evaluation of errors in clinical hematology practice

How to cite this article: Pavani B, Sri Manvitha V. Evaluation of errors in clinical hematology practice. MedPulse International Journal

of Pathology. October 2017; 4(1): 07-12. https://www.medpulse.in/Pathology/

Original Research Article

Evaluation of errors in clinical hematology practice

Pavani B1, Sri Manvitha V

2*

1Associate Professor, Department of Pathology, Kamineni Academy of Medical Sciences (KAMSRC), L.B. Nagar, Hyderabad, Telangalna

2MBBS 3

rd year, Department of Pathology, Mediciti Institute of Medical sciences (MIMS), Medchal, Telangana.

Email: [email protected]

Abstract Background: Medical laboratory errors are one of the major factors that affect the diagnosis and future clinical course of

management. These errors have a tremendous impact on patient safety and can translate into the risk of adverse events for

patients. Errors still prevail despite automated innovations in the field of laboratory science. Aim: We conducted this

study to evaluate and identify pre-analytical, analytical, and post-analytical laboratory errors with regard to our practice

in clinical hematology and their effect on patient health care. Materials and Methods: A total of 47, 800 samples were

received in to the laboratory from both in patients and out patients between January 2015 to December 2017. Out of

which 22,800 were received from In patients while 25,000 were received from out patients. Results: A total of 1200

errors were detected from the total of 47,800 samples with the error rate of 2.5%.Of all the total errors, pre-analytical

errors were most common, with a frequency of 82%, followed by post-analytical at9.1% and analytical at16.6%.The total

number of errors recorded on inpatient sampleswere1081 out of the 22,800 tests, with an error rate of 4.7%, while the

total number of errors on outpatient samples were 119 out of the 25,000 tests (an error rate of 0.4%). Conclusions: There

is every need for the lab to establish a reliable policy on error recording, possibly through informatics aids and settle

universally agreed “laboratory sentinel events” throughout the total testing process, which would allow gaining important

information about serious incidents and thereby holding both providers and stakeholders accountable for patient safety.

Key Words: Laboratory Errors, Quality control, Quality management system.

*Address for Correspondence:

Dr. Sri ManvithaVallam, H/no 16-11-310/6/2, Saleemnagar colony, Malakpet Extension, Hyderabad, Andhra Pradesh, INDIA.

Email: [email protected]

Received Date: 22/07/2017 Revised Date: 18/08/2017 Accepted Date: 10/09/2017

DOI: https://doi.org/10.26611/105412

INTRODUCTION Medical laboratories play a significant role in the

healthcare system and clinical decision-making.

According to official data, 60–70% of clinical decisions

about hospitalization, discharge, and prescription are

based on laboratory results. According to the

International Organization for Standardization (ISO),

laboratory error sac knowledge as “any defect from

ordering test store porting result switch appropriate

interpretation. A detailed understanding of the steps involved in the total testing process is required to identify

the hierarchy of risks and challenges to be addressed.

Various studies have reported the frequency of errors

ranging from 46% to 68.2% during there-analytical phase.

Complexity of lab testing and increasing automation,

frequently poses problems for clinical laboratories,

clinicians and patients due to lack of constant monitoring

on the overall system non conformities. Despite the low

incidence of errors, among the large number of total

laboratory tests performed all over the labs, there are

important implications for patient safety8,9.Quantification

of adverse events related to laboratory errors is a

challenging and still-little known subject, due to: (i) study

design heterogeneity; (ii) under-reporting in incident

notification systems (many times out of fear); (iii)

difficulty in associating diagnostic errors with adverse

events. According to the requirements of standard

15189:2012 of the International Organization for

Standardization (ISO) - Medical laboratories - particular

requirements for quality and competence -, laboratories

must adopt investigation processes to identify

nonconformities with the procedures or requirements of

their quality system. Such processes must be related to

corrective and preventive actions.7 Last few decades

Access this article online

Quick Response Code:

Website:

www.medpulse.in

Accessed Date:

04 October 2017

MedPulse International Journal of Pathology, Print ISSN: 2550-7605, Volume 4, Issue 1, October 2017 pp 07-12

MedPulse International Journal of Pathology, Print ISSN: 2550-7605, Volume 4, Issue 1, October 2017 Page 8

shows a significant decrease in the rates of analytical

errors in clinical laboratories. Improvements and

advancement sin automation, internal and external quality

control programs, accreditations and laboratory

standardization have greatly reduced the number of

overall analytical errors. The available evidence

demonstrates that the pre- and post-analytical steps of the

to attesting process are more error- prone than the

analytical phase.

