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The Laboratory Diagnostic Process
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MarioPlebani
2
Introduction
The laboratory diagnostic process is a fundamental part of
the overall diagnostic process and the evolution of modern
medicine, from curative to predictive and preventive, relies
more and more on laboratory information for early diagnosis, identication of disease risk, prognosis, and personalization of therapies.
The conceptual model underlying the laboratory diagnostic process remains the brain-to-brain loop, i.e., the coordinated and integrated set of the various steps that make up the
overall laboratory testing cycle. In the past decades, the use
of analytical quality indicators (basically imprecision and
inaccuracy) and tools for their measurement (internal control
and external quality assurance) led to a considerable improvement in performance and a reduction in analytical errors.
However, to ensure the overall quality of laboratory information, it is necessary to extend quality control to the extraanalytical phases, identifying specic indicators and
performance criteria that enable comparison among clinical
laboratories and continuous improvement. Therefore, laboratory diagnostic process cannot disregard the pre-preanalytical quality control, starting from the appropriateness
of the request and the quality of the biological sample, and
must extend to the post-post-analytical phase, i.e., the timeliness and accuracy of the interpretation and use of the results.
The improvement of the laboratory diagnostic process
must be based on two main objectives. The rst one is the
reduction of “cognitive” errors, which include the errors that
occur essentially at the time of request and interpretation of
results, and therefore on interventions at the interface
between laboratory and clinic. The second objective is the
reduction of “system” errors, i.e., all errors in the implemen-
M. Plebani (*)
Department of Laboratory Medicine and Department of Medicine,
University of Padova, Padova, Italy
Department of Pathology, University of Texas, Medical Branch, USA
e-mail: mario.plebani@unipd.it
tation and monitoring of the various procedures and processes performed in the various phases of the analysis cycle.
The Diagnostic Process
The most recent conceptualization of the diagnosis process
has been produced by the National Academy of Medicine,
formerly known as the Institute of Medicine (IOM), which in
the document “Improving Diagnosis in Health Care” focused
attention on diagnosis for its intrinsic and obvious implications in patient care, research, and social-health policy. There
is no doubt that an accurate and timely diagnosis not only
ensures the patient the best treatment modalities and
increases the probability of positive clinical outcomes, but it
also has a positive impact on health care planning processes.
Indeed, epidemiological data that collect information on
diagnoses performed inuence many health policy decisions,
including payment and reimbursement policies, resource
allocation, and research priorities.
The conceptual model developed by the National
Academy of Medicine, and illustrated in Fig.2.1, is based on
overcoming the emphasis on classicatory and categorization schemes, given the evidence that the diagnostic process
is “a complex, patient-centered, and collaborative activity
involving information gathering and clinical reasoning with
the aim of understanding the patient’s health problem.”
According to the National Academy of Medicine committee
that prepared the document, the diagnostic process represents an adaptation of the decision-making model based on
the cyclical process of collecting, integrating, and interpreting information that leads to the establishment of a working
hypothesis. This working hypothesis (working diagnosis)
may consist of a list of potential diagnoses (differential diagnosis) or a single potential diagnosis. As the diagnostic process proceeds, the list of possible diagnoses narrows– or the
probability that the provisional diagnosis is valid increases, a
process masterfully described by Jerome Kassirer et al. as
“diagnostic modication and renement.” Traditionally, it
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
M. Ciaccio (ed.), Clinical and Laboratory Medicine Textbook, https://doi.org/10.1007/978-3-031-24958-7_2
7
8
preparation
collection
Laboratory
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M. Plebani
was at this stage that laboratory testing intervened, but the
evolution of the discipline, technologies, and medicine has
changed this traditional view. In emergency medicine, for
example, the rapid availability of laboratory information has
changed the approach to the critical patient, improving diagnostic accuracy, and overcoming, especially in cases of
coma, the impossibility of collecting the anamnesis and the
limitations of the semeiological examination. Additionally,
the evolution of medicine from curative to the one now
known by the acronym “4 P” (predictive, preventive,
participatory, and personalized) makes the laboratory test
essential to acquire information in the asymptomatic patient
and, even more, to identify risk factors in the “healthy” subject and modify the natural history of the disease. The laboratory diagnostic process, therefore, ts into this changed
context of the diagnostic process of modern medicine and, in
the era of “omics”, cannot be reductively conned to the
frame of the diagnosis in the symptomatic patient.
