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

Documentation of Nursing Diagnosis01:10

Documentation of Nursing Diagnosis

1.9K
The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters...
1.9K
Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

12.0K
Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
12.0K
Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

11.3K
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...
11.3K
Accuracy and Errors in Hypothesis Testing01:13

Accuracy and Errors in Hypothesis Testing

672
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%...
672
Errors occurring during blood pressure monitoring01:25

Errors occurring during blood pressure monitoring

1.8K
Blood pressure monitoring is a crucial clinical procedure in diagnosing and managing various cardiovascular conditions. Despite its significance, the accuracy of blood pressure measurements can be compromised by multiple factors, potentially leading to either falsely high or low readings. These inaccuracies are critical as they can significantly impact patient care. So, it is vital to understand these challenges deeply and adopt strategic approaches to minimize errors.
Several factors...
1.8K
Random and Systematic Errors01:20

Random and Systematic Errors

16.0K
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...
16.0K

You might also read

Related Articles

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

Sort by
Same author

Population Dynamics and the Microbiome in a Wild Boreal Mammal: The Snowshoe Hare Cycle and Impacts of Diet, Season and Predation Risk.

Molecular ecology·2024
Same author

Prevalence and Outcomes of Emergency Presentations of Colorectal Cancer in Veterans Affairs Health Care System.

Digestive diseases and sciences·2024
Same author

Synthesis of existing literature on the colorectal surgery patients' challenges during hospital-to-home transitions: a scoping review protocol.

BMJ open·2024
Same author

Exploring the Perspectives of Older Adults Living With HIV on Virtual Care: Qualitative Study.

JMIR aging·2024
Same author

Implementation of Electronic Triggers to Identify Diagnostic Errors in Emergency Departments.

JAMA internal medicine·2024
Same author

Recommendations to Ensure Safety of AI in Real-World Clinical Care.

JAMA·2024
Same journal

Using generative AI to support clinical reasoning coaching: a theory-informed approach.

Diagnosis (Berlin, Germany)·2026
Same journal

Learning from what went right: a Safety-II application of the SIDER protocol to a case of occult breast cancer.

Diagnosis (Berlin, Germany)·2026
Same journal

Impact of clinical reasoning and diagnostic error education for nurses.

Diagnosis (Berlin, Germany)·2026
Same journal

Progress in mast cell activation syndrome: the global consensus-2 diagnostic criteria at six years.

Diagnosis (Berlin, Germany)·2026
Same journal

Japan and the future of diagnostic research.

Diagnosis (Berlin, Germany)·2026
Same journal

Evaluation of the analytical performance and usability of the VChemy S analyzer for decentralized multipanel testing.

Diagnosis (Berlin, Germany)·2026
See all related articles

Related Experiment Video

Updated: Mar 24, 2026

Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

17.4K

The challenges in defining and measuring diagnostic error.

Laura Zwaan, Hardeep Singh1

  • 1Houston Veterans Affairs Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey Veterans Affairs Medical Center and the Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA.

Diagnosis (Berlin, Germany)
|March 9, 2016
PubMed
Summary
This summary is machine-generated.

Defining and measuring diagnostic errors presents significant patient safety challenges. Research must address complexities like evolving conditions, balancing under/overdiagnosis, and hindsight assessment for accurate measurement.

Keywords:
clinical decision-makingcognitive errorsdiagnostic errorjudgmentpatient safety

More Related Videos

Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision
07:57

Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision

Published on: April 29, 2014

14.1K
A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
04:19

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

Published on: May 10, 2022

4.7K

Related Experiment Videos

Last Updated: Mar 24, 2026

Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

17.4K
Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision
07:57

Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision

Published on: April 29, 2014

14.1K
A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
04:19

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

Published on: May 10, 2022

4.7K

Area of Science:

  • Medical error research
  • Patient safety science
  • Diagnostic medicine

Background:

  • Diagnostic errors are a critical patient safety issue.
  • Current methods for detecting and defining diagnostic errors are insufficient.
  • Multidisciplinary expert consensus is needed to advance research in this area.

Purpose of the Study:

  • To synthesize expert discussions on challenges in defining and measuring diagnostic errors.
  • To identify key research obstacles in operationalizing diagnostic error measurement.
  • To propose approaches for addressing these research challenges.

Main Methods:

  • Convened a multidisciplinary expert panel at the 2013 Diagnostic Error in Medicine 6th International Conference.
  • Synthesized panel discussions on defining and measuring diagnostic errors.
  • Outlined research challenges and potential solutions.

Main Results:

  • Identified key challenges: evolving disease/diagnosis over time and across settings, balancing underdiagnosis and overdiagnosis, and determining diagnosis likelihood/severity in hindsight.
  • Highlighted the complexity of measuring diagnostic error in real-world clinical practice.
  • Provided a framework for addressing research challenges in diagnostic error measurement.

Conclusions:

  • Accurate measurement of diagnostic error is crucial for improving patient safety.
  • Further research is needed to overcome the identified challenges in defining and measuring diagnostic errors.
  • Addressing these complexities will enhance the reliability and validity of diagnostic error research.