Harnessing digital solutions to reduce pre-analytical errors in medical laboratories

Contributing lab leader: Amalia Ruiz Serrano

A significant challenge for laboratories and hospitals is that 62% of errors in the diagnostic process occur before samples even reach the lab, known as the pre-analytical phase of laboratory testing. Despite the high incidence of such errors, numerous medical laboratories still rely on handwritten data collection methods, and the use of paper records persists.1

This reliance on manual processes not only proves to be inefficient but also increases the vulnerability to errors in the overall diagnostic workflow. With mistakes in incorrect labeling of tubes, tube filling errors, and patient identification errors that occur at the pre-analytical phase,2 there is a clear need for a more streamlined and automated approach to monitoring patient test samples even before blood collection takes place to enhance accuracy and efficiency in the end-to-end process of diagnostics.

To address these errors, lab manager can implement digital cloud-based solutions that track samples during the pre-analytical phase, offering a platform connecting the lab’s Laboratory Information System (LIS) with pre-analytic digital solutions from various tech companies to address pre-analytical challenges. This setup provides lab managers with the flexibility to choose the solutions that best meet their specific needs. The enhanced connectivity provides enhanced visibility into the pre-analytical pathway of samples, streamlining operations with minimal additional effort while substantially minimizing the likelihood of errors.

Implementing digital sample tracking during sample ordering, collection, transportation, and reception can enable greater control of the pre-analytical process by:

  • Reducing costs by decreasing errors
  • Providing actionable, data-driven insights for lab
  • Improving lab process efficiency

Article highlights:

  • Many medical labs still use outdated handwritten and paper-based record-keeping methods, leading to errors occurring before samples reach the lab.
  • Common pre-analytical mistakes that arise include incorrect labeling of tubes, tube filling errors, and patient identification errors.
  • Digital sample tracking can reduce errors and save costs for lab managers, streamlining patient sample monitoring.
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Case study: Implementing sample tracking at CBT Bonn

The problem


The Center for Blood Coagulation Disorders and Transfusion Medicine (CBT) in Bonn, Germany, embarked on a mission to reduce errors in the pre-analytical phase, recognizing the potential consequences within laboratory operations if they did not address the errors. The CBT Group's portfolio includes laboratory medicine to hemostasis, transfusion medicine, endocrinology, gynecology, cytology, pathology, and molecular diagnostics.6

In laboratory practices, a single pre-analytical error in North American and European hospitals costs US $206 on average. These errors contribute to approximately 0.7% of the total operating costs.7 Addressing and mitigating such errors is crucial for operational efficiency and cost management within healthcare institutions.

Previously, CBT Bonn's blood sample collection process lacked digitalization, relying on handwritten records which were then manually digitized by in-house personnel. The laboratory can receive up to 120 samples a day, and with their current approach, this process resulted in high personnel costs, limited scalability, and was prone to input errors. With a commitment to quality management and a focus on the comprehensive blood sample workflow, the center explored integrating a pre-preanalytical (PPA) solution within the CBT LIS using automated sample tracking.8


The solution


As a result, the PPA solution allowed for digitized sample information of crucial information such as patient ID confirmation, sample collection details, and order completion timestamps. Other significant patient-related details, including collection difficulties, were also incorporated into the digital format. This digitalization enhanced sample collection data management allowing for a more comprehensive understanding of patient information.


The results


Utilizing a cloud-based sample tracking system and a digital PPA solution helped CBT Bonn consistently reduce reported error rates over a timespan where over 50,000 samples were processed. Notably, during the implementation of digital sample tracking, errors in inappropriate containers went from 0.34% to zero. Tube filling and problematic collection errors also significantly reduced, dropping from 2.26% to less than 0.01% and 2.45% to less than 0.02%, respectively. The frequency of missing test tubes decreased from 13.72% to 2.31%.9 As a result, the implementation of sample tracking streamlined workflow efficiency, minimizing paper documentation, automating quality assurance, and reducing the likelihood of order misinterpretation.

The integration of the sample tracking system has supported CBT Bonn's ability to oversee the quality of blood collection processes, in line with the CBT group's vision to support a digitally enhanced patient care journey. This initiative is part of a broader effort to develop an all-encompassing patient platform that aggregates all pertinent data during the preanalytical phase, thereby ensuring quality control and setting a new benchmark in laboratory medicine aimed at reducing unnecessary expenditures, avoiding misdiagnoses, and preventing incorrect treatment plans.8

Harnessing advanced data analysis, CBT has the opportunity to identify meaningful correlations between phlebotomy notes and diagnostic outcomes, conduct insightful comparisons of error rates across diverse locations, and strategically assess workload distribution throughout the month.

Gaining efficiency without compromising quality

Digital, automated sample tracking offers laboratory managers and leaders a streamlined process for continuous monitoring of patient samples that reduces errors, leading to cost savings. Before implementing these technologies, lab leaders should ensure that systems are simple to use such that personnel can easily incorporate them into existing infrastructure. 

By improving turnaround time and decreasing the need for resampling of patients, the digitalization of sample tracking improves operational efficiencies and enhances the overall quality of results. Sample tracking offers a value-added component to healthcare, benefiting patients, practitioners, and health systems alike.

To learn more about how implementing digital technology improved CBT’s pre-analytical pathways, click here!

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  1. Das et al. (2021). Asian J Med Sci 12, 31-38. Paper available from [Accessed February 2024]

  2. Plebani. (2012). Clin Biochem Rev 33, 85-88. Paper available from [Accessed February 2024]

  3. El-Khoury. (2019). Information available at [Accessed February 2024]

  4. Plebani (2023). Article available from [Accessible February 2024]

  5. Lippi G, Mattiuzzi C, Favaloro EJ. (2023). J. Med. Biochem. 42, 1-10. Paper available from [Accessible February 2024]

  6. CBT. Webpage available from [Accessible February 2024]

  7. Green. (2013). Clin Biochem 46, 1175-1179. Article available from [Accessible February 2024]

  8. Löckenhoff. (2023). Page 16. Article available from [Accessible February 2024]

  9. Roche. (2024) Article available from [Accessible March 2024]