Errors in the Hematology Laboratory at St. Paul’s Hospital Millennium Medical College, Addis Ababa, Ethiopia
Tadesse et al. BMC Res Notes
Errors in the Hematology Laboratory at St. Paul's Hospital Millennium Medical College, Addis Ababa, Ethiopia
Hirut Tadesse 3
Kassu Desta 2
Samuel Kinde 2
Fatuma Hassen 2
Addisu Gize 0 1
0 Department of Microbiology, St. Paul's Hospital Millennium Medical College , P.O.Box 1271, Addis Ababa , Ethiopia
1 Department of Microbiology, St. Paul's Hospital Millennium Medical College , P.O.Box 1271, Addis Ababa , Ethiopia
2 Department of Medical Laboratory Sciences, School of Allied Health Sciences, College of Health Sciences, Addis Ababa University , Addis Ababa , Ethiopia
3 Department of Laboratory Science, St. Paul's Hospital Millennium Medical College , Addis Ababa , Ethiopia
Objective: The objective of this study was to determine the magnitude of pre-analytical, analytical and post-analytical laboratory errors in hematology tests. Results: A total of 2606 hematology requests were studied. Out of the total, 562 (21.6%) pre-analytic, 14 (0.5%) analytical and 168 (6.4%) post-analytical errors were recorded which contribute a total frequency of 75.5, 1.9 and 22.6%, respectively. The name of the physician requesting the test was not provided on 2215 (85%) of request forms and 1827 (70.1%) of the request forms were unaccompanied with proper clinical details of the patient. Essential information required on the request forms was often missed. Close communication between clinicians and laboratory personnel is the key to improve laboratory quality in general.
Laboratory errors; Hematological errors; Pre-analytical errors in hematology
An error in the hematology laboratory may begin when
the patient is ready to give specimen for testing, analysis
until results are released to the clinician and makes
diagnostic and therapeutic decisions according to their
interpretation. This whole process is impossible to perform
totally free of error. Any laboratory analysis always works
to minimize this uncertainty and estimate their size with
acceptable degree [
The pre-analytical phase of work flow includes a set
of processes that take place in different places at
different times. The pre-analytical phases include all processes
from the time a laboratory request is made by the
physician until the sample is ready for testing [
main processes that should be taken into account in the
study of the pre- analytical phase are; properly
identification of patients and following the right sample
collection, transport, store and test selection [
]. Out of
the three phases errors occurring in the laboratory, the
pre-analytical phase account the major figure (46–68%),
followed by post-analytical phase (19–47%) of errors .
A minority (13–32%) according to the studies, occurred
in the analytical portion [
]. The magnitude of the effect
of these errors on patient care is not negligible; it may
lead to incorrect diagnostic and therapeutic decisions,
misinterpretation of results, and impairment of
meaningful comments from the clinical laboratory [
information provided by clinical laboratories affects up to
60–70% of clinical decisions .
The analytical phase begins when the patient specimen
is prepared in the laboratory for testing and it ends when
the test result is interpreted and verified by the
technologist in the laboratory [
]. Errors in this phase may be
originated from the equipment itself or from interfering
compound of the analytic sample. Analytical errors are
classified into random errors and systematic errors. It is
clear that random errors indicate poor precision while
systematic errors indicate poor accuracy. A few examples
of random errors are pipetting error, transcription error,
wrong sample numbering and labeling, and
fluctuating readings on the colorimeter. Systematic errors could
occur due to wrong procedure, incorrect standards and
calibration procedures [
In post-analytical phase, results are reported to the
physicians for their interpretation and to treat the
patient. However, careless reporting of results and wrong
transcription at this phase leads to post-analytical phase
]. In the post-analytical step, the most
common mistakes are wrong validation; delayed results, not
reported or reported to the wrong providers, and
incorrect results reported because of post-analytical data entry
errors and transcription errors are common activities.
