Reducing laboratory errors in pre-pre-analytical phase with navify® Sample Tracking

Success story

Female laboratory technician looking at tablet in a laboratory environment.

CBT Bonn

  • Leading healthcare provider in Germany with over 40 years of expertise

  • Operating across six sites

  • Processes samples from nearly 3,000 doctors and offers a range of outpatient and laboratory medicine services, including haematology, immunology, cytology, molecular diagnostics and endocrinology.

Reducing laboratory errors in pre-pre-analytical phase with navify Sample Tracking

The Center for Blood Clotting Disorders and Transfusion Medicine in Bonn, Germany, collaborated with Roche Diagnostics and the start-up Smart4Diagnostics (S4DX) to create navify Sample Tracking. This cloud-based software solution allows for efficient monitoring of patient samples from initial sampling to laboratory analysis.

Situation

Laboratories are all about delivering accurate, useful data, but some things are outside their control

Approximately 62% of errors in laboratory diagnostics occur in the pre-pre-analytical phase1, between the moment samples are collected and received by the lab. Many providers of digital solutions are trying to help laboratories address this significant challenge. However, there has been no comprehensive solution that focuses on the end-to-end pre-pre-analytical process — until now. Watch the video: Dr. André Körner answers 5 key questions on culture, innovation and transformation at CBT.

Higher testing quality enabled by greater process transparency

In designing this project, the three collaborators examined the complete process for the collection and transport of blood samples. This included original sample collection, transportation, checking and recording patient data for sample collection (e.g. time of collection).

With navify Sample Tracking, CBT was able to combine all sample-relevant pre-pre-analytical data, even if the data originated from different digital tools or suppliers, and connect this data directly with the laboratory information system (LIS).

The result was greater visibility into potential sources of testing errors, enabling laboratory managers to take prompt action, when necessary, to protect the integrity of sample quality and, ultimately, the quality of test results.

Solution

Significant reduction of errors in pre-pre-analytical phase

In the eight-month pilot phase of navify Sample Tracking, 60,000 patient samples were successfully digitized. In extensive test runs, the CBT project team compared error rates when using navify Sample Tracking with the average error rates in pre-pre-analytical phase. The results were clear: navify Sample Tracking produced significant improvements by reducing errors in sample filling, incorrect patient assignments and misinterpreted orders. In addition, because navify Sample Tracking produces a unique digital stamp for each sample, including time of blood collection, control for each orders’ completeness was automated and made more reliable. Above all, it eliminated confusion between samples — a highly relevant result given the previous error rate of nine percent during patient identification.

Results

Significant error reduction

Tube filling errors reduced from 2.26% to
0%within 2.25 years of implementing
Inappropriate container errors cut from 0.34% to
0%within 2.25 years of implementing
Difficult collection reduced from 2.45% to
0.02%within 2.25 years of implementing
Missing tube errors reduced from 13.27% to
2.31%within 2.25 years of implementing

For us, navify Sample Tracking is an essential part of value-based healthcare (VBHC) – just like the outcome measures reported by patients and collected by doctors. We are convinced that with navify Sample Tracking and other developments, we are making important contributions to VBHC.

André Körner

Head of Corporate Communications and the Department of Culture, Innovation and Transformation, CBT

Infographic comparing a complex, unstructured lab workflow with an optimized, streamlined process using navify Sample Tracking for improved efficiency and IT integration.
References and notes
  1. Cadamuro J, Gaksch M, Mrazek C, Haschke-Becher E, Plebani M. How do we use the data from pre-analytical quality indicators and how should we? J Lab Precis Med. 2018;3(6). DOI:10.21037/jlpm.2018.04.04.
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