The diagnostic process
The patient
has a health
problem
Information
gathering
Clinical
before
interview and
anamnesis
Referral
and
consultation
Has sufficient information
been gathered?
Diagnostic
hypothesis
Physical
examination
Diagnostic
Tests
Integration and
interpretation of
information
The Laboratory Diagnostic Process
Although the document of the National Academy of Medicine
is strongly addressed to clarify the traditional diagnostic process and reduce the errors related to it, already in the introduction of the paragraph dedicated to the “diagnostic
examination,” it claries the concept previously illustrated,
namely that the diagnostic examination (laboratory, imaging,
etc.) can identify clinical conditions “before” they become
symptomatic and provide visible signs to clinical observation and physical examination. Even more interestingly, the
paper introduces with great force the brain-to-brain loop
model, initially described by George Lundberg in 1981, and
more recently reviewed by Plebani etal. in 2011. Figure2.2
shows the brain-to-brain loop in its updated version, which
presents, in addition to the physician’s brain, the brains of
the clinical laboratory and the patient, to recognize the
change that occurred in recent years and characterized by the
more relevant role assumed by the clinical laboratory and the
patient in the overall management of the laboratory test. If
the role of the laboratory has progressively expanded from
the management of the analytical phase to an ever-greater
possibility of governing the initial and nal phases of the
cycle, the change in the gure of the patient is just as relevant. The patient is increasingly informed and interested in
knowing the various aspects of the laboratory test, the usefulness of the test in providing answers to his or her health
problems and the problems related to cost (in terms of both
price and time required to access the service and obtain the
results).
Although the model was designed and developed for laboratory examination, it has absolute utility and validity for
Physician’s
brain
Prescription
Problem
explanation
to the patient
Treatment
program based
on diagnosis
Patient and
outcome
Learning from
diagnostic errors,
missed incidents,
and inaccurate and
untimely diagnoses
Fig. 2.1 The diagnostic process model according to the National
Academy of Medicine. (Copyright EDISES 2021. Reproduced with
permission)
Diagnosis
Treatment
Outcome
Interpretation
brain
Action
Patient
Sample
Reporting
Sample analysis
Sample
Physician’s
Patient
identification
Sample
transport
Fig. 2.2 The brain-to-brain loop. (Copyright EDISES 2021.
Reproduced with permission)
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9
all types of diagnostic examinations. As is well known, the
model comprises nine essential processes, namely: examination selection and request, patient identication, specimen
collection, specimen transport, specimen preparation and
subsequent analysis, reporting and interpretation of results,
and clinical action. These processes have traditionally been
grouped into the pre-, intra-, and post-analytical phases.
More recently, however, the phases have been redened and
expanded to recognize the existence of an initial phase (prepre- analytical), which occurs even before a biological sample arrives at the clinical laboratory, and a pre-analytical
phase within the laboratory and is dedicated essentially to
the preparation of the sample for analysis (intra-analytical
phase). This is followed by the post-analytical phase, which
translates into the validation of results, composition and
transmission of the report, and the nal phase (post-postanalytical), which ranges from the moment in which the clinician (and/or the health professional) receives the laboratory
information, to the moment in which it is interpreted and
used in the diagnostic-therapeutic process. The last link in
the cycle is the evaluation of the clinical and economic outcomes related to the diagnostic process, outcomes that may
fall exclusively on the individual patient and/or the
population.
The main reasons for extending the phases of the cycle,
introducing the pre- and post-post-analytical phase, are basically three.
