Quality specifications for the extra-analytical phase of laboratory testing: Reference intervals and decision limits

2017 ◽  
Vol 50 (10-11) ◽  
pp. 595-598 ◽  
Author(s):  
Ferruccio Ceriotti
Keyword(s):  
Laboratory Testing ◽  
Reference Intervals ◽  
Quality Specifications ◽  
Analytical Phase ◽  
Testing Reference

scholarly journals Clinical laboratory services for primary healthcare centers in urban cities: a pilot ACO model of ten primary healthcare centers

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Soha A. Tashkandi ◽  
Ali Alenezi ◽  
Ismail Bakhsh ◽  
Abdullah AlJuryyan ◽  
Zahir H AlShehry ◽  
...  
Keyword(s):  
Saudi Arabia ◽  
Quality Improvement ◽  
Primary Healthcare ◽  
Laboratory Testing ◽  
Gap Analysis ◽  
Reference Laboratory ◽  
Pilot Model ◽  
Laboratory Services ◽  
Analytical Phase ◽  
Primary Healthcare Centers

Abstract Background Primary healthcare centers (PHC) ensure that patients receive comprehensive care from promotion and prevention to treatment, rehabilitation, and palliative care in a familiar environment. It is designed to provide first-contact, continuous, comprehensive, and coordinated patient care that will help achieve equity in the specialty healthcare system. The healthcare in Saudi Arabia is undergoing transformation to Accountable Care Organizations (ACO) model. In order for the Kingdom of Saudi Arabia (KSA) to achieve its transformational goals in healthcare, the improvement of PHCs’ quality and utilization is crucial. An integral part of this service is the laboratory services. Methods This paper presents a pilot model for the laboratory services of PHC's in urban cities. The method was based on the FOCUS-PDCA quality improvement method focusing on the pre-analytical phase of the laboratory testing as well as the Saudi Central Board for Accreditation of Healthcare Institutes (CBAHI) gap analysis and readiness within the ten piloted primary healthcare centers. Results The Gap analysis, revealed in-consistency in the practice, lead to lower the quality of the service, which was seen in the low performance of the chosen key performance indicators (KPI's) (high rejection rates, lower turn-around times (TAT) for test results) and also in the competency of the staff. Following executing the interventions, and by using some of the ACO Laboratory strategies; the KPI rates were improved, and our results exceeded the targets that we have set to reach during the first year. Also introducing the electronic connectivity improved the TAT KPI and made many of the processes leaner. Conclusions Our results revealed that the centralization of PHC's laboratory service to an accredited reference laboratory and implementing the national accreditation standards improved the testing process and lowered the cost, for the mass majority of the routine laboratory testing. Moreover, the model shed the light on how crucial the pre-analytical phase for laboratory quality improvement process, its effect on cost reduction, and the importance of staff competency and utilization.

Understanding and managing interferences in clinical laboratory assays: the role of laboratory professionals

2020 ◽  
Vol 58 (3) ◽  
pp. 350-356 ◽  
Author(s):  
Martina Zaninotto ◽  
Mario Plebani
Keyword(s):  
Patient Safety ◽  
Laboratory Testing ◽  
Clinical Laboratory ◽  
Careful Evaluation ◽  
The Matrix ◽  
Analytical Phase

AbstractThe recently raised concerns regarding biotin interference in immunoassays have increased the awareness of laboratory professionals and clinicians of the evidence that the analytical phase is still vulnerable to errors, particularly as analytical interferences may lead to erroneous results and risks for patient safety. The issue of interference in laboratory testing, which is not new, continues to be a challenge deserving the concern and interest of laboratory professionals and clinicians. Analytical interferences should be subdivided into two types on the basis of the possibility of their detection before the analytical process. The first (type 1) is represented by lipemia, hemolysis and icterus, and the second (type 2), by unusual constituents that are not undetectable before analysis, and may affect the matrix of serum/plasma of individual subjects. Type 2 cannot be identified with current techniques when performing the pre-analytical phase. Therefore, in addition to a more careful evaluation and validation of the method to be used in clinical practice, the awareness of laboratory professionals should be raised as to the importance of evaluating the quality of biological samples before analysis and to adopt algorithms and approaches in the attempt to reduce problems related to erroneous results due to specific or non-specific interferences.