MATERIALS AND METHODS An observational cum prospective study was designed to

evaluate laboratory errors during the period between Jan

2013 to Jan 2017. A total of 47, 800 samples were

received to the laboratory from both in patients and out

patients. Out of which 22,800 were received from In

patients while 25,000 were received from out patients.

Though the laboratory comprises of all the main six

disciplines, Clinical Chemistry, Hematology, Blood

Banking, Histopathology, Immunology, Microbiology

and molecular genetics. Data was collected exclusively

from the hematology test samples received from both in-

patient and outpatients. As per the hospital policy,

samples from inpatients were to be collected from

different wards by the phlebotomy technicians and

nursing staff throughout 24 hrs, as per the clinician’s

requirement. Test samples from the out patients were

usually registered between 08:00 am to 10:00 pm only.

Documentation of pre-analytical and analytical errors

during sample processing and post analytical errors

during the report dispatch were meticulously documented

and analyzed by the quality manager and lab director, as

per the ISO 15189: 2012 standard guide lines, with

appropriate root cause analysis. A proforma was designed

to document the non conformities, based on the number

of lab errors encountered.

RESULTS Table 1: Frequency of error variables on in-patient and outpatient samples

Type of Errors In-patient

(%)

Out-patient

(%)

Total number of

individual

variables(IP+OP)

Pre-analytical

Haemolysis Labeling errors / incomplete test request forms from consultants.

Inadequate sample/anticoagulant volume ratio

239 (19%)

71(5%)

10(0.8%)

13(1%)

249

84

Quantity Not Sufficient (QNS)/overfilling. 56(04%) 5(0.4%) 61

In appropriate container 80(06%) 33(7%) 83

Incorrect labeling 200(16%) 2(0.16%) 202

Physician Test request missed 44(3.6%) 6(0.5%) 50

Request slip without sample 40(3.3%) 0 34

Illegible handwriting 96(08%) 2(0.16%) 98

Sample not on ice 28(2.2%) 3(0.25%) 31

Incorrect request voucher

Defective screening MP cards without validation and usage of wrong cards by the

undertrained staff.

Equipment break down

20(1.6%)

7(0.5%)

6(0.5%)

4(0.3%) 33

Total 881 84 965

Analytical Errors

Undetected failure in quality control

Erroneous validation of analytical data

Non-conformity with QC

26(02%) 10(0.8%) 36

Calibration drift 31(2.5%) 5(0.4%) 36

Random error 20(1.6%) 0 20

Probe error

Undetected failure in quality control

Erroneous validation of analytical data

8(0.6%) 10(0.8%) 18

Total 85 25 110

Post-analytical

System input error of the requested test. 20(1.6%) 03(0.25%) 23

Delayed reporting 80(6.6%) 07(0.5%) 87

Wrong delivery of reports to patients.

Lack of patient andtreating physician contact details.

Lack of awareness to retrieve reports from the LIS.Critical result reporting errors.

15(1.25%) 00 15

Total 115 10 125

Copyright © 2017, Medpulse Publishing Corporation,

Phases (Types)

Preanalytical

Phase

Analytical Phase

Post Analytical Phase

A total of 47, 800 samples were received in to the

laboratory from both in patients and out patients between

January 2015 to December 2017. Out of which 22,800

were received from in patients while 25,000 were

received from out patients. A total of 1200 err

detected from the total of 47,800 samples with the error

rate of 2.5%.Of all the total errors, pre-analytical errors

were most common, with a frequency of

by post-analytical at 9% and analytical at

2).The total number of errors recorded on inpatient

Figure 1

Legend

Figure 1: Frequency of Preanalytical errors in laboratory

Postanalytical errors in laboratory

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

In Patients Error

Rate (%)

Out Patients

Error Rate (%)

Total Error Rate

73%

7%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

In Patients Error Rate

Pavani B, Sri Manvitha V

Copyright © 2017, Medpulse Publishing Corporation, MedPulse International Journal of Pathology, Volume 4, Issue 1 October 201

Table 2: Total errors in the laboratory

In Patient Error

Rate (%) Out Patient Error Rate (%)

Total Error Rate

(%)

