cbenson-tsu-vt.weebly.com · Web viewClinical pathology and laboratory analysis are vital tools in every doctor of medicine’s diagnostic arsenal. Errors can occur at three points

Running Head: REDUCING VARIABLES AFFECTING LABORATORY RESULTS

The Proposed Use of Quality Assurance and Standard Operating Procedures to Reduce

Preanalytic Variables Potentially Influencing Clinical Laboratory Results

Christina M. Benson

Tarleton State University

VETE 4208 Veterinary Research

December 4, 2017

Author Note

Christina M. Benson, Department of Veterinary Technology, Tarleton State University, Stephenville, Texas.

The author would like to thank Barb Lewis, MA, CVT, VTS (Clinical Pathology), Barbie Papajeski, MS, LVT, RLATG, VTS (Clinical Pathology), and Dan Walsh, MPS, RVT, VTS (Clinical Pathology) for their support and assistance in my professional journey, including their insight into quality assurance and control, and for sharing with new generations of veterinary technicians their love of clinical pathology.

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REDUCING VARIABLES AFFECTING LABORATORY RESULTS

Abstract

Clinical pathology and laboratory analysis are vital tools in every doctor of medicine’s

diagnostic arsenal. Errors can occur at three points in the laboratory process, affecting the

production of accurate results; these errors may adversely affect the diagnosis, prognosis, and

treatment of patients. Most frequently, these errors occur during the preanalytic phase, or during

the collection, handling, processing and storage of patient samples – affecting samples before

they are analyzed. The establishment of quality management in the clinical laboratory, focusing

on education, awareness, and the careful creation and use of standard operating procedures, can

reduce the frequency of preanalytic errors in the laboratory.

Keywords: analytic variable, clinical pathology, diagnostic testing, external quality assessment,

laboratory error, preanalytic error, preanalytic factor, preanalytic variable, quality assurance,

quality control, standard operating procedure, total quality management system

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Table of Contents

Introduction 4

Statement of problem 5

Purpose of review 6

Hypotheses 6

Research Questions 6

Definitions 6

Assumptions 8

Limitations 8

Delimitations 9

Literature Review 9

Methodology 11

Data Analysis 15

Findings 16

Summary and Conclusions 19

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Implications of Findings 22

Recommendations 23

References 25

Appendix 28

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The Use of Quality Assurance and Standard Operating Procedures to Reduce Preanalytic

Variables Potentially Influencing Clinical Laboratory Results

Introduction

Clinical pathology, the medical science of diagnostic sample analysis, is an important

tool in every doctor’s arsenal. Diagnostic samples such as plasma, serum, and urine contain

measurable substances called analytes, which are by-products of the digestive process; the levels

of these analytes in the blood or urine can inform the clinician of the patient’s systemic health.

Whole blood samples can relay the condition of the body’s bone marrow, and can also provide

warning of potential infection or inflammation. Body cavity fluids, bodily excretions, and

samples of tissue or bone can be examined in microscopic detail, revealing minute damage at the

cellular level that could contribute to a pet’s illness.

Veterinary clinicians expect to receive actionable data from the samples they tender to

the clinical pathology laboratory. They rely upon that data to provide their clients with both a

diagnosis and a prognosis of their pet’s condition. However, diagnostic results depend on the

submission of true diagnostic samples. Even the slightest mistake in sample handling or

processing can adversely affect the reported laboratory results.

Errors can occur at three points during the clinical pathology process: the preanalytic,

analytic, and postanalytic phases. The preanalytic phase spans the time from the order of the

diagnostic test, to when the sample is ready to be analyzed in the laboratory (Braun, Bourgès-

Abella, Geffré, Concordet, & Trumel, 2015). The analytic phase covers the interval during

which the sample is analyzed, and the postanalytic phase, as expected, is the period following the

analysis of the sample, when the test results are reported (Hammerling, 2012). Accurate

laboratory results require the elimination of as many sources of error possible.

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Historically, the source of laboratory error most commonly targeted for reduction has

been analytic error, or error that occurs during the active performance of the laboratory test or

analysis (Plebani & Carraro, 1997). Analytic quality is directly measured by internal quality

control, external quality assessments (EQA), and proficiency testing of laboratory personnel.

The literature shows that quality assessment programs have been employed for many years in

laboratory medicine. Internal quality control assesses the accuracy and precision of laboratory

instrumentation against a known control; EQA check the laboratory’s instruments and testing

procedures against an external and unbiased control, such as a reference laboratory; and

proficiency testing checks the ability of the laboratory employees to perform the analyses

correctly (Hammerling, 2012).

Little attention was paid to sources of extra-analytic errors until the early 1990s, when

laboratory automation became the rule rather than the exception, thus causing analytic errors to

decrease (Plebani, 2014). By the close of that decade, the focus had shifted to pre- and

postanalytic factors as ascendant issues impacting the accuracy or delivery of laboratory results.

Due to the noted frequency of preanalytic errors, which stem from procedures less likely to be

automated such as sample collection, handling, and processing (Hooijberg, Leidinger, &

Freeman, 2012), proposals began to arise for the reduction and control of these factors.

The premise of my research investigation is that the literature will demonstrate that

preanalytic errors in the clinical pathology laboratory can be reduced or eliminated with the

implementation of quality assurance and standard operating procedures.

Statement of Problem

Preanalytic factors – those influencing the sample from the time the test is ordered to the

moment of analysis – are a significant source of preventable laboratory error in human medicine

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(Braun, et al., 2015). It would be fair to assume the same would be true in veterinary medicine.

In order to obtain the best diagnostic laboratory results, clinicians must eliminate as many

sources of preanalytic error as possible. Would quality assurance protocols, quality control

procedures/protocols, and standard operating procedures assist in eliminating these sources of

error in the veterinary clinical pathology process?

