Abstract
Background: The key incident monitoring and management systems (KIMMS) quality assurance program monitors incidents in the pre- and postanalytical phases of testing in medical laboratories. Haemolysed specimens have been found to be the most frequent preanalytical error and have major implications for patient care. The aims of this study were to assess the suitability of KIMMS for quality reporting of haemolysis and to devise a meaningful method for reporting and monitoring haemolysis.
Methods: A structured survey of 68 Australian KIMMS laboratory participant organisations was undertaken. Quarterly haemolysis reports (2011–2014) were analysed.
Results: Among 110 million accessions reported, haemolysis rates varied according to the reporting methods that participants used for assigning accessions (16% of participants reported haemolysis by specimen and 83% reported by episode) and counting haemolysis rejections (61% by specimen, 35% by episode and 3% by test). More than half of the participants (56%) assigned accessions by episode and counted rejections by specimen. For this group, the average haemolysis rate per 100,000 episodes was 177 rejected specimens with the average rate varying from 100 to 233 over time. The majority of participants (91%) determined rejections using the haemolysis index. Two thirds of participants (66%) recorded the haemolysis manually in laboratory information systems.
Conclusions: KIMMS maintains the largest longitudinal haemolysis database in the world. However, as a means of advancing improvements in the quality of the preanalytical laboratory process, there is a need to standardise reporting methods to enable robust comparison of haemolysis rejection rates across participant laboratories.
Methods: A structured survey of 68 Australian KIMMS laboratory participant organisations was undertaken. Quarterly haemolysis reports (2011–2014) were analysed.
Results: Among 110 million accessions reported, haemolysis rates varied according to the reporting methods that participants used for assigning accessions (16% of participants reported haemolysis by specimen and 83% reported by episode) and counting haemolysis rejections (61% by specimen, 35% by episode and 3% by test). More than half of the participants (56%) assigned accessions by episode and counted rejections by specimen. For this group, the average haemolysis rate per 100,000 episodes was 177 rejected specimens with the average rate varying from 100 to 233 over time. The majority of participants (91%) determined rejections using the haemolysis index. Two thirds of participants (66%) recorded the haemolysis manually in laboratory information systems.
Conclusions: KIMMS maintains the largest longitudinal haemolysis database in the world. However, as a means of advancing improvements in the quality of the preanalytical laboratory process, there is a need to standardise reporting methods to enable robust comparison of haemolysis rejection rates across participant laboratories.
| Original language | English |
|---|---|
| Pages (from-to) | 565-573 |
| Number of pages | 9 |
| Journal | Clinical Chemistry and Laboratory Medicine |
| Volume | 56 |
| Issue number | 4 |
| Early online date | 15 Sept 2017 |
| DOIs | |
| Publication status | Published - Apr 2018 |
Bibliographical note
Copyright the Author(s) 2017. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.Keywords
- haemolysis
- laboratory medicine
- laboratory monitoring and management systems
- patient safety
- preanalytical errors
- quality control
- specimen rejection