881 {73%} 84 {7%} 965 {80%}

85 {7%} 25 {2%} 110 {9%}

115 {9.5%} 10 {0.83%} 125 {10.3%}

A total of 47, 800 samples were received in to the

laboratory from both in patients and out patients between

2017. Out of which 22,800

were received from in patients while 25,000 were

received from out patients. A total of 1200 errors were

detected from the total of 47,800 samples with the error

analytical errors

were most common, with a frequency of 80%, followed

% and analytical at 10.3% (Table-

errors recorded on inpatient

samples were 1081 out of the 22,800 tests, with an error

rate of 4.7%, while the total number of errors on

outpatient sampleswere119outofthe 25,000tests (an error

rate of 0.4%). Pre analytical phase errors were mainly

pertaining to sample in adequacy, errors during analytical

phase of sample processing were mainly due to IQC

outliers and calibration drift. Post

due to transcription errors and variation sin turnaround

time (Table 2).

Figure 2

Figure 3

Frequency of Preanalytical errors in laboratory; Figure 2: Frequency of Analytical errors in laboratory; Figure 3:

Total Error Rate

(%)

80%

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

In Patients Error

Rate (%)

Out Patients Error

Rate (%)

7%

2%

In Patients Error Rate

(%)

Out Patients Error

Rate (%)

Total Error Rate (%)

10%

1%

11%

, Volume 4, Issue 1 October 2017

Total Error Rate

965 {80%}

110 {9%}

125 {10.3%}

samples were 1081 out of the 22,800 tests, with an error

rate of 4.7%, while the total number of errors on

outpatient sampleswere119outofthe 25,000tests (an error

rate of 0.4%). Pre analytical phase errors were mainly

ng to sample in adequacy, errors during analytical

phase of sample processing were mainly due to IQC

outliers and calibration drift. Post-analytical errors were

due to transcription errors and variation sin turnaround

Figure 3: Frequency of

Out Patients Error Total Error Rate

(%)

9%



DISCUSSION A laboratory error is defined as “a defect occurring during

any part of the laboratory cycle, commencing from

accession of lab tests to the reporting of final results with

appropriate interpretation. This broad definition has

several advantages and, in particular, it encourages a

patient-centered evaluation of errors within laboratory

medicine. The quality of patient care depends up on

accurate and precise lab test reporting. The negative

feedback information provided by the users on the overall

lab performance must be evaluated and resolved

promptly. Our study revealed total error rate of 2.5%,

which appears to be within acceptable statistical limits

and also highlights the competency of our hospital

laboratory. The major number of errors in this study were

noted within pre-analytic phase and is in accordance with

other previousstudies2,6,7

.The study by Lippiet al.

highlights the frequency of pre-analytic errors up to 70%

which is higher than analytical and post-analytic errors 3.

The pre-analytical errors constituted the highest number

for inpatients than the outpatient category, despite the

total number of outpatient samples constituting the

greatest number. The variable receiving the highest rating

among in patients was specimen hemolysis, constituting

up to 19%. For both inpatients andoutpatients, a total pre

analytical error rate of 80% is reported from our lab.

These errors for inpatient samples were more during the

night shift, an observation similar to that of Akanetal2006

5. There as on attributed for the increased frequency of

haemolysis during night shift, is lack of awareness and

training among the nursing staff and phlebotomists about

sample collection and transportation which itself high

lights the need for training andperiodic competency

assessments. For the outpatients category, pre analytical

error variable associated with highest frequency rating

was that of loading of sample in an inappropriate

container constituting up to 7%,followed by other

miscellaneous group of errors such as sample container

labeling errors and incomplete test request forms from

consultants etc. The consultants were therefore informed

about the need for avoiding incomplete filling up of the

request slip. For both inpatients and outpatients, a total analytical error rate of 9.1% was reported. The variable