Purpose of Literature Review

The purpose of this literature review is to find confirmation of methods and means to

eliminate or reduce preanalytic errors in the veterinary clinic and the clinical pathology

laboratory. Should support for the hypothesis be found, the author would recommend specific

protocols and procedures to achieve that goal.

Hypothesis

Quality control procedures/protocols, quality assurance protocols, and standard operating

procedures specific to clinical pathology laboratory testing will reduce the potential occurrence

of preanalytic errors.

Research Questions

What is quality assurance, and how do quality assurance protocols assist in error

elimination? What specific quality assurance measures will aid the preanalytic phase of

laboratory analysis? How do well-written, detailed and thorough standard operating procedures

for all preanalytic factors and tasks assist clinic and laboratory personnel in avoidance of errors?

Definitions

In order to properly discuss the subject matter at hand, certain terms must be explained

and defined. Key terms in this paper include analytic error, postanalytic error, preanalytic error,

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quality assurance, quality control, and standard operating procedure. The working definitions for

each in this literature review are as follows:

Analytic error: Any error that occurs during the performance of a laboratory assay. This

can include technician errors and machine errors.

Postanalytic error: Any error that occurs after the performance of a laboratory assay.

This includes errors in the recording of results into the patient’s medical record, the reporting of

results to the attending physician or veterinarian, the interpretation of the results by the attending,

and the formulation of a treatment plan by the attending based on the given laboratory results.

Preanalytic error: Any error that occurs before the performance of a laboratory assay.

This starts with the doctor’s order of the diagnostic test, proceeds through sample collection and

submission to the laboratory, and ends with the preparation of the sample for performance of the

laboratory assay.

Quality assurance (QA): Specific procedures which are intended to provide oversight of

the complete clinical pathology process (from preanalytic to analytic to postanalytic factors),

with the goal of error reduction and the subsequent increase of accurate laboratory results

received (after AVCPT, 2016).

Quality control (QC): Specific procedures which are intended to confirm the efficacy of

testing kits, to monitor the analytic performance and assure the consistency of laboratory

instrumentation, and to monitor the performance of laboratory personnel, with the goal of

ensuring the reliability of laboratory results (after AVCPT, 2016). Quality control is an essential

part of quality assurance.

Standard operating procedure (SOP): Defined by Merriam-Webster as “established or

prescribed methods to be followed routinely for the performance of designated operations”

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(n.d.), in common veterinary practice, an SOP is a written document which outlines the

individual steps to be followed in completion of a prescribed task.

Assumptions

For the purpose of this literature review, it must be assumed that preanalytic errors can be

easily recognized and controlled. It is assumed that the subjects in the various studies reviewed

were equally well-informed on preanalytic errors, and that they were equally able to consistently

and accurately identify these errors as they arose. It is also assumed that the participants had

equal knowledge of the consequences that preanalytic errors may present to patient health, and

that they placed enough value on those consequences to wish to eliminate them.

Limitations

This literature review may be limited by a lack of studies exploring attempts to eliminate

preanalytic errors in veterinary medicine. The bulk of surveyed studies relating to preanalytic

errors involve the identification and quantification of these errors, rather than the steps taken to

eliminate them.

This literature review may also be limited by researchers focusing specifically on quality

control (in-laboratory test performance) over quality assurance (the full spectrum of laboratory

error, including pre- and postanalytic errors).

This review may be limited by the availability of literature in the online Tarleton library’s

collection. My local public and nearby college campus libraries are not well-supplied with

scientific, peer-reviewed clinical pathology or laboratory science journals.

This review may further be limited due to time constraints imposed by employment and

other additional school work. Time management and allocation to various tasks have required

careful attention.

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Delimitations

This literature review focuses exclusively on preanalytic factors in the clinical pathology

process, and on errors that may occur during the preanalytic phase of testing. It will not

investigate either analytic or postanalytic factors, nor will I be addressing errors that may occur

during these phases.

This review also searches for evidence that a quality assurance program involving

standard operating procedures will assist in the reduction and limitation of preanalytic errors. It

will not investigate the training of personnel, which, although important, is not always performed

consistently.

Literature Review

This literature review revealed that several studies have been performed in human

medicine to evaluate the types of errors found in the clinical pathology laboratory. The results of

these studies appear to confirm that preanalytic errors are the predominant type of error found

consistently over time.

In particular, the work of Mario Plebani and Paolo Carraro in Italy compares the same

laboratory, ten years apart. In 1996, Plebani and Carraro examined the “stat” section of the

Department of Laboratory Medicine in the University-Hospital of Padova, Italy. Their intent

was to determine the frequency and type of laboratory errors produced at the defined preanalytic,

analytic, and postanalytic phases, in order to construct corrective strategies as needed (Plebani &

Carraro, 1997).

To this end, they chose four medical departments within the hospital: Internal Medicine,

Nephrology, Surgery, and Intensive Care. They monitored all stat laboratory samples from these

departments for a period of three months; the study length was chosen to receive maximum data

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from the doctors and nurses while not over-burdening the medical personnel with an extended

period of intense test result scrutiny. The medical personnel were asked to record any suspicious

test results for daily consultation and discussion with a laboratory physician; if considered a

“clinically questionable” result, the sample was inspected and retested. A search was then

conducted to determine possible interferences (Plebani & Carraro, 1997).

A second study was performed in 2006 by Carraro and Plebani at the same Italian

university hospital’s stat laboratory, using the same study design and methodology for a three-

month time period (Carraro & Plebani, 2007).

In 2010, Carraro and Plebani teamed up with Tatiana Zago to investigate so-called “pre-

preanalytic” errors, or those errors which occur prior to the sample’s arrival at the laboratory for

analysis (as would commonly be found in veterinary practice). In this study, conducted over a

six-month period at the S. Antonio Hospital, a public hospital of the Italian National Health Care

system in Padova, Italy, three clinic wards were selected to be monitored. A one-week direct

observational phase, wherein Ms. Zago followed the medical personnel to observe all steps of

test ordering, preceded the main study. During the study period, the focus was on identification

and quantification of errors and instances of non-compliance with the established study operating

procedures. All medical personnel were directed to report potential quality assurance/control

failures and non-conformity with sample suitability.

