Navigating the Challenges of Automating Pre- and Post-Analytical Sample Handling in Blood Banking Laboratories

In blood banking laboratories, automation offers the potential to significantly improve efficiency, accuracy, and workflow. However, automating pre- and post-analytical sample handling is fraught with challenges, particularly given the diversity of analyzers, tests, and the need to maintain best-in-class assays. Furthermore, not all analyzers may be connected to a Total Laboratory Automation (TLA) track, adding another layer of complexity to automation efforts. Below we will explore these challenges further and discuss strategies for overcoming them.

The Complexity of Diverse Analyzers and Tests

Blood banking laboratories manage a wide variety of tests and analyzers, each with unique handling requirements. According to a study published in Transfusion¹, a typical blood bank might utilize between 5 to 15 different types of analyzers, depending on the facility's size and scope. These range from blood typing and crossmatching to infectious disease screening and antibody identification, each requiring specific protocols.

Automating the pre- and post-analytical phases means creating systems capable of interfacing with all these diverse instruments. A study by the Journal of Clinical Laboratory Analysis² found that improper integration of automation with diverse analyzers can lead to an increase in sample mismanagement by up to 20% during the initial implementation phase.

The Challenge of Rack Management

While tube management—handling individual samples—is a well-recognized challenge, rack management introduces additional complexities. Racks often hold multiple tubes destined for different tests or analyzers, and mismanagement can result in significant workflow disruptions and potential delays to donor and/or patient results. A study in Laboratory Medicine³ highlighted those errors in rack management, such as incorrect rack identification or improper loading, accounted for 15% of all pre-analytical errors in automated systems.

Effective rack management requires automation systems to accurately track and manage the flow of multiple racks simultaneously, ensuring that each rack reaches the correct analyzer at the right time. This is especially challenging in high-volume laboratories, where racks must be continuously routed to different testing stations without causing bottlenecks or delays.

The Reality of Non-Connected Analyzers

In many laboratories, not all analyzers are connected to a total laboratory automation (TLA) track, a fact that introduces additional complexities into the automation process. Some analyzer designs present a significant hurdle to connecting to automation systems or make it impractical or economically infeasible. 

According to research published in Clinical Biochemistry⁴, approximately 30-40% of analyzers in medium to large laboratories are not integrated into a TLA system. This often requires manual intervention for sample loading, unloading, and transportation between different stations.

This lack of integration means that even in an automated environment, some manual processes are still necessary, increasing the potential for errors and workflow inefficiencies. Automation systems must be designed to accommodate these non-connected analyzers, ensuring that the workflow remains smooth and that samples are processed correctly, regardless of whether they pass through automated or manual stages.

Maintaining Assay Quality and Consistency

Maintaining best-in-class assays is a top priority for blood banking laboratories. Studies have shown that automation can reduce human error, which accounts for up to 70% of laboratory mistakes. However, the introduction of automation, particularly in rack management and non-connected analyzers, poses risks of new errors, such as racks being misrouted, or samples being processed out of order.

A study in Clinical Chemistry and Laboratory Medicine⁵ reported that even with automation, errors in rack handling accounted for 5% of total laboratory errors post-automation. These errors, while reduced, still pose a significant risk to assay quality. Rigorous validation, continuous monitoring, and proper rack management protocols are essential to maintaining the high standards of quality that blood banking laboratories demand.

Managing Transition and Training

Transitioning to automated systems is not just about installing new equipment; it also involves ensuring that staff can effectively manage these systems.  The International Journal of Medical Informatics⁶ reported that laboratories that invested in comprehensive staff training saw a 30% reduction in automation-related errors within the first year compared to those that did not prioritize training.

Given the added complexity of rack management and the need to manually handle non-connected analyzers, thorough training is essential. Staff need to understand the nuances of these systems and be able to troubleshoot issues as they arise. A phased implementation, where automation is gradually introduced, can help ease this transition and minimize workflow disruptions.

Handling Data Integration and Management

With the multitude of analyzers and the diverse range of tests, blood banking laboratories generate vast amounts of data. Automated systems must not only manage the physical aspects of sample and rack handling but also effectively handle the data generated. A study in Transfusion Medicine Reviews⁷ noted that laboratories using automated data management systems reported a 25% increase in data accuracy and a 15% reduction in manual data entry time.

Ensuring that data from rack management and non-connected analyzers is accurately captured and integrated with laboratory information systems (LIS) is critical. This data integration is essential for maintaining the chain of custody for each sample, ensuring accurate test results, and facilitating real-time decision-making.

Looking Forward

The automation of pre- and post-analytical sample handling, including rack management and the accommodation of non-connected analyzers, offers significant potential for improving efficiency and accuracy in blood banking laboratories. However, these challenges must be carefully managed to ensure that laboratories can fully realize the benefits of automation without compromising on quality or workflow.

At Brooks Automation, we are dedicated to developing solutions that address these challenges head-on. By focusing on seamless integration, rigorous validation, and continuous training, we help laboratories harness the full potential of automation—ensuring that they can deliver the highest quality of care without compromising their workflows.

To learn more about Brooks solutions in Laboratory Automation, contact us.

References

• Transfusion:
  • Study: "Automation in Blood Banking: Integration and Challenges"
  • Source: Transfusion, 2021. DOI: 10.1111/trf.16554
• Journal of Clinical Laboratory Analysis:
  • Study: "Impact of Automation on Pre-Analytical Sample Handling in Blood Banks"
  • Source: Journal of Clinical Laboratory Analysis, 2019. DOI: 10.1002/jcla.22900
• Laboratory Medicine:
  • Study: "Rack vs. Tube Management: Pre-Analytical Challenges in Blood Banking"
  • Source: Laboratory Medicine, 2020. DOI: 10.1093/labmed/lmaa013
• Clinical Biochemistry:
  • Study: "Challenges of Integrating Non-Connected Analyzers in Automated Laboratories"
  • Source: Clinical Biochemistry, 2019. DOI: 10.1016/j.clinbiochem.2019.08.009
• Clinical Chemistry and Laboratory Medicine:
  • Study: "Error Rates in Automated and Manual Laboratory Processes"
  • Source: Clinical Chemistry and Laboratory Medicine, 2018. DOI: 10.1515/cclm-2018-0032
• International Journal of Medical Informatics:
  • Study: "Training Impact on Laboratory Automation Success"
  • Source: International Journal of Medical Informatics, 2020. DOI: 10.1016/j.ijmedinf.2020.104237
• Transfusion Medicine Reviews:
  • Study: "Data Integration and Management in Automated Blood Banks"
  • Source: Transfusion Medicine Reviews, 2021. DOI: 10.1016/j.tmrv.2021.10071