scholarly journals An overview of the European Organization for External Quality Assurance Providers in Laboratory Medicine (EQALM)

2017 ◽  
pp. 30-36 ◽  
Author(s):  
Anne Stavelin ◽  
Xavier Albe ◽  
Piet Meijer ◽  
Erika Sarkany ◽  
Finlay MacKenzie
Author(s):  
Carmen Perich ◽  
Carmen Ricós ◽  
Fernando Marqués ◽  
Joana Minchinela ◽  
Angel Salas ◽  
...  

AbstractThe purpose of this study is to understand the evolution of the analytical performance of the laboratories participating in the Spanish society of laboratory medicine (SEQCML) external quality assurance (EQA) programmes during its 30 years of operation and to compare it with the performance of other EQA programmes to establish whether the results are similar. The results obtained during this period are evaluated by applying the biological variability (BV) and state of the art-derived quality specifications. In addition, the results are compared with those obtained by other EQA programme organisations. It is noted that the laboratories participating in the EQA–SEQCML programmes have improved their performance over 30 years of experience and that the specifications derived from biological variation are achievable. It is difficult to compare EQA programmes, due to lack of accessibility and the differences in the design of these programmes (control materials, calculations used and analytical specifications established). The data from this study show that for some biological magnitudes the results obtained by the programmes are not yet harmonised, although efforts are being made to achieve this. Organisers of EQA programmes should also join the harmonisation effort by providing information on their results to enable comparison.


2018 ◽  
Vol 42 (6) ◽  
pp. 297-304
Author(s):  
Rae-Anne Hardie ◽  
Donna Moore ◽  
Derek Holzhauser ◽  
Michael Legg ◽  
Andrew Georgiou ◽  
...  

AbstractExternal quality assurance (EQA) provides ongoing evaluation to verify that laboratory medicine results conform to quality standards expected for patient care. While attention has focused predominantly on test accuracy, the diagnostic phases, consisting of pre- and post-laboratory phases of testing, have thus far lagged in the development of an appropriate diagnostic-phase EQA program. One of the challenges faced by Australian EQA has been a lack of standardisation or “harmonisation” resulting from variations in reporting between different laboratory medicine providers. This may introduce interpretation errors and misunderstanding of results by clinicians, resulting in a threat to patient safety. While initiatives such as the Australian Pathology Information, Terminology and Units Standardisation (PITUS) program have produced Standards for Pathology Informatics in Australia (SPIA), conformity to these requires regular monitoring to maintain integrity of data between sending (laboratory medicine providers) and receiving (physicians, MyHealth Record, registries) organisations’ systems. The PITUS 16 Informatics EQA (IEQA) Project together with the Royal College of Pathologists of Australasia Quality Assurance Programs (RCPAQAP) has created a system to perform quality assurance on the electronic laboratory message when the laboratory sends a result back to the EQA provider. The purpose of this study was to perform a small scale pilot implementation of an IEQA protocol, which was performed to test the suitability of the system to check compliance of existing Health Level-7 (HL7 v2.4) reporting standards localised and constrained by the RCPA SPIA. Here, we present key milestones from the implementation, including: (1) software development, (2) installation, and verification of the system and communication services, (3) implementation of the IEQA program and compliance testing of the received HL7 v2.4 report messages, (4) compilation of a draft Informatics Program Survey Report for each laboratory and (5) review consisting of presentation of a report showing the compliance checking tool to each participating laboratory.


2014 ◽  
Vol 123 (2) ◽  
pp. 108-116 ◽  
Author(s):  
Margaret C. Cummings ◽  
Louise Marquart ◽  
Anita M. Pelecanos ◽  
Gail Perkins ◽  
David Papadimos ◽  
...  

2011 ◽  
Vol 135 (7) ◽  
pp. 874-881
Author(s):  
Nikita Makretsov ◽  
C. Blake Gilks ◽  
Reza Alaghehbandan ◽  
John Garratt ◽  
Louise Quenneville ◽  
...  

Abstract Context.—External quality assurance and proficiency testing programs for breast cancer predictive biomarkers are based largely on traditional ad hoc design; at present there is no universal consensus on definition of a standard reference value for samples used in external quality assurance programs. Objective.—To explore reference values for estrogen receptor and progesterone receptor immunohistochemistry in order to develop an evidence-based analytic platform for external quality assurance. Design.—There were 31 participating laboratories, 4 of which were previously designated as “expert” laboratories. Each participant tested a tissue microarray slide with 44 breast carcinomas for estrogen receptor and progesterone receptor and submitted it to the Canadian Immunohistochemistry Quality Control Program for analysis. Nuclear staining in 1% or more of the tumor cells was a positive score. Five methods for determining reference values were compared. Results.—All reference values showed 100% agreement for estrogen receptor and progesterone receptor scores, when indeterminate results were excluded. Individual laboratory performance (agreement rates, test sensitivity, test specificity, positive predictive value, negative predictive value, and κ value) was very similar for all reference values. Identification of suboptimal performance by all methods was identical for 30 of 31 laboratories. Estrogen receptor assessment of 1 laboratory was discordant: agreement was less than 90% for 3 of 5 reference values and greater than 90% with the use of 2 other reference values. Conclusions.—Various reference values provide equivalent laboratory rating. In addition to descriptive feedback, our approach allows calculation of technical test sensitivity and specificity, positive and negative predictive values, agreement rates, and κ values to guide corrective actions.


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