Advancing patient safety through essential quality indicators and informatics

Across modern clinical laboratories, data-driven quality control has become central to ensuring accuracy, reliability, and patient safety. Yet, despite widespread awareness of the value of quality indicators (QIs), many labs struggle to put them into consistent practice. Time constraints, limited resources, and complex data extraction can make monitoring difficult, even for well-established facilities.

These were among the challenges discussed during From Data to Action: Leveraging Essential Quality Indicators and Digital Solutions to Improve Patient Safety, the second webinar in the two-part series Quality Data, Informed Action: Metrics and Assay Performance Amplified by Quality Indicators, hosted by SelectScience^® in association with Siemens Healthineers. While part one explored analyzer performance and the analytical phase of testing, this second session focused on the pre-analytical and post-analytical stages and how informatics and digital tools can help laboratories transform their approach to quality measurement.

The presentation was led by Dr. Vincent De Guire, clinical biochemist and researcher at the Maisonneuve-Rosemont Hospital and the Optilab Montreal-CHUM laboratory network, and clinical assistant professor at the University of Montreal. Dr. De Guire also serves as chair of the IFCC Working Group on Laboratory Errors and Patient Safety (WG-LEPS) and as president of the Canadian program for quality indicators comparison. Drawing from both international and local initiatives, he demonstrated how laboratories can use standardized metrics to benchmark, identify weak points, and improve patient care.

Keeping the patient at the center

De Guire reminded attendees that behind every laboratory error is a patient who may experience very real harm. “Behind every laboratory error, there’s an impact for our patients,” he said. “The potential consequences can be extremely important. We can talk about delayed diagnosis and treatment, inappropriate or harmful treatment, direct impact on quality of life, extended hospital stays, and higher costs for the institution.”

De Guire explained that even seemingly small error rates can have large effects when multiplied by the number of samples a laboratory handles. “We’re managing over two million samples every year, only in biochemistry,” he highlighted. “If I multiply by the average rate of preanalytical errors we face in our lab based on international data, leading to sample rejection, only in my case, it would be more than 34,000 sample rejections per year. This is 34,000 patients that are affected by laboratory errors.”

Defining and standardizing quality

According to Dr. De Guire, the foundation of quality assurance in laboratory medicine lies in ensuring every step of the total testing process is correctly performed. He referenced a definition by Professor Mario Plebani, founder of the WG-LEPS, that describes quality as the guarantee that each phase of testing supports valuable decision-making and effective patient care.

“When it comes to the analytical phase, things are more in control,” he noted. “We have a lot of tools in place to control the analytical phase. However, we’re all aware that most laboratory errors are at the pre-analytic and post-analytical phase. It’s related to our processes. So how can we monitor this, benchmark this, and improve this? This is through quality indicators.”

A strong QI framework, De Guire said, must be patient-centered, comprehensive, and scientifically robust. “First, it needs to be patient-centered, to promote total quality and patient safety,” he explained. “Secondly, we need to cover the total testing process. That means the pre-analytic, the analytic, and the post-analytical phase.”

Moving from measurement to improvement

The IFCC’s WG-LEPS has worked for more than two decades to develop internationally harmonized guidelines for QIs. “We actually have three different consensus group meetings to define our guidelines,” De Guire shared. The outcome is a standardized list of 53 quality indicators that can be used to monitor every stage of the testing process.

To show how these can be implemented in practice, De Guire shared an example from his own laboratory during a major system transition. “We replaced our chemistry and immunology instruments and lost automation for almost a year,” he explained. “We started doing risk analyses of our processes and selected two key quality indicators that were very valuable for us – the turnaround time of potassium from reception in the lab to release of results, and the rate of sample rejection related to excessive time of management.”

