Abstract:
Background: Clinical laboratory test results have become an essential part in medical decision
making and patient management. Currently, more than 60-70% of the most important decisions:
an admission, medication and discharge are based on laboratory test results. However, potential
errors throughout the total testing process affect the quality of laboratory test results which in
turn can affect quality of medical decisions. According to ISO 15189, 2012, the laboratory shall
establish and periodically review quality indicators to monitor and evaluate laboratory total
testing process.
Objective: To evaluate laboratory total testing process and performances using quality
indicators in clinical chemistry and hematology laboratories at Pawi general hospital,
Benshangul Gumuz, Ethiopia, from October 01/2021 to December30/2021
Methodology: A prospective cross sectional study was conducted at Pawi general hospital for a
period of two months. All venous blood samples and corresponding requests coming to clinical
Chemistry and Hematology laboratories were included in the study. Data were collected based
on International Federation of Clinical Chemistry (IFCC) approved quality indicators and ISO
15189 standards. Data were entered to EPI data version 3 and, transferred and analyzed using
SPSS version 21.Then the result was summarized by descriptive statistics using frequency tables
and cross tabulations and also chi square tests used for statistical significance between error
frequency. Multivariate and bivariate logistic regression was also used to assess the association
between patient result released with expected TAT with location of sample collection and
sections of sample processed.
Result: A total 4,140 samples and corresponding test requests were investigated or included.
From these, 14.7% (609) were clinical chemistry and 85.3% (3531) were hematology tests.
During the study period 136,722 quality indicators were reviewed in the total testing process,
out of which 24.7%(33,792) of errors were accounted. Among the total number of errors pre-
analytical, analytical and post-analytical accounted for 63.6% (21,504), 1.6% (526), and 34.8%
(11,762) respectively. Incomplete data on the test request form was observed to be the major
attributing determinant for pre-analytical errors followed by specimen rejection. Reagent stock-
out and equipment downtime greatly affected the proficiency of analytical phase. The major
post-analytical errors were ascribed by excessive turn-around-time. The chi square test analyzed
that there was a statistically significance difference between error frequency of the three phases
((χ2=4986, p <0.0001). Multivariate logistic regression also showed that result released with
expected TAT was independently associated with departments of clinical chemistry (AOR=5.842,
95% CI (4.787–7.130), p< 0.0001)
Conclusion: The study finding showed that high error rates were observed in pre- and post-
analytical phases. This implies that there should be strict supervision in pre and post analytical
phases to provide quality laboratory services at the study setting
