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

Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

11.0K
In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
11.0K
Random and Systematic Errors01:20

Random and Systematic Errors

15.1K
Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
15.1K
Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

1.5K
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
1.5K
Errors In Hypothesis Tests01:14

Errors In Hypothesis Tests

6.0K
When performing a hypothesis test, there are four possible outcomes depending on the actual truth (or falseness) of the null hypothesis and the decision to reject or not.
6.0K
Accuracy and Errors in Hypothesis Testing01:13

Accuracy and Errors in Hypothesis Testing

599
Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
599
Prevalence and Incidence01:08

Prevalence and Incidence

1.9K
In statistical epidemiology and health sciences, two essential metrics—prevalence and incidence—are fundamental for understanding disease dynamics within a population. These measures enable public health officials, epidemiologists, and researchers to assess the burden of diseases, allocate resources effectively, and design impactful public health policies and interventions.
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
1.9K

You might also read

Related Articles

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

Sort by
Same author

Characterizing pseudoangiomatous stromal hyperplasia (PASH) of the breast.

Histopathology·2026
Same author

The grossing competency evaluation process in a pathology residency program: transitioning from paper to digital.

American journal of clinical pathology·2026
Same author

Shortwave infrared imaging increases the number of lymph nodes and improves cancer staging: a 104-patient study.

Journal of clinical pathology·2025
Same author

Effects of High-Fidelity Simulation-Based Learning on Physical Therapy Student Learning and Performance: A Systematic Review.

Journal, physical therapy education·2025
Same author

Combined Radiation and Endocrine Therapies Elicit Benefit in ER+ Breast Cancer.

Cancers·2025
Same author

In Situ Encapsulated/Solid Papillary Breast Carcinoma With Lobular Differentiation.

International journal of surgical pathology·2025

Related Experiment Video

Updated: Feb 8, 2026

Meta-Analysis of the Effectiveness and Safety of Shugan Jieyu Capsules for the Treatment of Insomnia
04:34

Meta-Analysis of the Effectiveness and Safety of Shugan Jieyu Capsules for the Treatment of Insomnia

Published on: February 17, 2023

1.6K

Technical error prevalence in the complete pathology tissue testing process: a systematic review and meta-analysis.

Amanda Katsma1,2, Julie M Jorns2, Patrick Gardner2

  • 1Clinical Research, University of Jamestown, Fargo, North Dakota, USA amanda.katsma@uj.edu.

BMJ Open Quality
|February 6, 2026
PubMed
Summary

Technical errors in pathology tissue processing are more common than reported, potentially impacting patient diagnoses. Standardized methods are needed to accurately detect and report these errors.

Keywords:
Data AccuracyDiagnostic errorsPathologyPatient safetyQuality measurement

More Related Videos

Systematic Assessment of Mammalian Skull Specimens for Dental and Temporomandibular Joint Pathology
07:26

Systematic Assessment of Mammalian Skull Specimens for Dental and Temporomandibular Joint Pathology

Published on: August 22, 2022

2.0K
Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
08:36

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

1.2K

Related Experiment Videos

Last Updated: Feb 8, 2026

Meta-Analysis of the Effectiveness and Safety of Shugan Jieyu Capsules for the Treatment of Insomnia
04:34

Meta-Analysis of the Effectiveness and Safety of Shugan Jieyu Capsules for the Treatment of Insomnia

Published on: February 17, 2023

1.6K
Systematic Assessment of Mammalian Skull Specimens for Dental and Temporomandibular Joint Pathology
07:26

Systematic Assessment of Mammalian Skull Specimens for Dental and Temporomandibular Joint Pathology

Published on: August 22, 2022

2.0K
Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
08:36

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

1.2K

Area of Science:

  • Pathology
  • Laboratory Medicine
  • Quality Improvement

Background:

  • Technical errors in the total testing process of pathology tissue specimens can compromise patient diagnoses.
  • The true prevalence of these errors is often underestimated due to a lack of standardized detection and reporting methods.

Purpose of the Study:

  • To estimate the prevalence of technical errors across the entire workflow of pathology tissue specimen analysis.
  • To highlight the impact of undocumented and unidentified errors on diagnostic accuracy.

Main Methods:

  • A systematic review and meta-analysis of observational studies published after 2003 were conducted.
  • Data from 31 studies, encompassing over 2.7 million surgical pathology cases, were pooled using random-effects models.
  • Searches were performed across PubMed, CINAHL, Cochrane Library, and Science Direct.

Main Results:

  • The pooled prevalence of pre-analytic errors was 16.71 per 1000 cases.
  • Actively identified laboratory errors occurred at a rate of 40.17 per 1000 cases.
  • Surgical pathology specimen errors were reported at 4.94 per 1000 cases, with contamination at 62.23 per 1000 cases.

Conclusions:

  • Technical errors in tissue processing are likely more prevalent than currently documented.
  • The absence of standardized methodologies for error definition and detection leads to underreporting.
  • Improving error detection and reporting is crucial for ensuring reliable laboratory results and safeguarding patient diagnoses.