Error tracking in a clinical biochemistry laboratory

Clin Chem Lab Med. 2009;47(10):1253-7. doi: 10.1515/CCLM.2009.272.


Background: We report our results for the systematic recording of all errors in a standard clinical laboratory over a 1-year period.

Methods: Recording was performed using a commercial database program. All individuals in the laboratory were allowed to report errors. The testing processes were classified according to function, and errors were classified as pre-analytical, analytical, post-analytical, or service-related, and then further divided into descriptive subgroups. Samples were taken from hospital wards (38.6%), outpatient clinics (25.7%), general practitioners (29.4%), and other hospitals.

Results: A total of 1189 errors were reported in 1151 reports during the first year, corresponding to an error rate of 1 error for every 142 patients, or 1 per 1223 tests. The majority of events were due to human errors (82.6%), and only a few (4.3%) were the result of technical errors. Most of the errors (81%) were pre-analytical. Of the remainder, 10% were analytical, 8% were post-analytical, and 1% was service-related. Nearly half of the errors (n=550) occurred with samples received from general practitioners or clinical hospital wards. Identification errors were relatively common when non-technicians collected blood samples.

Conclusions: Each clinical laboratory should record errors in a structured manner. A relation database is a useful tool for the recording and extraction of data, as the database can be structured to reflect the workflow at each individual laboratory.

MeSH terms

  • Biochemistry / methods*
  • Biochemistry / standards
  • Chemistry, Clinical / methods*
  • Chemistry, Clinical / standards
  • Databases, Factual
  • Humans
  • Laboratories* / standards
  • Research Design*
  • Software