The post-analytical procedures performed within the
laboratory include verifying laboratory results, feeding
them into the laboratory information system, and
communicating them to the clinicians in a number of ways,
usually by producing a report and making any necessary
oral communications regarding ‘‘alert’’ or panic results
The United States agency for healthcare research and
quality estimates that medical errors are the 8th leading
cause of death in the United States, which is higher than
motor vehicle accidents cancer and AIDS events annually
]. Even though automation, standardization and
technological advances have significantly improved the
analytical reliability of laboratory tests [
12, 15, 18
laboratory errors still do occur in every process. Therefore,
the present study aims to fill this gap and generate
information on pre analytical, analytical and post analytical
errors as well as analyze their distribution across settings.
A cross sectional study was conducted from December
2014 to March 2015 at St. Paul’s Hospital Millennium
Medical College (SPHMMC), Addis Ababa, Ethiopia. The
hospital laboratory serves an average 300 patients daily
and many patients are referred from different parts of the
country for different services.
A structured check list was used to collect information
like patient card number, name of patient, ward/clinic
name, age of the patient, clinical detail, physician name
and signatures, the presence and absence of hemolysis,
clotting, and inadequate samples, etc.
The check list was pre-tested before the actual data
collection in the selected hospital to ensure the
validity of the study tool. Then, appropriate modifications
were made to standardize the tool. The principal
investigator was supervised the whole work during collection
Two data collectors were trained for 2 days about how
to use the check list. Storage condition, acceptable and
rejection sample criteria were some of the points
discussed with data collectors. In brief, they were oriented
that samples to be processed for hematology must be run
within 24 h, if kept at room temperature and 36 h, if kept
at 4 °C. No special preparation of the patient is necessary.
For erythrocyte sedimentation rate, specimens must be
run within 4 h. Samples were considered as acceptable
in hematology for this study; the samples must be
collected in correct sample container (LAVENDER TOP K2
EDTA anticoagulant tubes), correct specimen volume,
i.e., all EDTA tubes are optimized at 1.5 mg. EDTA/ml of
whole blood. The minimum amount suggested by BD, the
tube vendor is at least a 90% draw volume. For example,
the 6.0 ml EDTA tubes should have at least 5.4 of whole
blood and the 3.0 ml EDTA tubes should have at least
2.7 ml of whole blood.
However, reasons to reject samples were also noticed
like, clotted specimen, hemolyzed specimen, improperly
labeled or unlabeled specimen, leaking tubes and delay in
Data gathered in the study period were cleaned and
double entered into computer using Excel sheet. The
analysis was done using SPSS version19. Percentage and
frequency was calculated.
Ethical approval was obtained from the Department of
Medical Laboratory Science, College of Health Science,
Addis Ababa University Research and Ethical Review
Committee. Informed written permission was obtained
from St. Paul’s Hospital Millennium Medical College
Institutional Review Board (IRB) and submitted to the
head of the laboratory department.
A total of 2606 hematology request forms were collected
from outpatient department (OPD), private wings, and
emergency and in patient departments. Of the total tests
requested 386 (15%) were from emergency department
and 19 (0.73%) of the requested samples source were not
specified. From these requests 842 (32.3%) patients were
males and 1497 (57.5%) patients were females and sex
was not specified on 267 (10.3%) patients. Overall 742
(28.5%) hematology laboratory errors were detected, of
which 560 (75.5%) were pre-analytic, 14 (2%) analytical,
168 (22.6%) post-analytical errors. The highest frequency
of pre-analytical errors samples were from emergency
(23.6%), followed by in patient ward (23.4%),
outpatient (20.7%) and from private wing (17.2%). Out of all
the required information, the patient’s identity number
and the laboratory test being ordered were present in
2606 (100%) of request forms. The patient’s age was not
supplied in 298 (11.5%) test request forms, as listed in
Pre‑analytical, analytical and post‑analytical errors
We observed all hematology tests such as complete blood
count (CBC), erythrocyte sedimentation rate (ESR) and
coagulation tests like activated partial thrombo plastine
time (APTT), prothrombin time (PT) and partial
thrombin time (PTT). Of the total hematology specimen
ordered during the study period, 1509 (58%) were from
OPD, 529 (20.3%) from in patient department, 386 (15%)
from emergency department, 163 (6.3%) from the private
wing, and 19 (0.73%) did not specify the location.