On the veterinary side, Hooijberg, Leidinger, & Freeman (2012) followed for eight years

an error management system (EMS) used in an Austrian commercial veterinary clinical

diagnostic laboratory, which participated in a national EQA program designed for human

pathology laboratories, had ISO 9001 accreditation, and was approved as a training laboratory.

Following training in error categories and data entry, laboratory errors were tracked by the

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laboratory employees, and any necessary corrective actions were immediately taken to eliminate

the errors as they were noted.

Methodology

The 1996 study performed by Plebani and Carraro, as stated, was conducted utilizing the

in-house “stat” service laboratory and personnel employed by the University-Hospital of Padua

(Italy). The hospital population was large, with 2900 patient beds available. The laboratory

utilized automated equipment, connected to laboratory information system (LIS) to perform

hematology, blood chemistry, coagulation, toxicology, and drug analyses. Four department

wards of the hospital were chosen to have their stat laboratory submissions monitored for the

study period. All physicians and nurses employed in the involved wards were asked to give

“maximal critical attention” to all test results (Plebani & Carraro, 1997), and all were provided

with a special notebook into which any “suspect” laboratory results and related clinical

information were recorded. These results were then reviewed and discussed daily with the

laboratory physician.

Any results seen as questionable, when considered beside the clinical data, had their

original requests checked, and submitted specimens examined and retested, using either the same

method and instrumentation or occasionally with an alternate method or different instrument.

Investigations into possible interferences were also conducted when necessary.

For purposes of this study, the authors defined analytic errors as “all data outside of the

limits proposed as European quality specifications for imprecision (considered to be less than 0.5

of the average subject’s biological variation) and inaccuracy (less than 0.25 of the group’s

(within-subject plus between-subject) biological variation, or less than 1/16 of the reference

interval)” (Plebani & Carraro, 1997). Laboratory mistakes were considered to be “all results

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exceeding…the internally defined mean turnaround time” by greater than 3 Standard Deviations.

The Confidence Interval (CI) Analysis computing program was used to determine statistical

significance of mistake relative frequencies between the participating departments.

The 2006 follow-up study, also performed by Plebani and Carraro at the same hospital in

Padua, followed the exact study design as the original study from 1996 (Carraro & Plebani,

2007). The subject population had decreased from 2900 hospital beds in 1996 to 1750 beds

available in 2006; however, the “stat” laboratory performed a quarter of a million more analyses

in 2006 as were performed a decade earlier. To eliminate any internal bias regarding results

obtained during testing, the laboratory employees were not informed that a study was being

performed; this was not stated as occurring during the 1996 study. Also differing from the 1996

study was the condition that a laboratory scientist checked the internal quality control data during

the study (Carraro & Plebani, 2007).

For purposes of this second study, the authors defined laboratory errors as all data

“exceeding limits approved in the Stockholm Consensus Conference of 1999”, and based on

biological variation; any results that exceeded the same limits when repeated in the same

specimen; and any results obtained later than the established turn-around time limits for the

facility (Carraro & Plebani, 2007). Laboratory mistakes were classified according to the 1996

definition, with the addition of criteria from the International Organization for Standardization

(ISO) Technical Report 22367 regarding latent, cognitive, and preventable errors. The statistical

significance of mistake relative frequencies between the participating departments was calculated

using the Chi-Squared (𝜲2) test.

These two studies were run on a qualitative experimental research design, intended to

determine which of three variables (sources of lab error) was influencing the laboratory results;

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the data were measured numerically. There was internal validity to the design, as the

experimental variables were clearly defined and accurately measured, eliminating internal bias

such as deciding what an “abnormal” result would be. External validity was likely to be high as

well, based on the large subject population, the selection of subjects from four distinct groups

within the main population, and the large sample size contributing data to the results.

In the 2011 study performed by Carraro, Zago, and Plebani, the clinical laboratory,

laboratory personnel, and ward doctors and nurses of the S. Antonio Hospital in Padova, Italy

were used. This hospital had a much smaller population, with 375 beds available; only three

wards within the hospital were chosen to participate in the study; this introduced limitations to

the design regarding the extrapolation of the results to a larger population. Each ward’s “pre-

preanalytic” workflow was analyzed and then detailed in a flow chart; each ward also received

detailed instructions regarding the proper performance of pre-preanalytic procedures (i.e. test

ordering by the physician, patient preparation and identification, tube preparation, and sample

collection, preparation, and transportation to the laboratory). Any violation or departure from the

protocols was to be considered a nonconformity, even if no recorded laboratory error resulted

from the deviance (Carraro, Zago, & Plebani, 2012).

This study was performed in two parts. The first part, lasting one week, had one of the

researchers follow ward personnel in each of the participating wards during the steps of

requesting test analyses. The second portion of the study, lasting six months, was intended to

identify all errors and non-compliance events in sample submission and analysis. Pre-

preanalytic procedures in the treatment wards were all recorded. Laboratory personnel were

instructed to record all instances of true and even possible specimen quality failures as

nonconformities, as defined by the protocols enforced in the treatment wards. The differences in

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error rates found in the main six-month body of the study versus those noted in the preliminary

one-week direct observation phase were evaluated for statistical significance using the test for

equality of proportions (Carraro, Zago, & Plebani, 2012).

This was also a qualitative experimental research design, intended to determine which of

three variables (sources of lab error) was influencing the laboratory results; the data were

measured numerically. The internal validity was good, with clearly defined errors and non-

compliance events; the external validity, however, likely suffered because of the smaller sample

size.