• Recognition of one of the main domains of quality accord-
ing to IOM, namely the centrality of the patient. The prin-
ciple of patient-centeredness brings into play previous
visions centered on the organization and the different
responsibilities within the cycle. In order to ensure the
quality of the entire laboratory examination cycle, it is
necessary to remove the danger that lurks in the transition
areas of the various phases and procedures. For example,
it is evident that in the initial steps many procedures per-
formed outside the clinical laboratory are not strictly
under its control. Nevertheless, since the appropriateness
of the request, the identication of the patient and that of
the biological samples, as well as the quality of the collec-
tion and of the initial management of the samples, includ-
ing transport, have signicant repercussions on all the
residual activity, on the analytical quality and on the
global information, it is clear that the laboratory must take
charge and “govern” these processes, in close collabora-
tion with the health professionals and the clinicians who
treat the patient. The same reasoning applies to the post-
post- analytical phase, which cannot limit the responsibil-
ity of the clinical laboratory to the simple communication
of results. It is well known the importance of timeliness of
reporting and therefore of monitoring turnaround time
(TAT), interpretative comments, and communication of
critical results. It is now undisputed that there must be a
control of the timeliness of the reception of the reports
and of the quality of interpretation and use of laboratory
information.
• Technological developments, especially thanks to information technology, have made it possible to control the
processes outside the laboratory, starting with the identication of the patient and the biological samples, their
transport, up to the real-time communication of the
reports and the control of their receipt. The automation of
sample preparation, thanks to the introduction of preanalytical stations, has radically reduced the risk of errors
due to the creation and identication of aliquots, centrifugation errors, and sample addresses. These improvements,
however, have brought out the problems of incorrect
patient identication, poor quality of samples, delays in
receiving and interpreting laboratory reports.
• Studies on error in laboratory medicine have demonstrated the vulnerability of the early and late phases of
the cycle, in the face of a drastic reduction in analytical
error. Persisting in focusing only on analytical quality
indicators, typically measured by internal control and
external quality assessment, risks exposing the patient to
even more hidden and serious errors. Therefore, the need
to identify ex-analytical quality indicators that can be
used both for corrective actions and improvement within
the individual laboratory and for comparison with other
laboratories (benchmark) has emerged with increasing
strength.
Laboratory Information andDiagnostic
Reasoning
The laboratory information, which is the result of the articulated and complex set of the various phases of the cycle
described above, has the following main clinical objectives:
• Predict susceptibility to diseases
• Prevent diseases by identifying risk factors that can lead
to lifestyle changes or other types of clinical
interventions
• Diagnose diseases, preferably in the early stages where
the chances of cure are best
• Determine the prognosis at the individual patient level
• Monitor diseases, identifying the effectiveness of treatments and evaluating possible changes
• Personalize therapy to achieve better clinical outcomes,
reducing the risk of adverse events
In spite of the diversity of the abovementioned clinical
objectives, laboratory information has a common denominator: it is the result of the coordinated and integrated whole of
10
1
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M. Plebani
the various phases that make up the cycle and is not identied with the “analytical” moment alone. Indeed, the analytical quality, in addition to the intrinsic methodical aspects, is
signicantly affected by the quality of the biological sample
to be analyzed. “Good” biological samples are the necessary
premise for reliable results, while “bad” samples determine–
even with high analytical quality– clinically misleading and
“erroneous” results. However, despite the evidence that 70%
of errors in laboratory medicine occur in the pre-analytical
phase, the lack of pre-analytical, and in general extraanalytical, quality indicators have not been allowed so far to
ensure greater quality and safety to the laboratory
information.
In support of this assertion is the evidence showing that
few clinical laboratories collect in a systematic and objective
way the data on the main factors of pre-analytical nonquality, such as hemolyzed, jaundiced, coagulated samples,
with the wrong relation with the anticoagulant, etc. It should
Diagnostic
test cycle
Selection of tests
(pre-pre-analytical
phase)
Analytical
performance
(analytical phase)
Test interpretation
(post-post-analytical
phase)
Examination
and
bedside
anamnesis
are tests
2
3
4
Clinical
diagnosis
Differential
Hypothesized
Verified
Final
Therapeutic
monitoring
Patient
presentation
Therapeutic
cycle
Therapeutic
action
5
be even more emphasized that, even today, there is a high
percentage of clinical laboratories that relies on the “visual”
recognition of hemolysis (and of jaundiced and lipemic samples), compared to the possibility of using serum indices,
Fig. 2.3 The laboratory diagnostic process in the context of the
diagnostic- therapeutic cycle. (Copyright EDISES 2021. Reproduced
with permission)
which represent objective, automated indicators and do not
slow down the analytical productivity of the most widespread instruments in clinical laboratories. Moreover, the
criteria for the rejection of biological samples and the consequent operating procedures, also in terms of preventive and
corrective actions, are poorly harmonized and often left to
the will of individual operators.
