Contributing lab leader: Oguzhan Zengi, Assoc. Prof. EuSpLM
Reducing human error in the coagulation lab: The role of automation in ensuring accurate diagnostic results
Clinical diagnostics inform 70% of physicians' decision-making, playing a crucial role in treatment strategies.1 However, manual errors in the coagulation lab—such as imprecise sample handling, mislabeling, and incorrect data entry—can compromise diagnostic accuracy, delay treatment, and pose risks to patient safety.1 For healthcare organizations, these errors also lead to unnecessary labor costs and wasted resources.1
Additionally, processes that involve hands-on, manual processes are difficult to standardize, not just procedures between lab personnel, but also the replication of results by other labs.2 The inability to reproduce workflows can cause unreliable and inaccurate results.
Today, advanced technologies that leverage automation are reducing the rate of manual errors typically seen in the clinical setting.1 By taking this approach, leaders running a coagulation lab can provide clinicians with more precise diagnostic results in less time, especially as the demand for diagnostic testing continues to rise.3 This ensures that patients receive the most appropriate care for their specific disease in a timely manner.
Article highlights:
- Coagulation tests require precision in delivering results to ensure that clinicians can diagnose patients correctly.
- In the clinical lab, human errors can occur that lead to incorrect diagnostic results and wasted healthcare resources.
- Lab leaders running coagulation labs must incorporate automation strategies to ensure timely delivery of diagnostic tests to help reduce manual-based errors.

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Errors can occur at any stage of the clinical testing process—pre-analytical, analytical, and post-analytical. Reports indicate that 75% of testing errors happen during the pre-analytical phase, which includes sample collection, receiving, and storage.1
Common pre-analytical errors include:1
- Sorting and mistakes in transportation
- Labeling inaccuracies
- Order entry errors
- Sample collection issues
During the analytical phase, sample mix-ups, quality control failures, and lack of workflow standardization are common occurrences.4 Meanwhile, in the post-analytical stage, errors in data entry and analysis, as well as mistakes during reporting, further compromise diagnostic accuracy.5 These errors and unreliable results prevent doctors from correctly diagnosing patients.
Automation significantly reduces errors, particularly during manual, repetitive, and complex tasks during the pre-analytical and analytical phases. By handling high sample volumes with precision, automated systems minimize costly mistakes and optimize resource management by reducing the need for repeat patient testing.6
For lab personnel, automation alleviates time-consuming, repetitive tasks, allowing them to focus on high-value activities, such as complex diagnostics requiring human expertise.7 This supports advanced testing capabilities, ensuring high sensitivity and specificity for complicated diseases. Automation also enhances turnaround time, enabling 24/7 high-throughput testing to meet patient demand.8
Another key advantage of automation is enabling seamless digital integration, which enhances data integrity, real-time access, and seamless connectivity with laboratory information systems (LIS).6,9 By reducing errors, automation boosts overall lab efficiency, credibility, and reliability in delivering dependable results.
The coagulation lab needs to deliver precise results to ensure that patients suffering from clotting and bleeding disorders are identified rapidly and treatment strategies are correctly administered. However, errors can arise from manual processes within the clinical lab, such as labeling errors, mishandling of samples, and incorrect data entry, leading to delays in therapeutic interventions.
Transitioning from manual processes to modern automated platforms is a critical step for lab leaders. Automation strengthens consistency, operational workflows, and standardization, which is particularly critical for regulatory compliance. Furthermore, it enables cost savings for healthcare systems, reducing the amount of unnecessary sample re-testing.
The future of automation is promising, not only in patient diagnosis but also in biomarker and drug discovery.10 Labs play a crucial role in supporting researchers by facilitating studies in these areas and enhancing the development of new diagnostic and therapeutic solutions.
By minimizing human errors, automation drives greater diagnostic accuracy and impacts patient outcomes. Standardized, reliable processes lead to precise diagnoses and high-quality care, reinforcing the important role of automation in modern healthcare systems.