The Hooijberg, Leidinger, & Freeman study from 2012 was performed in an Austrian

commercial veterinary clinical diagnostic training laboratory. The laboratory personnel received

extensive training on the types of laboratory errors expected, and they were to record the errors

in the correct category in the LIS error management system (EMS) when encountered. Errors

were also expected to be corrected when encountered, if possible, and the correction

documented; the types of corrective action were decided by the laboratory director in

consultation with the quality manager. Depending on the errors found, a single sample could

generate more than one error annotation. Standard operating procedures were used to document

QC procedures, assessments, and responses. Error categories included preanalytic, analytic,

postanalytic, and “other”; sources of error included client complaints, laboratory staff, internal

machine-generated QC errors, proficiencies testing, errors reported during laboratory audits, and

supplier information. Laboratory personnel were instructed not to record hemolytic or lipemic

samples as errors, to avoid inflating the error rates recorded.

The EMS created monthly and annual error reports, and a list of the recorded corrections

and preventive actions taken. The error reports were examined by the laboratory director, and

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the director was also responsible for monitoring corrective and preventative action efficacy, and

producing a report for the annual management review (Hooijberg, Leidinger, & Freeman, 2012).

This study also featured a qualitative experimental research design, intended to calculate

the number of errors per defined category over the eight-year period of study; the data were

measured numerically. There was internal validity to the design, as the experimental variables

were clearly defined to the participants prior to the study; eliminating potential internal bias such

as deciding what an “abnormal” result would be. External validity was likely to be high, based

on the large subject population, the selection of subjects from four distinct groups within the

main population, and the large sample size contributing data to the results.

Data Analysis

In the 1996 study by Plebani and Carraro, during the three-month period of research,

nearly 40.5 thousand test analyses were performed, of which 359 results were judged to be

“questionable” – an error rate of just 0.89%. Over half (52.6%) of the 359 questionable results,

or approximately 189 results (0.47% of total tests performed), were found to be laboratory errors.

The error frequency rate was found to be highest in the Internal Medicine Department as

compared to the Surgery and Intensive Care units; the higher rate of error frequency was found

to be statistically significant based on Confidence Interval (CI) Analysis. No comparison was

made between the Internal Medicine Department and the Nephrology Department (Plebani &

Carraro, 1997).

In 2006’s follow-up study, Carraro and Plebani analyzed over 51.5 thousand laboratory

analyses, yielding 393 questionable results (or a 0.76% error rate); of these, 40.7%, or 160 errors,

were determined to be laboratory error. Seventy-three of the 160 errors were confirmed to be

laboratory errors as they entered the lab, and eighty-seven errors were identified by the

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laboratory staff. The overall laboratory error number proved to be a statistically significant

decrease from the 1996 results; there were no statistical differences in error frequencies between

the participating departments (Carraro & Plebani, 2007).

In the 2010 study by Carraro, Zago, and Plebani, the reported error frequency during the

one-week direct observational period was 0.47% (96 errors per 2349 tests performed); the error

frequency during the six-month laboratory study was 0.56% (304 errors per 53 thousand tests

performed). The difference in error frequency rates (among all error types) was not statistically

significant (Carraro, Zago, & Plebani, 2011).

In Hooijberg, Leidinger, & Freeman’s 2012 review, the EMS recorded both the number

of errors in each category, as well as the percentages of each error as a fraction of the total. The

annual error reports from 2003 – 2010 (inclusive) were used. All error data from the reports

were transcribed into a spreadsheet, including the absolute number of errors per year, the number

of corrective/preventive actions performed per year, and the error rate per number of samples run

in total. Each error type was calculated as a percentage of total errors for each year sampled, and

confidence intervals (95% CI) calculated per year. For the four different error categories, sigma

metrics were used for analysis, utilizing the Six Sigma online calculator.

Findings

Of the 189 confirmed laboratory errors in the 1996 Plebani and Carraro study, the

number of preanalytic errors was 129, or 68.2% of confirmed errors, as compared to 25 analytic

errors (13.3%), and 35 (18.5%) postanalytic errors. It was found that of the 129 preanalytic

errors, 84 (65%) arose in the participating medical departments. The most common preanalytic

errors were related to sample collection, particularly errors in obtaining samples and filling

collection tubes. Nineteen percent of the laboratory errors resulted in repeated or additional

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patient testing; 6.3% of the errors led to inappropriate therapy. The majority of the errors found

(74%) did not affect the clinical treatment of the patients involved (Plebani & Carraro, 1997).

In the Carraro and Plebani follow-up study a decade later, the preanalytic phase was

again the most error-prone, with a 61.9% error frequency noted – 99 out of the 160 laboratory

errors were found to be preanalytic in origin. In comparison, 15% (n=24) errors occurred during

the analytic phase, and 23.1% (n≈37) were found to occur in the postanalytic phase of testing.

Echoing the original 1996 study, the most common preanalytic errors again related to sample

collection. It was also determined by Carraro and Plebani that only 18.1% of the noted errors

originated in the clinical pathology laboratory itself; and that 73.1% of the errors were

considered “preventable.” As in the 1996 study, the majority (75.6%) of the errors did not affect

patient outcomes, but 24.4% (nearly a quarter) of the errors adversely affected patient care

(Carraro & Plebani, 2007).

In the 2010 study, the most common errors noted were related to order transmission and

hemolysis (a collection artifact) in blood samples. However, there were three incidents of

patients being misidentified, which could have caused profound harm to the patients involved.

Patient and sample identification, sample collection, and order transmission all fall under

preanalytic errors (Carraro, Zago, & Plebani, 2011).

A total of approximately 332.9 thousand samples were analyzed during the eight-year

period studied by Hooijberg, Leidinger, & Freeman (2012); the total recorded error rates for this

period ranged from 1.3% in 2003 to 0.7% in 2010 – a statistically significant decrease over time.

