Medical Laboratories Accreditation is covered by ISO 15189:2012 - Medical Laboratories — Requirements for Quality and Competence. In Portugal, accreditation processes are held under the auspices of the Portuguese Accreditation Institute (IPAC), which applies the Portuguese edition (NP EN ISO 15189:2014). Accordingly, Medical Laboratories accreditation processes now require the estimate of measurement uncertainty (MU) associated to the results. The Guide to the Expression of Uncertainty in Measurement (GUM) describes the calculation of MU, not contemplating the specific aspects of medical laboratory testing. Several models have been advocated, yet without a final consensus. Given the lack of studies on MU in Portugal, especially on its application in the medical laboratory, it is the objective of this thesis to reach to a model that fulfils the IPAC’s accreditation regulations, in regards to this specific requirement. The study was based on the implementation of two formulae (MU-A and MU-B), using the Quality Management System (QMS) data of an ISO 15189 Accredited Laboratory. Including the laboratory’s two Cobas® 6000–c501 (Roche®) analysers (C1 and C2) the work focused three analytes: creatinine, glucose and total cholesterol. The MU-B model formula, combining the standard uncertainties of the method’s imprecision, of the calibrator’s assigned value and from the pre-analytical variation, was considered the one best fitting to the laboratory's objectives and to the study's purposes, representing well the dispersion of values reasonably attributable to the measurand final result. Expanded Uncertainties were: Creatinine - C1 = 9,60%; C2 = 5,80%; Glucose - C1 = 8,32%; C2 = 8,34%; Cholesterol - C1 = 4,00%; C2 = 3,54 %. ...[cont.].

The majority of laboratory testing errors originate in the pre-analytical phase. While the causes and frequencies of pre-analytical errors are well characterized, there are few studies investigating the cost of these errors. The objective of this research was to build a model to quantify the cost of pre-analytical errors occurring during inpatient complete blood count (CBC) testing at Sunnybrook Health Sciences Centre (Sunnybrook). The resultant cost model accounts for the costs of materials, resources, and personnel-time consumed in the CBC testing process. In 2011, pre-analytical errors in inpatient CBC testing cost Sunnybrook $43,462, and represented a loss of 775 employee hours due to laboratory test repetition and error-related activities. This cost model represents the minimum cost of a pre-analytical error, as costs extraneous to the laboratory were beyond the study scope. Future studies investigating downstream effects of pre-analytical errors and the costs associated with them should be conducted.

The majority of laboratory testing errors originate in the pre-analytical phase. While the causes and frequencies of pre-analytical errors are well characterized, there are few studies investigating the cost of these errors. The objective of this research was to build a model to quantify the cost of pre-analytical errors occurring during inpatient complete blood count (CBC) testing at Sunnybrook Health Sciences Centre (Sunnybrook). The resultant cost model accounts for the costs of materials, resources, and personnel-time consumed in the CBC testing process. In 2011, pre-analytical errors in inpatient CBC testing cost Sunnybrook $43,462, and represented a loss of 775 employee hours due to laboratory test repetition and error-related activities. This cost model represents the minimum cost of a pre-analytical error, as costs extraneous to the laboratory were beyond the study scope. Future studies investigating downstream effects of pre-analytical errors and the costs associated with them should be conducted.