Defining and Managing the Preanalytical Phase With FMECA: Automation and/or "Human" Control

Preanalytical Errors in Clinical Laboratory Testing at a Glance: Source and Control Measures

The accuracy of diagnostic results in clinical laboratory testing is paramount for informed healthcare decisions and effective patient care. While the focus has traditionally been on the analytical phase, attention has shifted towards optimizing the preanalytical phase due to its significant contribution to total laboratory errors. This review highlights preanalytical errors, their sources, and control measures to improve the quality of laboratory testing. Blood sample quality is a critical concern, with factors such as hemolysis, lipemia, and icterus leading to erroneous results. Sources of preanalytical errors encompass inappropriate test requests, patient preparation lapses, and errors during sample collection, handling, and transportation. Mitigating these errors includes harmonization efforts, education and training programs, automated methods for sample quality assessment, and quality monitoring. Collaboration between laboratory personnel and healthcare professionals is crucial for implementing and sustaining these measures to enhance the accuracy and reliability of diagnostic results, ultimately improving patient care.

Design, Development, and Evaluation of the Blood Collection Management Workstation

Purpose

To design and develop a blood collection management workstation with high usability to reduce the risk of preanalytical errors and improve patient safety.

Methods

A five-phase mobile application development lifecycle model (MADLC) and experience-based co-design (EBCD) were used for design and development. Subsequently, the blood collection management workstation was evaluated using the Chinese System Usability Scale (SUS) in a general ward setting from January to June 2021.

Results

It was used on 2593 in-patients who underwent phlebotomy with 12,378 tubes being labeled. The rate of errors and meantime for blood sampling were decreased compared with the same period in the previous year. A total of 14 nurses agreed to participate in the evaluation, and the overall raw SUS score was 69.26 ± 10.39, which indicated above average results.

Conclusion

The blood collection management workstation has shown the potential to decrease errors and improve working efficiency in a clinical setting. The study also identified some weaknesses, which will be amended in the future.