As expected, based on the other studies reviewed, preanalytic errors were the most commonly-

encountered laboratory error, spanning a low of 52% to a high of 77% of annual recorded errors,

with a sigma metric of 4.1. Analytic errors were again the lowest, with a range of 4-14% (sigma

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metric 4.8) over the study period, and postanalytic errors ranged from 9-21% of annual recorded

errors over the eight-year period (sigma metric 4.5). The category of “other” errors (described as

containing errors with the potential to affect all three of the other phases, associated with the

QMS) occurred between 9-16% of the time (sigma metric 4.7; based on a sigma metric scale of 1

– 6, with a higher sigma score reflecting higher reliability).

As previously noted, hemolysis and lipemia were not recorded as sources of error, due to

their frequency of occurrence, and their occasional concurrence, which could have skewed the

results abnormally toward preanalytic error if included. The researchers noted that the errors

which were recorded reflect only the number of errors noticed by the laboratory personnel; the

data omit any unnoticed errors and those self-corrected but unreported. The study authors

theorize that preanalytic errors occurred more frequently in this veterinary laboratory versus a

human laboratory due to the processing of its samples on an outpatient basis, as opposed to

human laboratories which are often located in the same building as the patients and receive their

samples directly from the wards (Hooijberg, Leidinger, & Freeman, 2012). By this reasoning,

preanalytic errors might be reduced in cases of veterinary “in-house” or point-of-care testing

(POCT).

Hooijberg, Leidinger, & Freeman (2012) also speculate that pre- and postanalytic errors

may outstrip analytic errors because these phases of analysis are not automated and not well-

standardized; the possibility of multiple people being involved in a single preanalytic process

may have caused confusion and increased the likelihood of error as well. On the other hand,

having more people involved may have actually increased the likelihood of discovery and

recording of errors in the preanalytic phase.

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Summary and Conclusions

Summary

In this literature review, I have explored the issue of errors in the clinical pathology

laboratory, with a specific focus on preanalytic errors: The frequency of their occurrence, the

forms these errors take, and their effect on the production of consistent, reliable, and diagnostic

laboratory results. The literature appeared to demonstrate that preanalytic errors were the most-

frequently observed laboratory errors, and have the greatest opportunity to affect the

obtainability of accurate, diagnostic results.

Also demonstrated was that a large number of preanalytic errors occur outside of the

clinical laboratory setting, instead originating in the clinical treatment wards where the samples

for analysis are collected; this has earned them the unofficial term of “pre-preanalytic errors” in

human medicine. Braun, et al. report that this is also true in veterinary medicine, where

diagnostic sampling is even occasionally performed outdoors instead of inside of a clinic setting,

making it difficult to follow established preanalytic sampling, storage, and transport protocols;

however, the veterinary profession can and should attempt to “optimize” the “pre-preanalytic”

phase (Braun, et al., 2015).

Conclusions

As expected, it was found that preanalytic factors were a major source of error in the

human clinical pathology laboratory. This finding was seen to carry over into veterinary

medicine, having the same potential undue influences and effects on sample collection and

analysis, or adverse effects on the results produced. An old computing adage states, “Garbage

in, garbage out,” and this is also true of diagnostic clinical pathology. A poor sample would

logically be expected to produce poor quality results. If a non-diagnostic sample is submitted for

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analysis, not even the wiliest veterinary pathology diplomate would be able to glean diagnostic

value from it.

Laboratory errors can dramatically impact the diagnosis and treatment of medical

conditions, especially if the erroneous result leads a clinician to a faulty diagnosis. Tests which

must be repeated because of a laboratory error, additional testing ordered based on an incorrect

value, and treatments commenced in response to flawed laboratory results – per Plebani (2014),

in human medicine, these affect the patient as a source of additional pain, anxiety, and stress; the

same could easily be stated for veterinary patients (Cox, 2012), but also impacted is the client in

terms of lost time from work, additional (and ultimately unnecessary) expenses, and an increase

in concern or anxiety due to their pet’s perceived medical condition. The clinician may also

suffer consequences from a laboratory error in the potential loss of client esteem for the

clinician’s knowledge, in loss of client loyalty with transfer to another clinic, and a possible

reduction of the practice or clinician’s reputation should word spread from dissatisfied clientele.

Braun, et al. make a distinction between technical preanalytic factors (such as collection

technique, sample handling, and sample storage), which can be controlled; and biologic factors

related directly to the patient itself (such as stress levels, hydration, anorexia, medications,

circadian rhythms), which cannot (Braun, et al., 2015; Walsh, 2012). It is recommended that

biologic factors that may affect laboratory results be annotated in the patient’s chart, and that the

review of the laboratory results take these biologic factors into account.

Based on the nature of the so-called “pre-preanalytic” and preanalytic errors identified,

the various literature surveyed appeared to be of one mind when confronting the issue of

laboratory error: Errors could be reduced with the application of a total quality management

system (TQMS), including some form of quality assessment or assurance, quality control

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measures, training of personnel involved in collection and processing of laboratory samples, and

written guidance via standard operating procedures (Abaxis Inc., 2002; ASVCP, 2013; Braun, et

al., 2015; Carraro & Plebani, 2007; Carraro, Zago, & Plebani, 2012; Hooijberg, Leidinger &

Freeman, 2012; Plebani & Carraro, 1997).

In a brief, non-scientific survey of veterinary professionals, conducted by the author in

October 2017 (see Appendix 2), eleven participants surveyed described their top three errors in

the clinical pathology process; nine of the thirteen identified errors were preanalytic in nature

(69%). All eleven participants correctly identified the preanalytic phase as the time when the

most errors occur in clinical pathology. A majority of participants (8 of 11) indicated their belief

that standard operating procedures (SOPs) would standardize the test procedures; however, few

correctly placed SOPs into the general category of quality assurance. Most of the stated

perceived benefits assigned to an SOP program were in the realm of preventing analytic errors –

specifically within the realm of quality control.