Diagnostic reasoning, however, cannot disregard the evaluation and acceptance of the quality of the biological sample,
and without this premise, the quality of the laboratory information cannot be used with condence in the clinical
decision- making process.
It is therefore essential to guarantee the quality of the initial phases of the cycle, even if they are performed by health
care personnel who are not hierarchically traceable to the
responsibilities of the laboratory medicine units, strongly reproposing the concept of process responsibility, indepen-
to a dangerous dissociation between the quality required in
research activities and clinical practice.
Similarly, the undoubted improvement in analytical quality that has occurred in recent decades must not remain isolated from the post-analytical context, i.e., it must be
supplemented with better ways of interpreting and using
laboratory information. Data from the literature, and even
more from daily practice, underline the increasing difculties in the interpretation of clinical laboratory reports. The
increased complexity of laboratory tests, especially in some
diagnostic areas (autoimmunity, coagulation, allergology,
molar pathology, etc.), the insufcient training of physicians
in undergraduate and graduate courses, and the overload of
data that the clinician must manage on a daily basis are at the
basis of errors and difculties in the interpretation and use of
laboratory information.
dently of the physical locations in which the various phases
are performed. Figure2.3 shows the contribution of the laboratory diagnostic process, in its essential components, to
clinical diagnosis, therapeutic action, and again, to patient
How toImprove theLaboratory Diagnostic
Process
monitoring. It is clear from this diagram that laboratory
information is conditioned not only by analytical accuracy
but also by pre-analytical accuracy and by correct interpretation/use in the clinical context of the patient.
The importance of pre-analytical quality has been understood especially by researchers involved in the issue of biobanks and collections of biological samples aimed at
validating and developing new biomarkers, while it remains
dangerously underestimated in routine activities. This leads
A careful analysis of the laboratory test cycle and of the data
in the literature allows us to recognize two major categories
of errors: cognitive errors and system errors. Cognitive errors
include all the problems in clinical reasoning that lead to
errors in requesting the appropriate test, to poor interpretation of results, and to the insufcient synthesis of available
clinical information. Cognitive diagnostic errors can be summarized in the groups represented in Table2.1.
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Table 2.1 Possible causes of error in diagnostic reasoning
Errors in access to
care
Errors in the
information
collection process
Interpretation errors Inaccuracy or inability to interpret clinical
Errors in the
integration of
clinical information
Errors in dening
the diagnosis
Communication
errors
Errors due to delays by the patient in
recognizing symptoms and clinical signs of
the disease and/or barriers to the health
system in accessing care
Errors and/or delays in requesting appropriate
diagnostic tests
information (medical history, laboratory,
image, etc.)
Errors in the generation of diagnostic
hypotheses, inability to give due weight and
priority to the information collected in the
diagnostic process and inability to adequately
recognize clinical symptoms and signs
Inability to weigh the various clinical
information, delays in identifying the most
plausible diagnosis and in patient follow-up
Inability and delays in communicating the
explanation of the patient’s clinical problem
This type of error, therefore, has several roots: (1) insufcient preparation and training of those who prescribe and
subsequently interpret the results of the clinical laboratory;
(2) limits of scientic knowledge; (3) reduction of care time
and progressive “industrialization” of customer care activities; (4) concerns typical of defensive medicine and overload
of data and diagnostic reports; and (5) difculty in integrating laboratory data in the complex clinical context of the
patient also for the lack of knowledge of probabilistic and
Bayesian concepts.
System errors, on the other hand, include all errors that
arise from the implementation of the procedures and processes that constitute the laboratory test cycle and that can be
minimized through the development and continuous monitoring of the quality system, in particular by following the
requirements of the specic international standard for the
accreditation of clinical laboratories (ISO 15189).
There are several strategies to reduce cognitive errors in
the early phase of the cycle, beginning with more up-to-date
physician education in the various domains of laboratory
medicine and an increased focus on teaching the principles
governing appropriate testing requests. Clinical laboratory
professionals must play a role in improving this early phase
of the examination cycle and even more so in reclaiming
their responsibility at the clinical-laboratory interface.
