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Related Concept Videos

Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

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...
Common Leveling Mistakes and Errors01:17

Common Leveling Mistakes and Errors

A survey team is tasked with determining the elevation difference between points Point A and Point B, separated by uneven terrain. They use a leveling instrument and a leveling rod.Common MistakesMisreading the Rod: During a backsight reading at Point A, the instrumentman observes the rod partially obscured by tall grass. Instead of reading 1.135 m, they mistakenly record 1.735 m due to the misalignment of the crosshair with the wrong graduation. This error adds 0.600 m to all subsequent...
Errors in Taping01:18

Errors in Taping

Errors in taping arise from multiple factors that can significantly impact measurement accuracy in surveying. Misalignment of the tape, often due to human error, is one primary source. A skilled rear tapeman, using a telescope, can help correct alignment by guiding the head tapeman; however, human limitations still lead to small inaccuracies. These errors may include misplacement of pins or inaccurate tape readings due to common visual confusions, such as mistaking a six for a nine. Such...
Errors and Mistakes in Surveying01:19

Errors and Mistakes in Surveying

Errors and mistakes in surveying refer to inaccuracies in measurements and data recording. The errors are deviations from the actual value caused by human sensory limitations, equipment flaws, or environmental effects. These errors are typically unintentional and can result from the inherent imperfections in the instruments used, atmospheric conditions, or the observer’s inability to perceive exact measurements. On the other hand, mistakes are caused by the surveyor's lack of attention,...
Contaminants and Errors01:16

Contaminants and Errors

Effective sample preparation is crucial for accurate and reliable laboratory analysis. During this process, two significant sources of error can arise: concentration bias from improper sample splitting and contamination caused by methods used to reduce particle size, such as grinding or homogenization. Identifying and minimizing these potential errors is crucial to ensuring the validity of the analysis.
Another key consideration is determining the appropriate number of samples required to...
Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...

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Related Experiment Video

Updated: Jun 1, 2026

Driving Simulation in the Clinic: Testing Visual Exploratory Behavior in Daily Life Activities in Patients with Visual Field Defects
11:12

Driving Simulation in the Clinic: Testing Visual Exploratory Behavior in Daily Life Activities in Patients with Visual Field Defects

Published on: September 18, 2012

Driving out errors,.

Matthew Weinstock

    Hospitals & Health Networks
    |May 20, 2011
    PubMed
    Summary
    This summary is machine-generated.

    Eastern Maine Healthcare Systems aims for zero medical errors. Their strategy involves strong leadership, robust processes, and impactful communication to achieve patient safety.

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    Area of Science:

    • Healthcare Management
    • Patient Safety
    • Quality Improvement

    Background:

    • Medical errors pose significant risks to patient well-being and healthcare system efficiency.
    • Achieving zero medical errors requires a comprehensive and multi-faceted approach.

    Purpose of the Study:

    • To outline the strategy employed by Eastern Maine Healthcare Systems to achieve the goal of zero medical errors.
    • To highlight key components of their error reduction initiative.

    Main Methods:

    • Implementing highly involved leadership commitment to patient safety.
    • Designing and enforcing "fail-safe" processes to minimize human error.
    • Utilizing a powerful, emotionally resonant image for communication and reinforcement.

    Main Results:

    • The strategy focuses on creating an environment where medical errors are proactively prevented.
    • Leadership engagement and process design are central to the error-reduction efforts.
    • Communication strategies aim to deeply embed the zero-error goal.

    Conclusions:

    • A combination of strong leadership, foolproof processes, and impactful communication can drive significant progress toward eliminating medical errors.
    • Eastern Maine Healthcare Systems' approach offers a model for other healthcare organizations striving for enhanced patient safety.