Overall, 742 (28.5%) laboratory errors were detected. Of this
error of figures, pre-analytic had made contributions of
560 (75.5%), analytical 14 (2%), and post-analytical 168
(22.6%). The highest frequency of pre-analytical
problems requests were from emergency (23.6%) whereas the
frequencies the private wing (17.2%). The most frequently
occurring pre-analytical problems were inadequate
sample collection, with a frequency of 274 (48.9%) followed
by hemolysis 193 (34.5%) as it is shown in Table 2.
In the analytical phase, the most frequently detected
analytical problem was due to wrong temperature
storage of the reagent (42.8%) followed by equipment failure
of electric interruption. From post-analytical errors, 126
(75%) were communication errors as shown in Table 3.
Our study showed that among a total of 2606 hematology
samples the total errors were 742 of which 75.5% were
pre-analytical, 2% were analytical, and 22% were
postanalytical errors. Pre-analytical errors were more
common, perhaps caused by rotational duties and workload
]. This study was supported by a similar
study conducted in Padua Laboratory, which described
pre-analytical errors of 68.2%, analytical of 13.3%, and
post of 18.5%, however, the difference of results in
analytical errors, may be due to a shortage of internal
quality control (QC) systems in our study [
10, 21, 22
because of systemic errors due to inherent technical
problems, since accuracy and precision tests were also
As compared to the study done in Italy [
], clotting in
our study is very low, 13 (2.3%). This may be because of
the use of ready-made test tubes coated with
anticoagulant. The higher result of hemolysis and insufficient
volume of blood in the current study may be due to samples
collected by non-laboratory professionals who did not
recognize collecting samples by correct techniques.
The proportions of pre-analytical errors were the
highest in the emergency services (23.5%), followed by
inpatient and outpatient service, with 23.2 and 20.6%
respectively. The result was higher than other study [
3.32% (n = 92), and 1.55% (n = 43), respectively, and may
be a result of our professionals being too busy to collect
the specimens properly.
The evaluation of hematology request forms showed
a well-documented patient name and this result is
supported the study done in Nigeria. These forms rated
low in clinical diagnosis, recorded just as compared to
the study done in Nigeria [
]. The present study also
showed that age and gender were left off of the forms at
rate of 14.4 and 10.3%, respectively. The finding is low as
compared to the study done in Ghana, which 25.6% of
patient age and 67.3% of gender were missed .
Clinical detail was provided on only 29.8% of the
request forms, which varied greatly from the results
of the study conducted in Ghana, showing 77.3%. This
result may indicate that our clinicians do not have a habit
of writing clinical details.
The present study showed that the name of the
physician requesting the tests was provided on 391 (15%)
forms, and 1764 (67.7%) forms were signed. In a similar
study, 55.4% of the forms provided the name of physician
and 75.7% were signed. However, higher result of
written date of requisition was observed in the current study
2440 (93.6%) relative to the previous, 62.7% [
]. This low
result of physician identification in our case may be due
to requests ordered by staffs other than a physician. We
therefore demonstrated that laboratory requisition forms
were not adequately completed by clinicians. Based on
our findings post-analytical errors were 22.5%. From all
post-analytical errors, communication errors were the
highest at 126 (75%). This indicated that the laboratory
did not have a strongly linked system with clinicians in
the present study.
Since the pre- and post-analytical errors contribution
are very high, this suggests better co-operation with
clinicians is needed. In addition, provision of training on
sample collection and transportation to clinicians and
technicians/technologists is advisable.