receiving the highest frequency rating among in patients

was calibration drift, constituting up to 2.5%. For the

outpatients, the analytical error variable with the highest

frequency rating was QC failure (0.8%). The error

variable associated with sample without request slip was

found to be nil for outpatients. The advancements in

automation, implementation of internal quality control

program and participation in proficiency testing are the

factors which cause reduction of errors during analytical

phase. Our study highlights that most analytic errors were

instrument related, including the malfunctioning of

instruments and calibration drift that resulted in

unacceptable quality control. The laboratories should

ideally draft an SOP on equipment care, operation,

calibration, daily maintenance and corrective action

procedure for managing the QC outliers. Most of the IP

and OP errors (10.3%) within the post-analytic category

were mainly associated with delayed reporting accounting

to 6.6% for IP casesand0.5% for OP cases, which again

led to the increased turnaround time. This particular

aspect was due to unpredictable increases within the

workload and non–availability of adequate staff. The

other related errors were linked to the LIS, e.g. patient

input errors, unrecognized barcodes and lack of

implementation of LIS inallsections, due to which the

results were not transferred via direct interfacing from the

instruments. Root cause analysis of the latter revealed that

periodic function checks and validation of LIS were not

conducted as per the scheduled guidelines. Departmental

sections without interface facility had higher error rate as

compared to the departments with interface facility, since

the review criteria before report release was well placed

in the latter. The second most common error was the

discrepancy between tests marked on the request form

and system entry data of the same. This is important

because missing tests could cause increased TAT and

delay with the patient management. Most of the

discrepancies between the requisition and LIS entry

originated from input error of the requested test,

accounting up to 1.6% for IP samplesand0.25% for OP

samples. Few things such as inappropriate use of

laboratory test results, critical result reporting, and

transmission of correct results are areas of potential error

in the post-analytical phase of the total laboratory testing

process. The other potential reason for post analytical

errors were due to invalid data entry, missing computer

entry of one or more of the tests marked on the request

form and lack of review by the concerned authorities.

Few miscellaneous errors on in patient samples were due

to lack of communication to the treating physicians either

due to non availability of the contact details or

information lapse regarding the exact patient location,

which also led to wrong delivery of the test reports. Lack

of awareness to retrieve reports through hospital

information system also formed an important quality

indicator and in appropriate use of the LIS when the

results were transferred from the instruments to the LIS,

which led to delayedturnaroundtime11. All the above

mentioned miscellaneous post analytical errors

accounting to 15 cases (1.25%) exclusively on IP

samples. For OP reports, the recorded errors were nil

(0%).Therefore an efficient software was strongly

recommended by the lab management to handle the IP

Pavani B, Sri Manvitha V

Copyright © 2017, Medpulse Publishing Corporation, MedPulse International Journal of Pathology, Volume 4, Issue 1 October 2017

post analytical errors thereby including a provision for

better retrieval and display of interfaced test reports and

transmission of critical alerts within the wards. In an article by Plebani

7, the authors give a comprehensive

overview on the ongoing efforts for improving actual

consensus on the definition and notification of laboratory

critical values, and for evaluating their contribution to

improve clinical outcomes and patient safety. The article

also provides some highlights on a valuable experience of

automated notification, which is a reliable tool for

improving the timeliness of communication results are

released to and avoiding potential errors for which

accreditation programs require read-back of the results. Incident Reporting in Laboratory Diagnostics: While

major efforts have been made to monitor the pre-

analytical phase and provide reliable solutions, it is

surprising that concrete formal programs of incident

reporting have not been so pervasive in laboratory

diagnostics. The major focus in health care is placed on

incident reporting for several medical conditions with

lesser effort devoted to translating this noteworthy

practice into laboratory diagnostics. If, in fact, laboratory

errors are being underreported, then current statistics

reveal only a small portion of the medical errors actually

taking place. Some of these sentinel events have already

been identified, including inappropriate test requests and

patient misidentification (pre-analytical phase), use of

wrong assays, severe analytical errors, tests performed on

unsuitable samples, release of lab results in spite of poor

quality controls (analytical phase), and failure to alert

critical values and wrong report destination (post-

analytical phase). The Drafting Group of WHO’s

International Classification for Patient Safety (ICPS) has

also developed a conceptual framework that might also be

suitable for diagnostics errors. Development and

widespread implementation of a Total Quality

Management (TQM) system is the most. Effective

strategy to minimize uncertainty in laboratory

diagnostics. Pragmatically, this can be achieved. Using 3

complementary actions: preventing adverse events (error

prevention), making them visible (error Detection), and

mitigating their adverse consequences when they occur

(error management). A laboratory information

management system (LIMS), sometimes referred to as a

laboratory. Information system (LIS) or laboratory

management system (LMS), is a software-based

laboratory and laboratory system with features that

support a modern laboratory's operations. The features

and uses of a LIMS have evolved over the years from

simple sample tracking to an enterprise resource planning

tool that manages multiple aspects of laboratory

informatics. The definition of a LIMS is somewhat

controversial: LIMSs are dynamic because the

laboratory's. Requirements are rapidly evolving and

different labs often have different needs. Therefore, a

working. Definition of a LIMS ultimately depends on the

interpretation by the individuals or groups involved12

Other methodologies can also be used to prevent errors.