Performance criteria and quality indicators for the pre-analytical phase

2015 ◽  
Vol 53 (6) ◽  
Author(s):  
Mario Plebani ◽  
Laura Sciacovelli ◽  
Ada Aita ◽  
Michela Pelloso ◽  
Maria Laura Chiozza
Keyword(s):  
Quality Indicators ◽  
Performance Criteria ◽  
Analytical Quality ◽  
Performance Targets ◽  
Laboratory Services ◽  
Quality Specifications ◽  
Analytical Phase ◽  
Total Testing Process ◽  
The Individual

AbstractThe definition, implementation and monitoring of valuable analytical quality specifications have played a fundamental role in improving the quality of laboratory services and reducing the rates of analytical errors. However, a body of evidence has been accumulated on the relevance of the extra-analytical phases, namely the pre-analytical steps, their vulnerability and impact on the overall quality of the laboratory information. The identification and establishment of valueable quality indicators (QIs) represents a promising strategy for collecting data on quality in the total testing process (TTP) and, particularly, for detecting any mistakes made in the individual steps of the pre-analytical phase, thus providing useful information for quality improvement projects. The consensus achieved on the developed list of harmonized QIs is a premise for the further step: the identification of achievable and realistic performance targets based on the knowledge of the state-of-the-art. Data collected by several clinical laboratories worldwide allow the classification of performances for available QIs into three levels: optimum, desirable and minimum, in agreement with the widely accepted proposal for analytical quality specifications.

Analytical performance, reference values and decision limits. A need to differentiate between reference intervals and decision limits and to define analytical quality specifications

2012 ◽  
Vol 50 (5) ◽  
Author(s):  
Per Hyltoft Petersen ◽  
Esther A. Jensen ◽  
Ivan Brandslund
Keyword(s):  
Reference Values ◽  
Clinical Guidelines ◽  
Reference Intervals ◽  
Analytical Performance ◽  
International Expert ◽  
Analytical Quality ◽  
Quality Specifications ◽  
Reference Samples ◽  
Critical Situations

AbstractWith the increasing use of decision limits (action limits, cut-off points) specified for a number of analytical components in diagnosis and for action in critical situations, formulated in national or international recommendations, the traditional interpretation of reference intervals has been uncertain, and sometimes the two concepts are being mixed up by incorporating risk calculations in the reference intervals. There is, therefore, a need to clarify the two concepts and to keep them definitely separated. Reference intervals are the 95% limits for the descriptions of the distributions of the values of analytical components measured on reference samples from reference individuals. Decision limits are based on guidelines from national and international expert groups defining specific concentrations of certain components as limits for decision about diagnosis or well-defined specific actions. Analytical quality specifications for reference intervals have been defined for bias since the 1990s, but in the recommendations specified in the clinical guidelines analytical quality specifications are only scarcely defined. The demands for negligible biases are, however, even more essential for decision limits, as the choice is no longer left to the clinician, but emerge directly from the concentration. Even a small bias will change the number of diseased individuals, so the demands for negligible biases are obvious. A view over the analytical quality as published gives a variable picture of bias for many components, but with many examples of considerable bias which must be critical – yet no specifications have been stipulated until now.