Limitation of the study
Our study has some limitation like lack of similar studies
in Ethiopia which made difficult for getting more
information on the sample size calculation specially and also
possible comparison nationwide. In the case of some
variables; like hemolysis and icterus samples, measurements
were made by visual observation which may lead to
AIDS: Acquired Immuno Deficiency Syndrome; AOR: adjusted odd ratio;
APTT: activated partial thrombo plastine time; CBC: complete blood count; CI:
confidence interval; COR: crude odd ratio; ESR: erythrocyte sedimentation rate;
OPD: out patient department; PT: prothrombin time; PTT: partial thrombin
time; SPHMMC: St. Paul’s Hospital Millennium Medical College; SPSS: Statistical
Package for Social Science.
AG, HT and SK conceived the study, participated in the design, data
acquisition, and laboratory work and drafted the paper. AG, FH and KD critically
reviewed the paper. FH and KD made substantial contributions to conception
and design. All authors read and approved the final manuscript.
The authors would like to thank staff members of St. Paul’s Hospital
Millennium Medical College administration and laboratory staff facilitating the
overall the research work. This study was financially supported by Addis Ababa
University. We would also like to extend our profound gratitude to the study
subjects without their consent and the provision of the demanded
information this research work would not have been real. Last but not least we would
like to acknowledge Amy Vercler, admin assistant of the SPHMMC for her
language edition of the manuscripts.
The authors declare that they have no competing interests.
Availability of data and materials
The data that support the findings of this study will be available from the
corresponding author upon reasonable request in the form of Statistical Package
for Social Sciences (SPSS).
Consent for publication
Ethics approval and consent to participate
Ethical approval was obtained from the Department of Medical Laboratory
Science, College of Health Science, Addis Ababa University Research and
Ethical Review Committee. Informed written permission was obtained from St.
Paul’s Millennium Medical College Institutional Review Board (IRB) and
submitted to the head of the laboratory department. Any data generated from the
specimens protected the patent privacy, confidentiality and anonymity.
This research work was financed by Addis Ababa University, Addis Ababa,
Ethiopia. The funder had no role in study design, data collection and analysis,
decision to publish, or preparation of the manuscript.
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
1. Hammerling JA . A review of medical errors in laboratory diagnostics and where we are today . Lab Med . 2012 ; 43 ( 2 ): 41 - 4 .
2. Stark A , Jones BA , Chapman D , Well K , Krajenta R , Meier FA , et al. Clinical laboratory specimen rejection-association with the site of patient care and patients' characteristics: findings from a single health care organization . Arch Pathol Lab Med . 2007 ; 131 ( 4 ): 588 - 92 .
3. Chhillar N , Khurana S , Agarwal R , Singh NK . Effect of pre-analytical errors on quality of laboratory medicine at a neuropsychiatry institute in North India . Indian J Clin Biochem . 2010 ; 26 ( 1 ): 46 - 9 .
4. Plebani M. Exploring the iceberg of errors in laboratory medicine . Clin Chim Acta . 2009 ; 404 ( 1 ): 16 - 23 .
5. Carraro P , Plebani M. Errors in a stat laboratory: types and frequencies 10 years later . Clin Chem . 2007 ; 53 ( 7 ): 1338 - 42 .
6. Oladeinde BH , Omoregie R , Osakue EO , Onifade AA . Evaluation of laboratory request forms for incomplete data at a rural tertiary hospital in Nigeria . N Z J Med Lab Sci . 2012 ; 66 ( 2 ): 39 .
7. Plebani M. Errors in clinical laboratories or errors in laboratory medicine? Clin Chem Lab Med . 2006 ; 44 ( 6 ): 750 - 9 .
