Laboratory Results Processing — How to Make the Work Clearer

The core task of a quality control laboratory is to produce reliable and comparable results. Laboratory technicians are trained to perform analyses carefully, according to standards, and with full traceability. Work is carried out according to procedures, under the right conditions, and with professional skill — so that results are comparable regardless of who performed them.

That is the core of the work. And that is where the focus lies.

An experienced technician can often estimate the expected result level already during the analysis phase. The actual overall assessment, however, only becomes clear during the results processing and recording phase. And this phase is often where errors are most likely to occur.

Many laboratories perform multiple different analyses daily. Converting raw data into final results and entering them into systems tends to pile up toward the end of the working day — precisely when the sharpest concentration has already been used and fatigue is understandable.

Based on my own experience as a laboratory technician, the most mentally demanding phase was not the analysis itself or the workload involved, but processing the results and entering them into various tables and programs. Results were often handled across multiple systems and entered into different programs for different stakeholders. You had to remember where certain results were calculated and which table each result belonged to.

This is exactly the phase where concentration should be focused on evaluating the correctness of results. In practice, however, attention is easily divided between remembering and navigating between systems.

And that is when the risk of error increases.

Why does this happen?

It is not a question of competence. It is not a question of carelessness.

It is a question of process.

When a system is built from several separate stages and information is transferred manually from place to place, the work burdens memory more than is appropriate. A laboratory technician should be using their expertise to evaluate results — not trying to remember which files or tables data flows through.

People are not designed to function as an integration interface between systems.

When memory load increases and the working day stretches, the risk of error inevitably grows. This is not an individual weakness — it is a structural consequence.

Limit Values and Result Evaluation

Through repetitive work and experience, a technician often learns to evaluate the level of results already during the analysis phase. Many deviations are noticed before the result has even been recorded in the system — determining whether the result is valid, whether the analysis needs to be repeated, or whether the deviation is genuine.

The actual evaluation, however, only takes place during the results processing phase. Results are compared against previous measurements, the normal level of production, and analysis-specific limit values. A deviating result may indicate a genuine change in the process — but equally, an analysis error or a simple typographical mistake.

This evaluation should be the central part of the work.

In practice, evaluation often happens simultaneously with result calculation and recording. When the volume of analyses is high and results are handled across multiple systems, it is not realistic to expect all limit values to remain in memory.

This is why deviations should be made visible directly in the system. Clear visual indicators — such as color highlights — help the technician quickly identify when a result deviates from the normal range and requires closer evaluation.

If a limit value is exceeded, that information should also be communicated automatically. Daily notifications or automated messages ensure that deviations do not rely on any single person's memory, but that information reaches the right people without separate reporting.

What Happens When an Error Is Detected?

Errors happen — it is human. What matters is not the complete prevention of errors, but what happens afterward.

If a limit value exceedance is clearly visible in the system, the deviation will not go unnoticed. It may indicate a genuine change in the process — or equally, a simple typographical error.

This is why it must be possible to correct results in a controlled manner. Changes should also remain visible: what was changed, when, and why. This way, an individual result and the entire analysis history of a sample remain traceable even when errors are being corrected.

Traceability is not lost due to an error — on the contrary, it is documented.

Conclusion

A good results system brings clarity to the work above all else. Results are found in one place, their level is easy to evaluate, and deviations are easier to detect.

It also helps that results can be accessed regardless of time and place. The ability to check previous results — for example, during an ongoing analysis, or from a mobile device when needed — reduces unnecessary interruptions and supports decision-making during work.

In many laboratories, results are still processed in Excel. It is a versatile and flexible tool, and for tasks like creating graphs or reviewing data, it works well. There is nothing inherently wrong with Excel.

The challenge is that it was not designed for laboratory results management. When the same tool is used to handle data entry, processing, monitoring, and reporting, the responsibility for managing the whole easily falls on the user.

When tools are built specifically for the purpose they are used for, they support the work — rather than burden it.

A good system does not do the laboratory technician's work for them — but it gives them the opportunity to do their work better.

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How has your laboratory solved the challenge of results processing?