Clarifying accuracy – with help from ISO IWA 15

Oct 01, 2015

One of the benefits to participating in standardization projects1 such as ISO IWA 15 is the opportunity to work with experts from a variety of countries, companies and backgrounds. Each participant brings their unique perspective and then everyone works together to find and describe common points of agreement.   One example of reaching common agreement and finding a way to express it is a graphical figure that describes the relationship between Accuracy and five other ideas.

Note 1: ISO IWA 15 is an International Workshop Agreement, titled “Specification and method for the determination of performance of automated liquid handling systems”.  This document deals with volumetric performance including measuring and expressing the liquid delivery accuracy of such systems.

Accuracy is a particularly important concept because it is foundational to a quantitative laboratory measurement. Accuracy invokes an image of something that is correct, reliable and trustworthy. I have never met a conscientious laboratory professional who will say that they don’t care about accuracy; as a conceptual goal, accuracy is nearly universally sought after.

However, what is it precisely that we mean when we speak of accuracy? Try this experiment: The next time someone uses the word “accuracy”, engage in a conversation and try to understand as clearly as possible what they mean by the term. These are some of the things I’ve heard:

  • Highly consistent results (e.g., a low standard deviation, or small CV).
  • An average which is very close to the true value.
  • Knowing that each measurement correctly represents what is present in the sample.

Removing ambiguity

In a previous article2, I mentioned two different ways that the word “accuracy” is used in the context of pipetting. There I described the accuracy of a single liquid delivery, and also how the average value of a group of dispenses can be evaluated for accuracy. This “double usage” of the term was fairly common at the time (and is still common today) but recent work in developing definitions for the ISO IWA 15 project has provided more precise explanations which help to clarify our thinking, and allow us to be more exact in what we are talking about.

Defining 6 key terms

Six terms in IWA 15 which relate to accuracy are:  Precision, Trueness, Accuracy, Random Error, Systematic Error and Uncertainty.  There is a logical arrangement between these, shown in Table 1.

Table 1. Relationships between error concepts and the way they are quantified.

Concept Quantitative Measurement
Accuracy  Uncertainty
Precision Random Error
Trueness Systematic Error

These terms might be more easily understood by use of the target diagrams shown in Figure 1.

Figure 1. Relationship between trueness, precision and accuracy

definition-of-accuracy-trueness-precision

Precision

Precision is a concept meaning that results are tightly clustered. Precision can be achieved regardless of where the cluster falls on the target. The degree of precision can be measured by quantifying the overall effect of all random errors using descriptive statistics such as standard deviation, relative standard deviation (RSD) or coefficient of variation (CV). Precision is necessary for achieving good accuracy, but it is not sufficient. Good accuracy requires both precision and trueness.

Trueness

Trueness is labeled on the vertical axis and like precision is a concept. The measure of trueness is systematic error (Note 2). The idea is that a measurement is true when it is aimed squarely at the center of the target.  A pipette which is true, will deliver on average a result which is close to the center.  As shown in the upper left target in Figure 1, it is possible to be true, while also having poor precision.  Trueness and precision are independent of one another.  Each can be increased or decreased without changing the other.

Note 2: Systematic errors can be positive or negative, and there can be multiple systematic errors in any measurement. Systematic errors can be additive, or offsetting. However the net effect of all systematic errors is what we are illustrating. So it would be slightly more correct to say that “trueness is quantified as the net effect of all systematic errors”. For simplicity, IWA 15 uses the term systematic error to mean the “net effect of all systematic errors”. This terminology is consistent with prior standardization work in ISO 5735 and ISO 8655. 3,4

Accuracy

Accuracy is a combination of trueness and precision. Good accuracy requires good trueness and good precision. Accuracy is measured and reported as an uncertainty. Thanks to the growing popularity of laboratory requirements standards such as ISO 170255, much has been written about uncertainty and the detailed procedures to how to calculate or estimate uncertainty. Uncertainty is frequently presented in a very mathematical way, with lots of equations. The mathematical expressions in authoritative documents such as the Guide to the expression of uncertainty in measurement6 , can create the impression that uncertainty is a mysterious and difficult concept. It is helpful to remember that uncertainty is simply a quantitative expression that tells us the accuracy of a measurement.

With these three concepts now defined, let’s return to the bullet list of three ideas and classify them using current terminology.

  • Highly consistent results (e.g., a low standard deviation, or small CV).

    Classification: PRECISION

  • An average which is very close to the true value.

    Classification: TRUENESS

  • Knowing that each measurement correctly represents what is present in the sample.

    Classification: ACCURACY

Adopting the definitions proposed in Figure 1 permits people to communicate more clearly about the issues that impact the accuracy of laboratory results. Careful use of this terminology allows us to be more exact in our thinking, and more exact in the remedy when seeking to improve the accuracy of laboratory results. As we see, good accuracy requires both good precision and good trueness. By deconstructing an accuracy challenge into its systematic and random components we are able to better identify opportunities for improvement.

There are many more good ideas to be found in IWA 15 and I look forward to seeing this document published in the near future. As soon as it is published, I plan to be back with more information on how to obtain IWA 15, how it could be useful to you, and also provide information on what’s expected to happen next in the world of liquid handling standards.


Additional Resources


References

1. ISO IWA 15 Specification and method for the determination of performance of automated liquid handling systems at http://iwa15.org/
2. Defining accuracy and precision, G. Rodrigues at http://www.qualitydigest.com/inside/fda-compliance-article/defining-accuracy-and-precision.html
3. ISO 5725-1 Accuracy (trueness and precision) of measurement methods and results – Part 1: General principles and definitions
4. ISO 8655-1 Piston-operated volumetric apparatus – Part 1: Terminology, general requirements and user recommendations
5. ISO/IEC 17025 General requirements for the competence of testing and calibration laboratories
6. JCGM 100:2008 Evaluation of measurement data – Guide to the expression of uncertainty in measurement (GUM)


About the Author

George Rodrigues, Ph.D.

George Rodrigues, Ph.D., is Senior Scientific Manager at Artel, the global leader in liquid delivery quality assurance. Rodrigues is responsible for developing and delivering communications and consulting programs designed to maximize laboratory quality and productivity through science-based management of liquid delivery. Rodrigues is Artel’s chief representative to key commercial clients, government regulatory bodies and industry organizations. His speaking and teaching engagements, along with his publications, build awareness of the challenges and solutions for laboratories in maintaining data integrity and confidence in their testing protocols. He plays a key role in developing the manufacturing and quality assurance processes for Artel products and organizes programs to assist pharmaceutical, biotechnology and clinical laboratories in improving their liquid delivery quality assurance and analytical process control. Rodrigues earned his BS in Chemical Engineering at the U.C. Berkeley, and a PhD in Chemical Engineering at the University of Wisconsin.