8. Bonini P , Plebani M , Ceriotti F , Rubboli F. Errors in laboratory medicine. Clin Chem . 2002 ; 48 ( 5 ): 691 - 8 .
9. Gyawali P , Shrestha RK , Bhattarai P , Raut BK , Aryal M , Malla SS . In the completion of laboratory requisition forms . https://www.researchgate. net. Accessed 16 Mar 2016 .
10. Alagoa PJ , Udoye EP . Laboratory request forms-how well do Doctors fill them? A look at the practice at the Niger Delta University Teaching Hospital, Okolobiri, Bayelsa State, Nigeria. Niger Health J. 2015 ; 15 ( 1 ): 14 .
11. Rattan A , Lippi G . Frequency and type of pre-analytical errors in a laboratory medicine department in India . Clin Chem Lab Med . 2008 ; 46 ( 11 ): 1657 - 9 .
12. Hawkins R. Managing the pre- and post-analytical phases of the total testing process . Ann Lab Med . 2012 ; 32 ( 1 ): 5 - 16 .
13. Saibaba KSS , Rao PVLNS , Ramana GV , Kumar EGTV , Tripathi RL . Analytical bias due to calibrator matrix effects . Indian J Clin Biochem . 1995 ; 10 ( 2 ): 112 - 5 .
14. Trivedi P , Shah N , Ramani KV . Managing clinical laboratories: monitor and control lab errors to improve lab performance . Indian Institute of Management; 2011. Accessed 15 Mar 2016 .
15. Fryer AA , Smellie WSA . Managing demand for laboratory tests: a laboratory toolkit . J Clin Pathol . 2012 . https://doi.org/10.1136/jclinpath-2011- 200524.
16. Valenstein PN , Raab SS , Walsh MK . Identification errors involving clinical laboratories: a college of American Pathologists Q-Probes study of patient and specimen identification errors at 120 institutions . Arch Pathol Lab Med . 2006 ; 130 ( 8 ): 1106 - 13 .
17. Nichols JH . Reducing medical errors at the point of care . Lab Med . 2005 ; 36 ( 5 ): 275 - 7 .
18. Makubi AN , Meda C , Magesa A , Minja P , Mlalasi J , Salum Z , et al. Audit of clinical-laboratory practices in haematology and blood transfusion at Muhimbili National Hospital in Tanzania . Tanzan J Health Res . 2012 ; 14 ( 4 ): 257 - 62 .
19. Abdollahi A , Saffar H , Saffar H . Types and frequency of errors during different phases of testing at a clinical medical laboratory of a teaching hospital in Tehran, Iran . North Am J Med Sci . 2014 ; 6 ( 5 ): 224 .
20. Addis Z , Wondimagegn T , Tachebele B. Types and frequency of preanalytical errors at University of Gondar hospital laboratory. Elect Med J. 2015 ; 2 ( 4 ): 363 - 5 .
21. Plebani M , Carraro P. Mistakes in a stat laboratory: types and frequency . Clin Chem . 1997 ; 43 ( 8 ): 1348 - 51 .
22. Söderberg J , Brulin C , Grankvist K , Wallin O . Preanalytical errors in primary healthcare: a questionnaire study of information search procedures, test request management and test tube labelling . Clin Chem Lab Med . 2009 ; 47 ( 2 ): 195 - 201 .
23. Salvagno GL , Lippi G , Bassi A , Poli G , Guidi GC . Prevalence and type of pre-analytical problems for inpatients samples in coagulation laboratory . J Eval Clin Pract . 2008 ; 14 ( 2 ): 351 - 3 .
24. Osegbe I , Afolabi O , Onyenekwu C , Dada A , Azinge E. Clinician education as a strategy for the proper completion of laboratory request forms in a Nigerian tertiary hospital . http://aslm. org/aslm2012. Accessed 15 Mar 2016 .
25. Olayemi E , Asiamah-Broni R . Evaluation of request forms submitted to the haematology laboratory in a Ghanaian tertiary hospital . Pan Afr Med J. 2011 ; 8 ( 1 ): 33 .