Performance specifications in extra-analytical phase of laboratory testing: Sample handling and transportation

2017 ◽  
Vol 50 (10-11) ◽  
pp. 574-578 ◽  
Author(s):  
Martina Zaninotto ◽  
Adriano Tasinato ◽  
Gianni Vecchiato ◽  
Angelo Legnaro ◽  
Alessio Pinato ◽  
...  
Keyword(s):  
Laboratory Testing ◽  
Sample Handling ◽  
Testing Sample ◽  
Performance Specifications ◽  
Analytical Phase

scholarly journals Biological Variation of Vitamins in Blood of Healthy Individuals

2005 ◽  
Vol 51 (11) ◽  
pp. 2145-2150 ◽  
Author(s):  
Dinesh K Talwar ◽  
Mohammed K Azharuddin ◽  
Cathy Williamson ◽  
Yee Ping Teoh ◽  
Donald C McMillan ◽  
...  
Keyword(s):  
Whole Blood ◽  
Total Error ◽  
Reference Intervals ◽  
Biological Variation ◽  
Reference Change Value ◽  
Objective Quality ◽  
Variation Data ◽  
Quality Specifications ◽  
Index Of Individuality ◽  
Apparently Healthy

Abstract Background: Components of biological variation can be used to define objective quality specifications (imprecision, bias, and total error), to assess the usefulness of reference values [index of individuality (II)], and to evaluate significance of changes in serial results from an individual [reference change value (RCV)]. However, biological variation data on vitamins in blood are limited. The aims of the present study were to determine the intra- and interindividual biological variation of vitamins A, E, B1, B2, B6, C, and K and carotenoids in plasma, whole blood, or erythrocytes from apparently healthy persons and to define quality specifications for vitamin measurements based on their biology. Methods: Fasting plasma, whole blood, and erythrocytes were collected from 14 healthy volunteers at regular weekly intervals over 22 weeks. Vitamins were measured by HPLC. From the data generated, the intra- (CVI) and interindividual (CVG) biological CVs were estimated for each vitamin. Derived quality specifications, II, and RCV were calculated from CVI and CVG. Results: CVI was 4.8%–38% and CVG was 10%–65% for the vitamins measured. The CVIs for vitamins A, E, B1, and B2 were lower (4.8%–7.6%) than for the other vitamins in blood. For all vitamins, CVG was higher than CVI, with II <1.0 (range, 0.36–0.95). The RCVs for vitamins were high (15.8%–108%). Apart from vitamins A, B1, and erythrocyte B2, the imprecision of our methods for measurement of vitamins in blood was within the desirable goal. Conclusions: For most vitamin measurements in plasma, whole blood, or erythrocytes, the desirable imprecision goals based on biological variation are obtainable by current methodologies. Population reference intervals for vitamins are of limited value in demonstrating deficiency or excess.

Analytical quality specifications for common reference intervals

2004 ◽  
Vol 42 (7) ◽  
Author(s):  
Carmen Ricós ◽  
Maria Vicenta Doménech ◽  
Carmen Perich
Keyword(s):  
Real Life ◽  
Reference Interval ◽  
Population Based ◽  
Reference Intervals ◽  
Healthy Population ◽  
Analytical Quality ◽  
Related Factors ◽  
Cross Sectional ◽  
Reference Change Value ◽  
Quality Specifications

AbstractInterpretation oflaboratory test results requires comparison to some type of reference value or reference interval. These comparisons can be cross-sectional (population-based reference interval and cut-off values) or longitudinal (reference change value). Quality specifications for cross-sectional comparison have been established by determining the influence of analytical bias and imprecision on the percentage ofthe healthy population falling outside the reference limits, when sharing population-based reference intervals in a Gaussian distribution ofresults. Quality specifications for longitudinal comparisons are equally important and are often overlooked, since less work has been done in this area. Some criteria suggest that a difference between consecutive results designates a true change in a patient health status when the difference is higher than the within-subject biological variation plus the within-laboratory analytical variation. In this chapter we discuss the clinical considerations and laboratory-related factors that must be considered when quality specifications are applied to sharing reference comparisons. Real life experience shows that different analytical methods can produce comparable results when common quality goals are established, and quality can be achieved through a willingness to work together. Within the existing organization, the current specifications for analytical quality and a dedication to quality health care makes it possible to achieve transferability between laboratories within a geographic area.

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