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

11.2K
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...
11.2K
Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

11.7K
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...
11.7K
Accuracy and Errors in Hypothesis Testing01:13

Accuracy and Errors in Hypothesis Testing

642
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%...
642
Random and Systematic Errors01:20

Random and Systematic Errors

15.6K
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...
15.6K
Improving Translational Accuracy02:07

Improving Translational Accuracy

15.3K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
15.3K
Improving Translational Accuracy02:07

Improving Translational Accuracy

3.7K
3.7K

You might also read

Related Articles

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

Sort by
Same author

Achieving Quality Through Evidence-Based Practice and Process Improvement Synergy: The EQUiPP Framework.

Worldviews on evidence-based nursing·2026
Same author

Culturally Adapted Lifestyle and Mental Health Intervention for Low-Income Pregnant Women: A Feasibility Study.

Western journal of nursing research·2025
Same author

The Evidence-Based Practice Mentor: Findings From a Role Delineation Study to Support the Role's Needed Knowledge and Skills.

Worldviews on evidence-based nursing·2025
Same author

Leveraging the Jigsaw Learning Strategy to Promote Competence, Confidence, and Efficiency in Evidence-Based Practice.

Worldviews on evidence-based nursing·2025
Same author

Does Hospital Accreditation or Certification Impact Patient Outcomes? Findings From a Scoping Review for Healthcare Industry Leaders.

The Journal of nursing administration·2024
Same author

A pilot study of Keto Prescribed+: A healthy thinking and eating educational program for African American women.

Journal of the American Association of Nurse Practitioners·2024
Same journal

Compassion fatigue among critical care nurses: a literature review.

Nursing management (Harrow, London, England : 1994)·2026
Same journal

Repositioning entrepreneurial competence as a core nursing capability: unlocking nurses' leadership and innovation potential.

Nursing management (Harrow, London, England : 1994)·2026
Same journal

How to design and deliver a nurse fellowship.

Nursing management (Harrow, London, England : 1994)·2026
Same journal

Relationship between leadership transparency and workplace cynicism among nurses: a systematic review and meta-analysis.

Nursing management (Harrow, London, England : 1994)·2026
Same journal

Strengthening nurses' recognition of, and response to, domestic violence and abuse.

Nursing management (Harrow, London, England : 1994)·2026
Same journal

From strain to strength: enhancing the benefits of employing temporary nurses.

Nursing management (Harrow, London, England : 1994)·2026
See all related articles

Related Experiment Video

Updated: Mar 3, 2026

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

12.6K

In rooting out errors, evidence holds the key.

Lynn Gallagher-Ford1, Bernadette Melnyk2

  • 1Ohio State University.

Nursing Management (Harrow, London, England : 1994)
|April 28, 2017
PubMed
Summary
This summary is machine-generated.

US healthcare faces a crisis, with preventable medical errors being the third leading cause of death. Creating a culture of best practices is essential for improving patient safety and outcomes.

More Related Videos

Errors as a Means of Reducing Impulsive Food Choice
07:07

Errors as a Means of Reducing Impulsive Food Choice

Published on: June 5, 2016

9.3K
Proofreading and DNA Repair Assay Using Single Nucleotide Extension and MALDI-TOF Mass Spectrometry Analysis
11:08

Proofreading and DNA Repair Assay Using Single Nucleotide Extension and MALDI-TOF Mass Spectrometry Analysis

Published on: June 19, 2018

10.3K

Related Experiment Videos

Last Updated: Mar 3, 2026

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

12.6K
Errors as a Means of Reducing Impulsive Food Choice
07:07

Errors as a Means of Reducing Impulsive Food Choice

Published on: June 5, 2016

9.3K
Proofreading and DNA Repair Assay Using Single Nucleotide Extension and MALDI-TOF Mass Spectrometry Analysis
11:08

Proofreading and DNA Repair Assay Using Single Nucleotide Extension and MALDI-TOF Mass Spectrometry Analysis

Published on: June 19, 2018

10.3K

Area of Science:

  • Health policy
  • Patient safety
  • Medical ethics

Background:

  • The United States healthcare system is experiencing a significant crisis.
  • Preventable clinical errors represent a major public health concern, ranking as the third leading cause of death.
  • There is a critical need to address systemic issues contributing to medical errors.

Purpose of the Study:

  • To highlight the severity of preventable medical errors in the US healthcare system.
  • To advocate for the establishment of healthcare cultures prioritizing best practices.
  • To emphasize the urgency of transforming healthcare delivery to enhance patient safety.

Main Methods:

  • This abstract does not detail specific methodologies but focuses on a critical analysis of the current healthcare landscape.
  • It calls for a cultural shift within healthcare institutions.
  • The emphasis is on systemic change rather than a single intervention.

Main Results:

  • Preventable clinical errors are a leading cause of mortality in the US.
  • The current healthcare culture is insufficient in preventing these errors.
  • A significant gap exists between current practices and optimal patient care standards.

Conclusions:

  • Immediate action is required to address the healthcare crisis.
  • Fostering a culture where best practices are the norm is crucial for reducing medical errors.
  • Transforming healthcare culture is paramount to improving patient outcomes and safety.