Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Nursing Evaluation01:15

Nursing Evaluation

The evaluation stage signals the end of the nursing process. The nurse gathers evaluative data to assess whether or not the patient has attained the expected results. Whereas the nurse collects data in the nursing assessment to identify the patient's health concerns, the evaluation stage data determines if the indicated health issues are resolved. Evaluative data collection includes two sections: the data acquired to evaluate patient outcomes and the time criteria for data collection.
Section...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Quality Assurance01:19

Quality Assurance

Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
Health Information Technology and Healthcare Information System01:30

Health Information Technology and Healthcare Information System

Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
Statgraphics01:10

Statgraphics

Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
Purpose of Health Records I01:11

Purpose of Health Records I

The vital purpose of health records is to provide a complete and accurate account of a patient's medical history, including communication, diagnostic and therapeutic orders, care planning, research, and quality review.
Here's a breakdown of how health records serve these purposes:

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Predictive value of kynurenine pathway metabolites in patients with diabetic kidney disease.

Acta diabetologica·2026
Same author

Comparison of AI-based Chatbot Performance in Analyzing Clinical Scenarios versus Medical Residents: A Novel Approach in Chest Diseases Education.

Thoracic research and practice·2026
Same author

Impact of sample size and data origin on the simulation-based analytical performance specification derivation.

Clinical chemistry and laboratory medicine·2026
Same author

Peer Review of "Investigating the Variable Component of the Systematic Error, a Neglected Error Parameter: Theoretical Reevaluation Study".

JMIRx med·2026
Same author

Serum Kynurenine Pathway Metabolites as Candidate Diagnostic Biomarkers for Pituitary Adenoma: A Case-Control Study.

Medicina (Kaunas, Lithuania)·2025
Same author

Relationship between obesity and serum resistin, apelin, and sterol regulatory element binding protein-1c levels: the changes in the analyte levels durin g weight loss in obese patients.

Revista da Associacao Medica Brasileira (1992)·2025

Related Experiment Videos

Is statistical evaluation sufficient? New external quality assessment performance metrics through clinical

Halil İbrahim Akbay1, Elvar Theodorsson2, Hamit Hakan Alp1

  • 1Department of Medical Biochemistry, Faculty of Medicine, Van Yüzüncü Yıl University, Van, Türkiye.

Clinical Chemistry and Laboratory Medicine
|June 18, 2026
PubMed
Summary

New metrics for External Quality Assessment (EQA) integrate biological variation, improving clinical relevance. These tools, SDI_RCV and pSDI, enhance laboratory quality assessment by detecting biases missed by conventional methods.

Keywords:
analytical performance specificationsbiological variationproficiency testingreference change value

Related Experiment Videos

Area of Science:

  • Clinical Chemistry
  • Laboratory Medicine
  • Quality Management Systems

Background:

  • External Quality Assessment (EQA) traditionally uses Standard Deviation Index (SDI) with fixed limits (-2 to +2).
  • This conventional SDI does not account for biological variation or clinical relevance of laboratory results.
  • Analytical imprecision is a key concern in diagnostic testing.

Purpose of the Study:

  • To develop and validate novel metrics (SDI_RCV and pSDI) that incorporate biological variation into EQA interpretation.
  • To quantify sources of analytical imprecision using variance component analysis (VCA).
  • To establish a biologically grounded framework for laboratory quality assessment.

Main Methods:

  • Analysis of monthly EQA results for 45 analytes over 12 cycles in a clinical laboratory.
  • Calculation of SDI_RCV (ratio of reference change value to peer-group CV) and pSDI (EQA bias as a percentage of RCV).
  • Decomposition of total imprecision into repeatability, between-month variation, and reagent lot-to-lot variation using VCA.

Main Results:

  • Nine observations (1.67%) showed clinically significant bias despite acceptable SDI (-2
  • Four observations (0.74%) had clinically inconsequential SDI exceedance (SDI≥±3 yet -100%
  • Lot-to-lot variation contributed a median of 23.6% to total variance, exceeding 50% for six analytes.

Conclusions:

  • SDI_RCV and pSDI effectively detect false acceptance and false rejection in conventional EQA criteria.
  • These novel metrics provide a biologically grounded approach for aligning laboratory quality assessment with clinical needs.
  • Variance component analysis highlights the impact of reagent lot variation on analytical imprecision.