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Related Concept Videos

Introduction to Statistical Process Control01:15

Introduction to Statistical Process Control

Statistical Process Control (SPC) is a method used to monitor and control quality within processes, particularly in manufacturing and service delivery, by employing statistical methods. SPC aims to distinguish between natural (common cause) variation and variation due to specific changes or events (special cause), allowing for timely improvements and sustained quality. The control chart, a pivotal tool in SPC, visually displays data over time alongside a central line of upper and lower control...
Reducing Line Loss01:18

Reducing Line Loss

In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss in...
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.
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Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

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...

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Related Experiment Video

Updated: Jun 13, 2026

A New Hybrid Quantitative Evaluation Model for Axillary Junctional Hemorrhage in Swine
08:27

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Published on: December 6, 2024

Blood wastage reduction using Lean Sigma methodology.

Eugenie S Heitmiller1, Richard B Hill, Christi E Marshall

  • 1Division of Transfusion Medicine, Department of Pathology, the Center for Innovation in Quality Patient Care, The Johns Hopkins Hospital, Baltimore, Maryland 21287, USA. eheitmi1@jhmi.edu

Transfusion
|May 12, 2010
PubMed
Summary

Implementing Lean Sigma methodology significantly reduced hospital red blood cell (RBC) wastage by over 50%, saving substantial costs and improving blood product management.

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Area of Science:

  • Healthcare Management
  • Transfusion Medicine
  • Process Improvement

Background:

  • Hospital red blood cell (RBC) wastage rates range from 0.1% to 6.7%, with a specific institution reporting 4.4% wastage.
  • A significant portion of wastage stemmed from units dispensed but not administered or temperature-related issues with transport containers.

Purpose of the Study:

  • To investigate the effectiveness of Lean Sigma methodology in reducing RBC product wastage.
  • To decrease RBC wastage by 50% through targeted interventions.

Main Methods:

  • An interdisciplinary team applied the five-part Lean Sigma process (define, measure, analyze, improve, control).
  • Focused interventions on container wastage and staff training regarding RBC handling and temperature monitoring.

Main Results:

  • RBC wastage was reduced from 4.4% to a sustained rate below 2%.
  • This reduction prevented approximately 4300 RBC units from being wasted annually.
  • The study yielded savings of approximately $800,000 over four years.

Conclusions:

  • Lean Sigma methodology proved effective in significantly reducing RBC wastage in a large academic hospital setting.
  • Addressing staff awareness, training, and temperature management protocols are key to minimizing blood product waste.