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The prevalence of pre-analytical errors in the laboratory of the Cantonal Hospital Zenica in Bosnia and Herzegovina

2018; Medical Association of Zenica-Doboj Canton; Volume: 16; Issue: 1 Linguagem: Inglês

10.17392/979-19

1840-2445

Damira Kadić, Aida Avdagić Ismić, Sabaheta Hasić,

Meta-analysis and systematic reviews

<p><strong>Aim</strong> <br />To identify rates of most common pre-analytical errors and to document possible (different) error rates between inpatients and outpatients.<br /><strong>Methods <br /></strong>This retrospective study was conducted at the Department of Medical Biochemistry and Immunology Diagnostics,<br />Cantonal Hospital Zenica, from December 2016 until March 2017. Data on rejected blood samples in the laboratory information system were analysed.<br /><strong>Results<br /></strong> During the 3-month period 35,343 patient blood samples (25,545 inpatients and 9,798 outpatients) were received in<br />the laboratory. The study identified 602 (1.70%) rejected samples because of pre-analytical errors, mostly due to haemolysis, 292 (48.50%), and clotted samples, 240 (39.87%). The remaining 70 (11.63%) samples were rejected because of inappropriate sample volume, inappropriate container and identification errors (7.81%, 2.16% and 1.66%, respectively). The proportion of inpatient rejected samples was 8.7-fold higher than in the outpatient samples.<br />The proportion of inpatient rejected samples because of haemolysis, clotted samples, inappropriate sample volume and inappropriate containers were higher than in the outpatient samples (20.5-, 12.1-, 2.3- and 1.3-fold higher, respectively); proportion of rejected samples because of identification errors was 8.0-fold higher in the outpatient (collection sites outside the hospital) than in the inpatient samples.<br /><strong>Conclusion<br /></strong> Higher pre-analytical sample error rates were connected with inpatient samples, while higher identification error rates<br />were connected with outpatient samples. Establishment of periodic stuff training and introduction of information technology could reduce pre-analytical errors.</p>