RESULTS

The laboratory received 1, 68,354 blood samples and preanalytical mistakes recorded were 5,120 (only 3% of total) samples, during 2016-17 (Table 1, Figure 1).

 

Table 1: Preanalytical errors according to the type of blood investigations and during the study period

Sr. No	Type Of Blood Investigation	Samples Received	Preanalytics	Most Observed Error
1	Blood Investigations	154643	4645 (3%)	Insufficient Volume, Hemolysis
2	Hb Electrophoresis	1331	105 (7.8%)	clot due to improper mixing with anticoagulant (EDTA) and post transfused sample
3	ABG	1435	20 (1.39%)	transportation without ice
4	PT,APTT	10945	350 (3.19%)	short draw leading to improper mixing with anticoagulant
	Total	168354	5120 (3.04%)

Out of the total number of error samples, 3123 (61%) were from pediatric ICUs, 563 (11%) from other inpatient wards and 1434 (28%) from outpatient services (Figure 2).

Figure 2: Sample collection area wise preanalytics (5120 samples)

 

The preanalytical errors were categorized as A) Requisition (Test order); B)Sample vacutainers tubes; C)Transport; D)Storage, E) Centrifugation and F)Timing. Category wise potential problems were shown with their frequency as percentages in Table 2 and Figure 3. The individual quality indicators are shown in detail in Table 3.

 

Table 2: Preanalytical errors in general at our Lab

	CATEGORY	Detected errors	%
A	requisition (Test Order)	Inadequate details, wrong entries, mismatching of request with that of vacutainers, Duplication of regn. numbers, Handwriting not legible, Missed requisition	15
B	sample vacutainers	QNS, identification label, visible hemolysis,, clotted sample,, wrong color code of vacutainers, Inappropriate specimen	30
C	Transportation	transport temperature, light exposure, delayed transport time	31
D	storage	damaged tubes or unsuitable tubes or blood sample	1
E	centrifugation	QNS, Hemolysis, lipemic, icteric, fibrin clots	20
F	Timing	drawing sample at inappropriate time	3

 

 

Figure 3: Category wise preanalytical errors in %                                               Figure 4: Sample rejection shown in %

Out of 5120 specimens with preanalytical errors, 409, (8%) specimens were unsuitable for further processing hence rejected (SR) due to wrong tubes (45%), clots (39%), clerical mistakes (12%) and broken tubes (4%).

 

Table 4: Sample rejection in number

 

Table 3: Quality Indicators of the preanalytical phase and the outcomes with their frequency in% (*TAT: Turnaround time; SR: Sample rejection)

