relative (%). an expanded measurement uncertainty of 12 mmol/l associated with concentrations of creatinine below 120 mmol/l and of 10% associated with concentrations above 120 mmol/l was estimated. The diagnostic uncertainty encompasses both measurement uncertainty and biological variation, and can be estimated for a single value and for a difference. This diagnostic uncertainty for the difference for two samples from the same patient was determined to be 14 mmol/l associated with concentrations of creatinine below 100 mmol/l and 14 % associated with concentrations above 100 mmol/l.
Uncertainty of Measurement in Laboratory Medicine
Journal of Medical Biochemistry, 2018
An adequate assessment of the measurement uncertainty in a laboratory medicine is one of the most important factors for a reliable interpretation of the results. A large number of standards and guidelines indicate the need for a proper assessment of the uncertainty of measurement re sults in routine laboratory practice. The available docu ments ge nerally recommend participation in the proficiency schemes/ external quality control, as well as the internal quality control, in order to primarily verify the quality performance of the method. Although all documents meet the re quirements of the International Standard, ISO 15189, the standard itself does not clearly define the method by which the measurement results need to be assessed and there is no harmonization in practice regarding to this. Also, the uncertainty of measurement results is the data relating to the measured result itself, but all factors that influence the interpretation of the measured value, which is ultimately used for diagnosis and monitoring of the patient's treat ment, should be taken into account. So in laboratory medicine, an appropriate assessment of the uncertainty of the measurement results should have the ultimate goal of reducing diagnostic uncertainty. However, good profes sional laboratory practice and understanding analytical aspects of the test for each individual laboratory is ne ces sary to adequately define the uncertainty of measurement results for specific laboratory tests, which helps to imple ment good clinical practice. Also, setting diagnoses in medicine is a decision with a certain degree of uncertainty, rather than statistically and mathematically calculated conclusion.
Accreditation and Quality Assurance, 2017
On the basis of long-standing proficiency testings (PTs) for the small number of PT participants p (7 B p B 30), laboratory bias and uncertainty were calculated by applying inter-laboratory experimental approaches. Uncertainty was estimated in two ways, according to Eurolab TR No 1/2007 and Nordtest TR 537 (2012). In the case of 24 tested feed components (basic nutrients, macro-and microelements, undesirable elements and some feed additives including vitamins A and E, lysine, threonine, methionine and urea) in the large variety of feed samples, differences between the expanded uncertainties calculated according to Eurolab TR No 1/2007 and Nordtest TR 537 did not exceed 1.4 % for all tested feed and analytes in wide concentration ranges. In order to get a reliable evaluation of bias and uncertainty, minimum of 6 PT rounds and a sufficient number of laboratories participating (p C 10) are recommended. When the above parameters are applied and the standard deviation of the bias s bias B 5 %, the expression s bias 2 /n can be omitted while calculating bias. Generally, both approaches fit the purpose of feed evaluation and the calculated uncertainties can be used for compliance assessment.
The use of error and uncertainty methods in the medical laboratory
Clinical Chemistry and Laboratory Medicine (CCLM), 2017
Error methods – compared with uncertainty methods – offer simpler, more intuitive and practical procedures for calculating measurement uncertainty and conducting quality assurance in laboratory medicine. However, uncertainty methods are preferred in other fields of science as reflected by the guide to the expression of uncertainty in measurement. When laboratory results are used for supporting medical diagnoses, the total uncertainty consists only partially of analytical variation. Biological variation, pre- and postanalytical variation all need to be included. Furthermore, all components of the measuring procedure need to be taken into account. Performance specifications for diagnostic tests should include the diagnostic uncertainty of the entire testing process. Uncertainty methods may be particularly useful for this purpose but have yet to show their strength in laboratory medicine. The purpose of this paper is to elucidate the pros and cons of error and uncertainty methods as gr...