The tools are various and range from making available “at
the point of care” tools such as LabTestOnline and other
sources of information on the meaning of the various laboratory test, to the creation of alert systems to restrict the request
for expensive and complex tests to particular clinical questions and, again, to computer blocks in case of requests for
repetition of tests before the minimum interval of biological
plausibility.
Recently, the theme of the appropriateness of the request
for diagnostic exams, and in particular of laboratory tests,
has assumed ever-increasing importance, even if focused
only on the economic cost of test requested in an “inappropriate” way. The topic of the inappropriateness of the request,
indeed, deserves an in-depth examination that involves both
the real dimension and the motivations and the clinicalmanagement consequences.
Data from the literature show that in the case of laboratory medicine is greater the underuse than the excessive
demand for tests, thus contradicting the current thinking too
often based on impressions and anecdotal evidence. In reality, the problem is complex because appropriateness, or
rather inappropriateness, can only be assessed by knowing
the clinical picture of the individual patient, given that any
diagnostic test and clinical intervention are considered
“appropriate” when the benet to health exceeds the risk to
the patient by an adequate margin. Certainly, however, there
is consensus on the denition of “inappropriate request” in
terms of requesting examinations outside any consensually
accepted form of “guidance.” In practice, this means that a
request that, even in the absence of a dened guideline, does
not take into account the presence of evidence, recommendations, and suggestions from the literature and experts is
considered inappropriate. Another problem concerns the
reasons that lead to inappropriateness. There are many reasons why laboratory tests are requested in an “inappropriate” way, among which we cannot underestimate the
problems deriving from the existence of defensive medicine, the pressure from patients, and the attempt of clinicians to overcome diagnostic uncertainty in many clinical
situations. It is important to emphasize that the problem of
the cost of inappropriateness should not be seen purely in
terms of the cost of the tests themselves, but in terms of the
impact, it has on the economy and patient outcomes. Modest
variations in the results of laboratory tests, especially if they
are requested uncritically and not addressed to a specic
clinical question, can lead, by fall, to new requests for the
same laboratory tests, but also requests for imaging tests,
other diagnostic investigations, specialist visits, and inappropriate hospitalizations. Moreover, they can determine
negative psychological fallout for patients due to the anxiety
and fear caused by what we could dene “asterisk syndrome.” Finally, the debate on inappropriateness has shifted
to the issue of overdiagnosis and overtreatment that is inherent in modern medicine. Overdiagnosis and overtreatment
represent, however, problems of modern medicine in the era
of “omics” and the attempt to overcome curative medicine
based on the recognition, often late, of clinical symptoms
and signs. The improvement of appropriateness is, therefore, a complex but equally important goal for all laboratory
medicine professionals and for the relationship with
clinicians.
12
Cholesterol: interlaboratory variability
Year
CV%
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M. Plebani
In the nal stages of the cycle, the cognitive tools that can
improve clinical reasoning– in addition to better preparation
and training of physicians– are basically the correct denition of the reference interval and, even more than the critical
difference in the case of repeated examinations over time,
interpretive comments, and communication of critical
results. In addition, the availability of expert systems and
computer databases at the point of care presents a further
approach to the problem.
Quality andOutcome Indicators
The mantra “you only improve what you measure” has
proven its truth in the case of the analytical quality of laboratory testing. There is ample evidence of improved analytical
performance in terms of imprecision and inaccuracy since
the introduction of analytical quality indicators, i.e., quality
specications, and the tools to measure them, i.e., internal
quality control and external quality assessment programs.
Figure 2.4 is emblematic in documenting the improvement in analytical error, expressed as the average coefcient
of variation (CV%) since the “discovery” of external quality
assessment as a tool for comparison among clinical laboratories and improvement of analytical performance. There is no
doubt that analytical quality still represents the core business
of the profession and that there is still room for improvement
and error reduction. However, the magnitude of analytical
error is far less than the risk to the patient of the more serious
pre-analytical errors such as misidentication of patient and
biological samples or failure to recognize issues that should
lead to sample rejection. Similarly, post-analytical errors
such as transcription errors and/or errors in units of measure
can lead to serious diagnostic errors and real risks to patient
health.