To visualize results and spot issues quickly, De Guire’s team built a dashboard. “We developed this dashboard in Excel,” he said. “We were generating it weekly, looking at performance every day and spreading turnaround time based on hours when there was a suspicion of a problem. We were able to identify that a specific problem occurred in the morning at the change of shift between the team. We discussed this with the team, identified the problem, and made significant change so it won’t happen again.” But this work was time consuming and De Guire recognized the need to automate these insights with informatics tools.

Benchmarking for context and collaboration

Monitoring quality is only meaningful when laboratories can see how their performance compares to peers. De Guire underscored that there is still work to do to begin measuring and comparing quality processes across labs. “How can I know if the performance is optimal? How can I have a clear target of what is a good performance?” De Guire asked. “When it comes to the quality of the analytical phase, could you imagine running your lab without any EQA? It’s not the case when it comes to our processes and follow up of quality indicators.”

By participating in national and international benchmarking programs, laboratories gain perspective and confidence in their performance. “If you look at our performance before and after losing automation, we actually had a slight increase of turnaround time,” he said. “But considering the loss of automation, we’re on the median. We know we’re in control, we know we’re good to go, because I’m able to compare with all my peers across Canada.”

De Guire strongly encouraged laboratories to participate in the IFCC Quality Indicators Comparison Program, which allows free data submission for one or several indicators. “You need to bring your initiatives and quality indicators monitoring to the next level,” he cautions. “You need to make sure you’re able to compare with benchmark. It can be with literature, with the IFCC program, or with national comparison programs.”

Establishing essential quality indicators

Although the IFCC list contains 53 indicators, participation rates have remained lower than desired. “Users are claiming that the number of QIs are excessive,” De Guire explained. “People are struggling with data collection, data analysis, and production of reports.”

To address this, the WG-LEPS recently convened a third consensus meeting hosted in Quebec, which led to the creation of a smaller essential set of six key indicators focused on patient outcomes. “We wanted to select a smaller set of what we call the essential quality indicators to really facilitate the process, maximize participation, and also make sure we’re all working in the same direction,” said De Guire.

These six indicators span the total testing process, with particular emphasis on the pre-analytical phase where most errors occur. Among them are the rate of misidentified samples or requests, the overall rate of sample rejection, indicators related to hemolysis and blood sampling quality, turnaround time for troponin, the rate of corrected laboratory reports, and the rate of unacceptable EQA schemes.

“We strongly recommend to prioritize these quality indicators,” he said. “The list of the 53 still exists and is extremely important. What we recommend is to work all together in the same direction, prioritizing this panel when it comes to continuous follow up of our processes.”

Automation, informatics, and accessibility

De Guire highlighted that automation and digital tools are essential to make quality data easier to collect and act upon. “We were able to build this in our LIS, and it facilitated the process so much to record errors and provide clear, standardized reports,” he noted. At a broader level, Quebec’s laboratory network has integrated IFCC QIs into a standardized informatics platform, enabling harmonized reporting across the province.

De Guire also described collaborative projects between the IFCC, European Federation of Laboratory Medicine, and regional bodies to align and report on QIs. This, he said, will help labs “declare the same thing, the same way” and allow seamless comparison of preanalytical errors worldwide.

The ultimate goal is to make root-cause analysis and feedback faster and more meaningful. “Right now, when it’s time to submit my data in the IFCC program, it literally takes me two minutes,” said De Guire. “I can interact with the dashboard and do live, personalized root cause analysis.”

A shared responsibility for patient safety

To close, Dr. De Guire reminded laboratories that implementing QIs is not just an accreditation requirement, but a shared commitment to patient care. “We need to put effort to assess the robustness of our processes,” he concludes. “Make sure you’re in line with international guidelines, bring your game to the next level, and participate in comparison initiatives to really improve patient safety and outcomes.”

The PACE^®- and ACCENT^®-accredited webinar From Data to Action: Leveraging Essential Quality Indicators and Digital Solutions to Improve Patient Safety is now available to watch on demand, along with part one of the series, Precision in Practice: Using Metrics to Elevate Laboratory Quality.