According to the American Society for Veterinary Clinical Pathology (ASVCP), most

veterinary colleges in the United States provide little to no formal education or training on

quality assurance or quality control in their curricula, meaning that that graduate veterinarians

are ill-equipped to evaluate point-of-care testing (POCT) equipment or judge the quality of

results produced (ASVCP, 2013). Increasingly, veterinary facilities are purchasing POCT

machines to populate their clinical pathology profit centers; the immediacy of laboratory results

for clinically ill patients means diagnoses can be made sooner, and treatments begun more

quickly, than if clinicians were forced to wait on reference laboratory results. In emergent cases,

POCT can be the difference between life and death – but only if the results obtained are reliable

and trustworthy.

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In many facilities, credentialed veterinary technicians and nurses are tasked with

obtaining samples for evaluation in the laboratory. The same technicians/nurses, and

occasionally veterinary assistants, are usually then tasked with processing the samples for

analysis, and performing the analyses to obtain results for the veterinarian to interpret (Cox,

2012). This intimate relationship with the preanalytic phase of testing means that veterinary

paraprofessionals also have a large role to play in proper diagnoses and treatment.

Mirroring the veterinarian’s experience, there has been little formal instruction in

veterinary technician/nursing programs regarding quality assurance and control; however,

veterinary technicians/nurses (and occasionally assistants) are placed in charge of machine

maintenance and quality control procedures. How are they, then, expected to properly evaluate

the values obtained and the implications these have on diagnostic results with no training?

Implications of Findings

It seems evident that there is a need to make veterinary clinicians and veterinary

technicians/nurses more aware of preanalytic errors, and of the role that veterinary clinical

personnel play in the prevention of these errors. Readers are referred to Table 1 (sub-tables 1.1 –

1.8) in the Appendix for a list of potential preanalytic factors that could affect clinical diagnostic

specimen evaluation.

All veterinary professionals should be educated about the effects that preanalytic factors

may have on the results they obtain. For example, veterinarians are notorious for sending

lipemic, hemolyzed, or “short” samples to the laboratory for analysis, rationalizing that the

laboratory will “make do” with the sample they receive, while ignoring such preanalytic factors

such as dilution by anticoagulant, erythrocyte shrinkage due to equalizing of intracellular

osmolarity with the anticoagulant, and others that may cause false abnormalities to be reported.

23


This suggests that knowledge of the reviewed research and an understanding of how preanalytic

factors can affect the results obtained should make them more likely to implement at least

minimum QA standards.

Since 2013, credentialed veterinary technicians have had the opportunity to become

Veterinary Technician Specialists in Clinical Pathology (NAVTA, 2014). Among the skills

required to become eligible for the Academy of Veterinary Clinical Pathology Technicians’

(AVCPT) certification examination are performing quality control and quality assurance on all

testing methods used in one’s laboratory, and developing standard operating procedures for each

individual type of test performed (AVCPT, 2014). Additional topics of required knowledge

include the use of a Levy-Jennings chart to evaluate accuracy and precision, and knowledge of

commercial quality control materials for testing (AVCPT, 2013). The ASVCP suggests that

these qualified Veterinary Technician Specialists in Clinical Pathology might be ideal to employ

as in-house laboratory technicians and supervisors, and also to implement and maintain a quality

management program.

Recommendations

The ASVCP (2013) recommends that veterinary staff be adequately trained and proven

competent to perform POCT before being allowed to do so. Veterinarians and technicians/nurses

must be self-committed to quality assurance and quality control, as there is no federal regulation

of POCT in veterinary medicine. Continuing education in total quality management programs

would also be of benefit.

Based on the reviewed literature, it is the author’s recommendation that standard

operating procedures for sample collection, handling, preparation, and storage, be created and

utilized in clinics and laboratories to help reduce preanalytic errors and provide overall quality

24


assurance in preparation for analysis. Only properly trained, credentialed, and responsible

veterinary paraprofessionals should be allowed to conduct in-house sample collection,

processing, and analysis via POC equipment.

25


References

Abaxis, Inc. (2002, December 17). Good laboratory practices [PDF file]. Retrieved from

http://www.abaxis.com/sites/default/files/resource-papers/GoodLabPractices.pdf

Academy of Veterinary Clinical Pathology Technicians (AVCPT). (2016). Quality

assurance/assessment and quality control [PDF file]. Retrieved from

http://avcpt.net/yahoo_site_admin/assets/docs/Quality_Assurance_Document_.19011425

1.pdf

Academy of Veterinary Clinical Pathology Technicians (AVCPT). (2014). Skills list [PDF].

Retrieved from

http://www.avcpt.net/yahoo_site_admin/assets/docs/Skills_List_2014_updated.21912130

5.pdf

Academy of Veterinary Clinical Pathology Technicians (AVCPT). (2013). Knowledge list

[PDF]. Retrieved from

http://www.avcpt.net/yahoo_site_admin/assets/docs/Knowledge_List_2013.93152226.pd

f

American Society for Veterinary Clinical Pathology (ASVCP). (2013, May). ASVCP guidelines:

Quality assurance for point-of-care testing in veterinary medicine [PDF]. Retrieved from

http://www.asvcp.org/pubs/qas/newQas/PDF/ASVCP%20POCT%20QA%20Guideline

%20May%202013.FINAL.pdf

Braun, J-P., Bourgès-Abella, N., Geffré, A., Concordet, D., and Trumel, C. (2015). The

preanalytic phase in veterinary clinical pathology. Veterinary clinical pathology 44(1), 8-

25. DOI: 10.1111/vcp.12206

26


Carraro, P. & Plebani, M. (2007). Errors in a stat laboratory: Types and frequency 10 years later.

Clinical chemistry 53(7), 1338-1342.