DISCUSSION

The International Organization for Standardization (ISO) 15189:2012 standard for laboratory accreditation defines the preanalytical phase as “processes that start, in chronological order, from the clinician’s request and include the examination request, preparation and identification of the patient, collection of the primary sample(s), and transportation to and within the laboratory, and end when the analytical examination begins”¹¹. For the prevention of preanalytical errors, the most reliable approach is to construct preanalytical standardization¹². In our setup, bar-coding of the sample is not available hence; a request form generally accompanies the specimens. Re check is done for transcription errors by comparing results on the report forms with those on the results log book. Specimens that require further analysis because of dilution or assay problems are mentioned as “alerts” on the master log, as per the standard lab practices¹⁰. Each type of test has its own kind of preanalytical problem particular to that investigation. Some preanalytical errors are predominant in serum chemistry tests whereas those may not be important in others. For instance, hemolysis is a problematic error in serum potassium estimation but not for ABG, as the sample itself is a whole blood. An incomplete requisition can be corrected but a mismatched tube is rejected for ‘run’. Blood transfusion is a rejecting preanalytical error for Hb variants analysis but not for other serum investigations. In our laboratory, preanalytical errors were 3% for the blood tests which use serum as the sample. Insufficient volume (QNS) and the hemolysis were most common occurrences as the preanalytical errors (see Table 1, Fig 1). The manual agar gel Hb electrophoresis technique at our lab required at least 5ml of whole blood in an EDTA bottle, we often received improperly mixed sample giving rise to a clot sample. And QNS received, which were not suitable to prepare hemosylate and for fetal Hb testing. As these samples were drawn just before blood transfusions, it was not possible to re-draw the sample, hence sample rejected. Sometimes patient attendant reveals at the lab reception that patient was blood transfused a few days earlier before they took admission and thus the blood sample brought for Hb electrophoresis stands unsuitable. This particular preanalytical error also sometimes revealed retrospectively, i.e., post analytically, when the treating doctor consults the lab to discuss the results (for example, a possible false negative report; patient being positive for Sickling test but a negative for sickle Hb band in electrophoresis., as patient attenders conceal the fact of recent blood transfusion, for the fear of refusal of admission). For these reasons, preanalytical factors misguide the total testing process; hence out of 1331 specimens, 105 (7.8%) preanalytical errors occurred for this test. ABG analysis had 1.39% (20 of 1435) of storage and transport errors. The arterial blood samples were often brought without icepack and rarely, those were sent to the lab without being kept stored in a refrigerator. The noted preanalytical mistake for PT, aPTT samples were mostly a “short draw”, (3.19%) i.e., the blood was short of the mark given on the vacutainer tube (see Fig 5). This error results in improper ratio of blood to anticoagulant Tri Sodium Citrate and thus gives an erroneous result. We also received samples as clots because of improper mixing of blood. The guidelines from Lippi et al states that tubes should not be accepted for analysis if < 80 % full because the results of PT, APTT, thrombin time were significantly longer when tubes were under-filled, frequently to the extent that patient management decisions could be affected¹³. Samples which arrived from ICUs were having 61% preanalytical errors, followed by samples from OPD, 28% (Fig 2). We could replace the samples which had preanalytical errors, except from OPD, with the adequate and suitable samples from the respective wards. The preanalytical mistakes were rectified in most of the cases by communication to respective collection areas except for a few number of blood investigations. Pediatric /Neonatal ICUs were the problem area for our pre analytics as here, sample collection is a difficult task for the phlebotomists, with inevitable insuffient volume (i.e., QNS), in spite of their sincere effort to draw sufficient volume. OPD patients were non traceable due to lack of communication in many of cases. All the preanalytical errors were categorized in to 6 types (see Table 2, Fig 3) and transportation error category is a predominant observation (31%) as the samples were carried ‘by hand’ from respective wards and especially OPD, open to the environment which could subject the sample tubes to temperature changes and from one building to another leads to exposure to the sunlight and the distance by walk has resulted in delayed transport and delivery of the samples to laboratory reception. This could have resulted in erroneous bilirubin values. Vacutainer tubes category has 30% of preanalytical errors with QNS (25%), mislabeling on tubes and clot samples. Often, in precious samples, we had to dilute the available serum and ‘run’ the tests. Centrifugation of blood samples surfaced the preanalytical errors to 20% with hemolysis, fibrin clots and lipemic. Lipemia interferes with optical reading by the instrument and can affect interpretation of electrolyte values. Test order request slips category amounted to 15% of preanalytical mistakes which were mostly “clerical”. In house deliveries of twins, also given rise to preanalytical mistake; of single test requisition with single ID but accompanied twin samples. Timing of sample drawing is also a contributory factor, as patients force phlebotomists to take their sample before scheduled time of post prandial or before 2h time of OGTT. This inappropriately increases the incidence of lipemic samples in OPD patients, may be due to lack of information regarding prior preparation to the patients by the clinicians as well as ignoring of preparation rules by the pa­tients. Hence, many patients give samples in non-fasting states leading to erroneous reporting¹⁴. Sample storage category contributed the least (1%) of preanalytical mistakes because those specimens reaching the lab are very few. These data are comparable to those provided by other investigators, which confirm that problems directly related to specimen collection are the main cause of Preanalytic er­rors, especially hemolysed, clotted, insufficient, and incorrect samples^14,15,16.

 

 

 

 

 

Table 5: Corrective actions suggested improving various categories of preanalytical errors

Figure 5: A few examples are shown for preanalytical errors

 

Our lab specimen rejection rate was 8% see (Table 4 and Fig 4), comparable to a study done by Dikmen ZG et al [6]. But, QNS was our major concern (25%) leading to difficult decisions for ‘SR’ or to run test with dilution as 61% of total samples received were ‘precious’ from neonatal / premature born ICUs. Though clerical mistakes (12%) were corrected to a few extents, broken (4%) and wrong tubes (45%) were rejected. Fibrin clots (39%) were a second major factor for our rejection, pre or post centrifugation. Category wise quality indicators of preanalytical phase of total testing process and their individual outcomes are mentioned in detail in Table 3 and a few examples with images are shown in Figure 5.

 The Phlebotomy techniques used to acquire a specimen also affect many laboratory tests, hence this been considered a separate area of improvement for medical techni­cians in developed countries^17,18. For example, prolonged tourniquet application causes local anoxia causes potassium leak from cells, and the back venous pressure concentrates cells, proteins, and substances bound to proteins (such as calcium). Monitoring by a QC specialist will minimize errors as detected by limit checks, delta checks, etc¹⁹. Creating awareness for accurate and timely submission of laboratory test request forms, training in the correct method of sample drawing (using evacuated tube system) and the distribution of protocols for proper specimen collection and handling, as well as periodical auditing of preanalytical mistakes is helpful and this can be used in a targeted manner for information and training purposes, providing the direct link between the blood collection practice and the resulting sample quality issues^6,15. Lippi G, McBride KB et al, states that ‘preanalytical errors often cause random errors undetectable by normal quality control methods. In order to determine the cause of these random errors, it is necessary for the laboratory professional to become a sort of “detective”. Through a series of deductions and research, (s) he can identify the cause and put corrective actions in place’¹³. A few corrective actions are suggested for the preanalytics as well as to reduce SR to a minimum level is shown in a tabular form in the Table ^{56, 10,20}.