Failure Mode and Effect Analysis (FMEA) has been

broadly cited as reliable approach to risk management. It

is a systematic process for identifying potential process

failures before they occur, with the aim to eliminate them

or minimize the relative risk. Root Cause Analysis (RCA)

is an additional most commonly adopted valuable aid,

since it is based on a retrospective analytical approach.

An RCA focuses on identifying the latent conditions

underlying variation in medical performance and, if

applicable, developing recommendations for

improvements to decrease the likelihood of a similar

incident in future. Risk management is a planned process

that is part of both corrective and preventive actions, and

is related to stability and predictability of results. It is

worth noting that both kinds of action need reports or

notifications that depend on the existence and

implementation of a culture directed to quality care and

patient safety. In a hospital lab with large work load,

negligent attitude of the persons involved in whole

process can cause problems, and therefore, manual entry

of patient data with lab numbers, must be replaced by

electronic entries. Electronic data should be made secure

via password protection. Documentation of the strategies

for evaluation of error detection and risk evaluation must

be adopted to document the errors occurring all the three

phases of sample processing in order to improve the

efficiency of lab. Laboratory errors, besides carrying

deleterious effect on patient overall health, they also

translate into huge amount of financial losses for the

hospital management.

CONCLUSION It is possible to reduce the errors in laboratory medicine

during whole testing process but impossible to completely

eradicate errors. Significant progress has been made since

the release of “To Err is Human.” Basically what has

changed is the willingness to recognize the challenge and

not argue about the numbers, but appreciate care must be

safe always and everywhere for each patient. This has led

to remarkable changes in the culture of health care

organizations, so medical errors can no longer be seen as

inevitable, but as something that can be actively

streamlined and prevented. Sample collection errors may

be prevented via continuous training programs and

competency assessments of the staff The laboratory

professionals must be leaders in ensuring patient safety

both inside and outside the walls of clinical laboratories.



REFERENCES 1. Ottomano C. Errors in medicine and errors in laboratory

medicine: What is the difference? Blood transfusion

2010; 8:79-81.

2. Chhillar N, Khurana S, Agarwal R, Kumar N. Effects of

pre-analytical errors on quality of Laboratory medicine at

neuropsychiatry institute in North India. Ind J Clin

Biochem 2010; 26(1):46-9.

3. Lippi G, Banfi G, Buttarello M, Ceriotti F, Daves M,

Dolci A, et al. Recommendations for Detection and

management of unsuitable samples in clinical

laboratories. Clin Chem Lab Med 2007; 45(6):728-36.

4. SharmaP.Editorialpre-

analyticalvariablesandlaboratoryperformance.IndJClinBi

ochem 2009; 24(2):109–10.

5. Akan OA, Elmali E, Karaeren Z. Evaluation of pre-

analytical errors in clinical laboratory. Lab Med 2006;

37(8):478-80.

6. Carraro P, Plebani M. ErrorsinaStat Laboratory: Types

and frequencies 10 years later. Clin Chem 2007;

53(7):1338–42.

7. BoniniP,PlebaniM,CeriottiF,RubboliF.Errorsin laboratory

medicine. Clin Chem 2002; 48:691–8.

8. HowanitzPJ. Errors in laboratory medicine: practical

lessons to improve patient safety. Arch Pathol LabMed

2005; 129:1252–61.

9. AstionML, Shojana KG, HamilTR, KimS, NgVL.

Classifying laboratory incidents reports to Identify

problems that jeopardize patient safety. Am J Clin Pathol

2003; 120:18–26.

10. Lippi G, Bassi A, Brocco G, Montagnana M,Sal-

vagnoGL,Guidi G Cet al: Pre-analyticerror Tracking in a

laboratory medicine department: results of a 1-year

experience. Clin Chem 2006; 52(7):1442-3.

11. Wang S, Ho V. Corrections of clinical chemistry test

results in laboratory information System. ArchPathol Lab

Med 2004; 128:890-2.

12. Kohn Cramer, Kevin (28 November 2016). "What is a

LIMS?". sapiosciences.com. Retrieved 28 November

2016.

Source of Support: None Declared

Conflict of Interest: None Declared

evaluation of errors in clinical hematology practice

Documents