Carraro, P., Zago, T., & Plebani, M. (2012). Exploring the initial steps of the testing process:

Frequency and nature of pre-preanalytic errors. Clinical chemistry 48(3), 638-642.

Cox, S. (2012). Diagnostic sampling in small animal patients. In NAVC, Proceedings of the

NAVC conference, vol. 24: Veterinary technician and practice manager (pp. 37-40).

Gainesville, FL: North American Veterinary Conference.

Hammerling, J.A. (2012). A review of medical errors in laboratory diagnostics and where we are

today. Laboratory medicine 43(2), 41-44. DOI: 10.1309/LM6ER9WJR1IHQAUY

Hooijberg, E., Leidinger, E., & Freeman, K.P. (2012). An error management system in a

veterinary clinical laboratory. Journal of veterinary diagnostic investigation 24(3). 458-

468. DOI: 10.1177/1040638712441782

National Association of Veterinary Technicians in America (NAVTA). (2014). Specialties [Web

post]. Retrieved from http://www.navta.net/?page=specialties

Plebani, M. (2014). Laboratory-associated and diagnostic errors: A neglected link. Diagnosis

1(1), 89-94. DOI: 10.1515/dx-2013-0030

Plebani, M. & Carraro, P. (1997). Mistakes in a stat laboratory: Types and frequency. Clinical

chemistry 43(8), 1348-1351.

Standard operating procedure. (n.d.). In Merriam-Webster’s online dictionary (11th ed.).

Retrieved from https://www.merriam-webster.com/dictionary/standard%20operating

%20procedure

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Walsh, D.J. (2012). It’s not just a sample, it’s a patient (part 1). In NAVC, Proceedings of the

NAVC conference, vol. 24: Veterinary technician and practice manager (pp. 129-131).

Gainesville, FL: North American Veterinary Conference.

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Appendix 1

Table 1

Preanalytic Errors Seen in the Veterinary Clinical Pathology Laboratory

TABLE 1.1GENERAL FACTORS AFFECTING SYSTEMIC ANALYTES

Patient Preparation ErrorsUnfasted sampleEffect of medication on analytes

Patient SignalmentAgeGenderReproductive StatusBreed

TABLE 1.2GENERAL ERRORS IN REFERENCE LABORATORY SUBMISSION

Improperly labeled sample vesselsMissing sample labelsMissing test request submission formsMissing samplesSample sent with another pet’s test request submission formWrong test requestedWrong type of sample submitted for test requestedIncorrect submission vessels usedSamples sent at wrong temperatureDelays in sample submissionImproper packaging resulting in leakage / breakage

TABLE 1.3PREANALYTIC FACTORS AFFECTING HISTOLOGY / HISTOPATHOLOGY RESULTS

Sample Collection Incomplete excision of desired tissue Collection of tissue from incorrect locationSample Preparation Failure to obtain clean edge before imprinting a tissue cytology slide Failure to blot excess blood before imprinting a tissue cytology slideSample Handling Freezing and thawing of tissue prior to sampling Delay in placing tissue sample into formalin Submitting “dry” samples for analysisSample Storage Improper formalin to tissue ratio

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Improper formalin fixation time Failure to change formalin when needed

TABLE 1.4PREANALYTIC FACTORS AFFECTING HEMATOLOGY, CHEMISTRY, COAGULATION,

AND BLOOD GAS ANALYSIS RESULTSSample Collection Errors

Tube filling errorsUnderfilling tubeOverfilling tubeIncorrect order of drawFilling incorrect tube for test order

Prolonged collection timeImproper vein selectionInappropriately-sized needleInappropriately-sized syringeSample hemolysis

Poor venipuncture technique / Redirecting for veinIncorrect sampling through an IVC used to run IV fluidsSample drawn from incorrect patientIncorrect sample drawn for requested testInsufficient isopropanol evaporation time prior to sample collection for coagulation panel

Sample Handling ErrorsTransferring sample through needle into vacuum collection tubePushing plunger to force sample through needle into collection tubeDelay in transferring sample from syringe to collection tubeDelay in centrifugation of a serum sampleCentrifuging too soon after sample drawDelay in removing serum from a centrifuged sampleNot shipping sample with ice pack when neededNot re-suspending cells before performing a CBCNot allowing proper time for sodium citrate to equalize with whole blood for coagulation panelNot re-suspending cells before performing coagulation panelEvaporative loss from serum samples in uncapped tubes

Sample Storage ErrorsNot refrigerating promptly when neededStoring unstained blood films under refrigerationProlonged exposure to light (may degrade certain analytes)

Sample Preparation ErrorsUsing dirty glass slides to make blood filmsUsing degraded or exhausted stains on blood filmsIncorrect blood film techniqueUsing incorrect staining technique for intended test

30

REDUCING VARIABLES AFFECTING LABORATORY RESULTS 31


TABLE 1.5PREANALYTIC FACTORS AFFECTING URINALYSIS RESULTS

Sample Collection ErrorsImproper collection, general: cage floor / tabletop / exam room floorImproper collection, urine culture: voided / catheterized sampleNot performing an US-guided cystocentesis

Sample HandlingNot allowed to return to room temperature before analysisNot analyzed within 30 minutes of collectionSterility of sample not maintained during transfer to culture submission tube

Sample StorageNot kept cool during in-clinic storageSample not sent on ice to reference laboratory for bacterial culture

Sample PreparationSediment centrifuged at wrong RPM / wrong length of timeSediment allowed to sit for extended period before wet-mountedWet mount allowed to sit in ambient room humidity for extended period

Miscellaneous ErrorsExpired urine chemistry stripsImproperly stored urine chemistry stripsImproperly calibrated refractometerDirty / scratched prism on refractometer

TABLE 1.6PREANALYTIC FACTORS AFFECTING FUNGAL SCRAPING / CULTURE RESULTSSample Collection

Collection of hair/skin scraping from incorrect area of lesionFailure to use proper collection equipmentFailure to pre-warm Woods lamp before use

