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Special Series: Quality Assurance

An exclusive collection of articles from our print editions, all in one convenient place.

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Throughout 2011 and 2012, we've been running an exclusive Quality Assurance series in print issues of ADVANCE for Administrators of the Laboratory. Here, those articles are presented in one place for you to explore. Read and share the articles of value to you--and leave us a comment in the area below telling us how you are assuring quality in your lab.

Learning from Laboratory Failures
Despite best intentions, out-of-control conditions will occur and it is the lab's responsibility to deal with them in a manner that minimizes patient harm. Sometimes out-of-control conditions occur because of manufacturing defects in reagent systems, for example, microbial contamination in some small number of reagent packs. Other times mechanical or electronic failures or other environmental factors cause undetected failures in the test system. When failures occur, in addition to detecting and correcting the failures along with any unreliable patient results produced because of the failures, a good QC and risk management program also investigates failures to identify potential opportunities for improving the overall quality of the total test system.

Statistical QC and Risk Management
Risk management provides a formal approach to identify potential failure modes in the lab, rank those modes in terms of their risk, and establish policies and procedures to prevent or reduce (mitigate) the risks. The concept of risk has different definitions depending on the area of application. In the risk management arena risk is a concept comprised of two components: the likelihood of occurrence of an unwanted outcome and the severity of the unwanted outcome. In laboratory medicine, the unwanted outcome is generally defined as patient harm.

A Closer Look at Control Material
There are typically two sources of control materials: the instrument, kit or method manufacturer (manufacturer-supplied controls) and manufacturers of control materials (independent or third-party controls). These are further characterized into three types: dependent, semi-dependent and independent (third party) controls. Each has a risk profile. This article takes an in-depth look at control materials and offers valuable comparison information.

Analytical Assessment in the Clinical Laboratory
For a variety of reasons--consolidation, automation and rising sophistication in testing platforms--it is increasingly common to have multiple instruments or analytical "modules" that evaluate the same analyte in clinical diagnostic laboratories. Parallel test systems can produce high throughput and improved turnaround times, but they also create additional quality assurance issues. An important quality management decision, therefore, is determining how much difference between analytical modules (or instruments) can be tolerated while maintaining an acceptable quality level.

The Focus of Laboratory Quality Control
QC thinking that focuses on the instrument is concerned with the likelihood that a QC rule will trigger an alert after an error condition has occurred. Instrument-focused QC strategies are designed to control the number of QC events required to detect an error condition. QC thinking that focuses on the patient, on the other hand, is concerned with how many unreliable patient results are produced while an undetected error condition exists. Patient-focused QC strategies should be designed to control the number of unreliable patient results produced before the error condition is detected.

Designing a Quality Control Strategy
In the modern laboratory, the majority of instruments perform discrete testing. With automated discrete analyzers there is no longer a natural association between a set of QC results and a batch of patient specimens. Instead, QC results simply reflect the status of the test system at a point in time when the QC samples are tested. If the QC sample results are unacceptable, it suggests that a problem has occurred sometime earlier. This implies that if the laboratory doesn't do something to correct the problem then most assuredly future patient results will be adversely affected, but it doesn't give the laboratory any information about how many previous patient results were adversely affected. Learn how to develop a strategy that makes the most out of QC testing.

The Frequency of Quality Control Testing
There are two different ways that the frequency of QC testing can be considered-in terms of the time between QC evaluations or the number of patient specimens examined between QC evaluations. Two laboratories that perform QC testing at the same frequency in terms of time could be testing at very different frequencies in terms of number of patient examinations between QC evaluations. Likewise, two laboratories that perform QC testing at the same frequency in terms of number of patient examinations between QC evaluations could be testing at very different frequencies in terms of the time interval between QC evaluations.

 Recovering from an Out-of-Control Condition
Recovering from an out-of-control condition always has an element of difficulty, but it can be much easier with some preparation. One of the most important things you can do in preparation for analytical problems is to establish how much error in a patient's result can be tolerated before it is considered unacceptable for its intended use, and how many unacceptable patient results are likely to be produced as a result of the test system experiencing an out-of-control condition of a given size.

Sigma Metrics, Total Error Budget and QC
Sigma values and total error budgets can help provide general guidance on how well a laboratory's test system performance and QC procedures align with its specified quality goals. Ideally, a laboratory should strive for a total error budget of 33% or less. Then the laboratory can be assured that their test system performance and QC procedures will be properly aligned with their quality goals.


 

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Jo  McKenna,  Lab Consultant,  Self-employedJanuary 20, 2012
Townville, SC




     

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