Abbott Molecular - Assessing performance of molecular testing

The accuracy of diagnostic testing is vital in helping clinicians make the best possible medical recommendations. Compromised test results can have serious ramifications for the patient's health and well-being. Sten Westgard, director of client services and technology, Westgard QC, explains how the Six Sigma metric employed by Abbott Molecular aids optimal performance of diagnostic assays in molecular laboratory testing.


Why is precision and accuracy so important for patient care?

Sten Westgard: Laboratories are constantly under pressure to provide accurate results due to the cost associated with therapies. This is understandable because disease status and therapy decisions are often based on a single positive or negative result. In the case of molecular viral-load testing of patients with hepatitis or human immunodeficiency virus (HIV) infections, expensive antiviral therapies are continued, modified or terminated based on laboratory results. If these results are inaccurate, that may force patients through additional rounds of confirmatory testing or altogether unnecessary resistance testing, which can add expense and anxiety to the physician and patient. HIV and hepatitis clinical decision points are at the lower end of the assay's analytical range; therefore, test result accuracy and precision near these decision points is now even more important.

Why do we need quality measures?

Laboratory medicine accepts the fundamental importance of quality. The main goal of diagnostic testing is to provide results that are accurate and precise, and reflect true patient status. But we cannot be sure of the tests' quality without appropriate tools to measure whether required accuracy has been met. Unfortunately, there is an assumption that the laboratory's test results are always valid, meaning they are unaffected by medically important errors that might change clinical decisions taken by a physician. How can we ensure that medical decisions are not made based on faulty assumptions? Naturally, we want to avoid patient diagnosis or treatment being endangered by poor test performance. What we need to know is how to analyse our quality-control data to prove that the assay is functioning properly.

How can molecular diagnostic laboratories assess their viral-load assay's performance?

Answers can be found in the statistical assessment of results derived from testing quality-control material. The statistical tools are collectively known as Sigma metrics. The Six Sigma quality measure can be applied to any process, identify what the defects are, assess them when they occur and implement improvements that reduce or eliminate the occurrence of those defects. For viral-load assays such as quantitative HIV-1 or hepatitis, we can define a defect as any instance in which a patient result is misinterpreted, thus compromising medical decisions. Applied Sigma metrics can help with objective assessment and comparison of analytical methods and instrumentation performance. Six Sigma has been adopted by manufacturing and service industries, as well as healthcare institutions, from hospitals to reference laboratories.

Part of the power of the Six Sigma scale is its ability to provide a universal benchmark. Sigma metrics allow comparison of different processes with each other, even comparing processes across different institutions and industries. For example, airline safety is known to surpass Six Sigma, with a rate of only 1.5 crashes every million departures, while airline baggage handling in the US is only 4.1 Sigma since approximately 0.5% of luggage is misplaced or lost, and US airline departures perform at only 2.3 Sigma since nearly 30% of flights are delayed, which helps to explain chronic customer complaints. Examining the death rates at US hospitals reveals that healthcare is performing at only 3.8 Sigma (48,000-90,000 unnecessary deaths a year). If healthcare were achieving Six Sigma, the death rate would be only 16-34 deaths a year.

The goal of Six Sigma is to eliminate or reduce all variation in a process. Variation in a process leads to duplicated effort and wasted resources on retesting and workarounds. Reducing defects lowers costs, improves performance and enhances profitability. A process, procedure or an assay that achieves the goal of Six Sigma delivers high quality and efficiency.

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