 

CONCLUSIONS

Every laboratory must identify and document the steps in total testing process; especially preanalytical errors part which is mostly not under the purview of the lab. Thus devising corrective strategies for their prevention can significantly reduce the laboratory errors and minimize sample rejection. At the same time quality reporting of a laboratory is assured and laboratory can confidently contribute to the safety management of the patients.

 

REFERENCES

1. Nutting PA, Main DS, Fischer PM et al. Toward optimal laboratory use. Problems in laboratory testing in primary care. JAMA. 1996 Feb 28; 275(8):635-9.
2. LippiG, GuidiGC, Mattiuzzi C, Plebani M. Preanalytical variability: The dark side of the moon in laboratory testing. Clin Chem Lab Med 2006; 44:358–65.
3. Lippi G, Salvagno GL, Montagnana M, Franchini M, Guidi GC.Phlebotomy issues and quality improvement in results of laboratory testing. Clin Lab 2006; 52:217–30.
4. Plebani M, Carraro P. Mistakes in a stat laboratory: types and frequency. Clin Chem 1997; 43:1348–51
5. Lippi G, Banfi G, Church S, Cornes M, De Carli G, Grankvist K, et al. Preanalytical quality improvement. In pursuit of harmony, on behalf of European Federation for Clinical Chemistry and Laboratory Medicine (EFLM) Working group for Preanalytical Phase (WG-PRE). Clin Chem Lab Med 2015; 53:357–70.
6. Dikmen ZG, Pinar A, Akbiyik F. Specimen rejection in laboratory medicine: necessary for patient safety? Biochem Med 2015; 25:377–85.
7. Lippi G, Bowen R, Adcock DM. Re-engineering laboratory diagnostics for preventing preanalytical errors. Clin Biochem 2016; 49:1313–4.}
8. Plebani M. Errors in clinical laboratories or errors in laboratory medicine? Clin Chem Lab Med 2006; 44:750–9.
9. Plebani M. Errors in laboratory medicine and patient safety: the road ahead. Clin Chem Lab Med 2007; 45:700–7.
10. George G. Klee and James O. Westgard (2012); Quality management: Control of Preanalytical Variables. In: Carl A. Burtis, Edward R. Ashwood, David E. Bruns.Tietz textbook of clinical chemistry and molecular.(5th ed) .Elsevier: P 172-75.
11. International Organization for Standardization. ISO 15189:2012: medical laboratories: particular requirements for quality and competence. Geneva, Switzerland: International Organization for Standardization; 2012.
12. Lippi G, Guidi GC. Preanalytic indicators of laboratory performances and quality improvement of laboratory testing. Clin Lab 2006; 52: 457–62.
13. Lippi G, McBride KB, et al. Preanalytical quality improvement: in quality we trust. Clin Chem Lab Med 2013; 51(1): 229–241
14. Ranjna Chawla, Binita Goswami, et al; Identification of the Types of Preanalytical Errors in the Clinical Chemistry Laboratory: 1-Year Study at G.B. Pant Hospital, Laboratory Medicine, Volume 41, Issue 2, 1 February 2010, Pages 89–92
15. Romero A, Munoz M, Ramos JR, et al. Identification of preanalytical mistakes in the stat section of the clinical laboratory.Clin Chem Lab Med. 2005; 43: 974–975.
16. Jones BA, Calam RR, Howanitz PJ.Chemistry specimen acceptability: A College of American Pathologists Q-Probes study of 453 laboratories. Arch Pathol Lab Med. 1997; 121:19–26.
17. Lippi G Blanckaert N Bonini P et al.Causes, consequences, detection and prevention of identification errors in laboratory diagnostic .Clin Chem Lab Me. 2009; 47:143–153.
18. Fidler JR.Task analysis revisited: Refining the phlebotomy technician scope of practice and assessing longitudinal change in competencies .Eval Health Prof.2007; 30:150–169
19. George GK, James OW. Quality management, Ch.8. In: Burtis CA, Ashwood ER, Bruns DE, editors. Tietz Textbook of Clinical Chemistry and Molecular Diagnostics. 5 th Edition. St. Louis (MO): Elsevier Saunders; 2013. p 174.
20. CLSI.Collection, transport, and processing of blood specimens for testing plasma-based coagulation assays and molecular hemostasis assays: approved guideline, 5th edn. CLSI Document H21-A5.Wayne, Pa: Clinical and Laboratory Standards Institute, 2008.