Sample PreparationExcess moisture on surface of DTM agar before sample inoculationUse of incorrect clearing / staining technique for cytology

MiscellaneousImproper storage of DTM tubes / platesExpired / exhausted fungal stain

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TABLE 1.7PREANALYTIC FACTORS AFFECTING MICROBIOLOGY / CULTURE RESULTS

Sample Collection ErrorsImproper aseptic collection techniqueSample collected from incorrect site

Sample HandlingFailure to secure collected sample into aseptic/clean vessel for submissionFailure to heat-fix cytology slide for Gram’s staining

Sample StorageFailure to note indicated storage suggestions for sample submissionImproper transport medium selected

Sample PreparationThick cytology preparation made for Gram’s stainingUsing improper Gram’s staining techniqueOver-decolorizing of Gram’s stained slideUsing incorrect stain for sample examinedImproper growth medium selectedimproper isolation agar selected

Miscellaneous ErrorsUsing expired or exhausted stains

TABLE 1.8PREANALYTIC FACTORS AFFECTING CYTOLOGY RESULTS

Sample CollectionImproper preparation of area to be sampled (contamination with bacteria/yeast)Accidental blood contamination from surface vesselsSampling wrong massSampling wrong area within a massInappropriately-sized needle for fine needle biopsyInappropriately-sized syringe for FNA

Sample PreparationUsing dirty slides for preparationCytology preparation too thickUsing incorrect method to prepare the cytologyUsing improper preparation technique for the sampleHeat-fixing an exfoliative cytologyUsing incorrect staining procedureUsing degraded/exhausted stain on cytology slide

Sample StorageStoring unstained cytology slides near formalin-fixed samplesStoring unstained cytology slides under refrigeration

Miscellaneous ErrorsShipping unstained cytology slides in same package as formalin-fixed samples

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Appendix 2

Informal Survey of Veterinary Professionals Regarding Laboratory Errors

Question 1: There are three phases of laboratory sample analysis: the pre-analytic phase, the

analytic phase, and the post-analytic phase. Of these three, at which phase in the clinical

pathology process do you think the most errors occur?

a. Pre-analytic: 11b. Analytic: 0c. Post-analytic: 0

Pre-Analytic Analytic Post-Analytic0

2

4

6

8

10

12

Q1: In Which Phase of Clinical Pathology Do Most Errors Occur?

Question 1

Question 2: What do you believe are the top three errors made in the clinical pathology process?

a. Error in sample collection: 6b. Error in sample handling: 4c. Error in sample storage: 4d. Error in sample processing: 1e. Error in sample preparation: 3f. Error in sample reading: 3g. Failure to perform test: 2h. Error in test performance: 5

34


i. Error in result interpretation: 2j. Poor sample quality: 2k. Failure to label sample properly: 2l. Lack of standard operation procedures: 1m. Lack of quality controls: 1

n =

0 1 2 3 4 5 6 7

Q2 - Top 3 Clinical Pathology Errors

Lack of QC Lack of SOPs Sample Labeling Poor Sample QualityResult Interpretation Test Performance Unperformed Test Misreading SampleSample Preparation Sample Processing Sample Storage Sample HandlingSample Collection

Question 3: What effect would a standard operating procedure plan have on the clinical

pathology process?

a. Provide effective quality assurance: 1b. Minimize test performance errors: 5c. Standardize test procedures: 8d. Provide information on instrument maintenance: 1e. Provide information on reagent storage: 1f. Minimize sample handling errors: 2g. Provide test references: 1h. Increase confidence in test results: 2i. Increase test completions: 1j. Increase test accuracy: 1k. Increase test precision: 1

35


n =

0 1 2 3 4 5 6 7 8 9

Q3 - Potential Effects of Standard Operating Procedures

Increase Precision Increase Accuracy Increase Test CompletionsIncreased Confidence in Results Provide Test Reference Minimize Handling ErrorsReagent Storage Instrument Maintenance Standardize ProceduresMinimize Performance Errors Effective Quality Assurance

Question 4: What could be done to increase confidence in a result obtained by automated

laboratory equipment?

a. Create a quality assurance program: 1b. Perform in-house quality control: 7c. Develop standard operating procedures: 3d. Participate in external quality control programs: 2e. Routine equipment maintenance: 6f. Routine equipment calibration: 1g. Manual confirmation of results: 3h. Keeping equipment software up to date: 1g. Repeat test with new sample from patient:1h. Perform test correctly: 1i. Use the appropriate sample:2j. Maintain/compare result logs:1

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n =

0 1 2 3 4 5 6 7 8

Q4 - Increasing Confidence in Automated Laboratory Equipment Results

Keep Result Logs Use Appropriately Sample Perform Test CorrectlyRepeat Test Update Software Manual ConfirmationEquipment Calibration Equipment Maintenance External Quality ControlDevelop SOP In-House Quality Control Quality Assurance

Question 5: On a scale of one to five (five being highest), how important is:

5a: Quality assurance in laboratory accuracy?

a. One: b. Two:c. Three:d. Four: 2e. Five: 9

5b: Quality control in laboratory accuracy?

a. One: b. Two:c. Three: 1d. Four: e. Five: 10

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One Two Three Four Five0

2

4

6

8

10

12

Q5 - How Important are Quality Assurance and Control?

Quality Assurance Quality Control

Definitions provided:

Quality assurance: a system for ensuring a desired level of quality in the development,

production, or delivery of products and services.

Quality control: a system for verifying and maintaining a desired level of quality in an existing

product or service by careful planning, use of proper equipment, continued inspection, and

corrective action as required.

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Documents

cbenson-tsu-vt.weebly.com · Web viewClinical pathology and laboratory analysis are vital tools in every doctor of medicine’s diagnostic arsenal. Errors can occur at three points