For all these reasons, the laboratory diagnostic process
cannot be based solely on analytical quality but must be
based on ensuring that all stages of the cycle are performed
23.7
25.0
20.0
15.0
10.0
5.0
0.0
Fig. 2.4 Analytical error in the determination of cholesterol: decrease
over time in the average coefcient of variation (CV%), starting from
the time of the introduction of the external quality assessment
18.5
11.1
6.4 6.2
1949 1969 1980 1983 1986 1997 2007 2011 2015
4.4 3.9 3.3 33
according to strict operating procedures. In addition, there
is the need to monitor all phases of the cycle with quality
indicators that allow for detecting non-conformities and
errors that may determine risks for the nal quality of laboratory information. The harmonization of these indicators
and the reporting system is an essential tool to make possible not only improvement actions within the individual
clinical laboratory but also the comparison and benchmarking among different laboratories. In this way, it will be possible, as already happened for the analytical quality, to
identify performance criteria (quality specications) that
can indicate the appropriate corrective actions and continuous improvement. Unlike analytical performance criteria
that, being related to measures, can be established according to the hierarchy established in the Stockholm
Conference of 1999 and updated in the Milan Conference
of 2014, extra-analytical quality specications do not target
a number, be it a percentage, an absolute number or a sigma
value, but tend to “zero defects.” Indeed, patient identication errors, like that of the transcription of analytical data,
cannot be admitted nor justied, also because of the serious
repercussions on clinical outcomes and patient safety.
However, in order to make improvement goals practical, it
is necessary to establish the current “state of the art,” i.e.,
the current level of performance that clinical laboratories
should document and continuously monitor. Similar to analytical quality specications, only the collection of numerically signicant data from an adequate number of clinical
laboratories can lead to the denition of performance criteria in the extra-analytical phase.
Currently, there is a phenomenon that has been called “the
paradox of quality indicators.” On the one hand, several
quality indicators have been identied for which a harmonization process has been agreed upon. A website has been
developed that, in addition to providing all the information
on the project of the LEPS (Laboratory Errors and Patient
Safety) working group of the International Federation of
Clinical Chemistry and Laboratory Medicine (IFCC), allows
interested laboratories to enter the data collected on the indicators and a homogeneous reporting system to compare the
data of the individual laboratory with the consensus values
obtained by all the laboratories participating in the project
(benchmark).
On the other hand, there are still very few clinical laboratories that continuously and consistently collect data on
quality indicators, especially in the pre-analytical phase.
Overcoming this paradox requires, rst, that clinical laboratory professionals understand the need to broaden the
scope of action and quality control from the analytical sphere
to all phases of the cycle. Secondly, it is necessary that scientic societies, international federations, and clinical laboratory regulatory and accreditation bodies promote the use of
quality indicators and the adoption of extra-analytical per-
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formance criteria as tools for monitoring and improving service quality.
The next step is the identication of outcome indicators
that can be used by clinical laboratories to assess the nal
quality of their daily operations and to guarantee to users
(patients and prescribers) that laboratory information is safe
and is really used appropriately in the diagnostic and therapeutic context. In other words, the brain-to-brain concept,
40years after its formulation, is now living a fundamental
moment in which it is recognized the need and the possibility
to document and monitor all phases of the cycle and measure
the clinical and economic outcomes of the laboratory test.
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Elements ofBiomedical Laboratory
https://t.me/medicina_free
Organization
GiuseppeLippi, CamillaMattiuzzi, andChiaraBovo
3
Introduction
The organization of a biomedical laboratory is complex,
multifaceted, and represents the result of a series of reforms
that over the years have determined its structure and functioning. The aim of this chapter is to provide the basic elements and legislative references to understand the
organizational context of a biomedical laboratory, the role of
different structures, and various professional proles in the
different articulations and duties.
As rationally dened by the guidelines for the reorganization of laboratory medicine services in the National Health
System (NHS), the scope of laboratory medicine, strongly
focused until a few years ago on the analytical aspect, has
expanded in favor of a more integral and holistic vision,
aimed at recognizing the contribution of disciplines from a
patient-centered perspective and, more generally, on clinical
needs. A biomedical laboratory (historically and conventionally known by the term “biomedicallaboratory”) has the fundamental task of performing investigations with chemical,
physical, or biological methods on materials from the human
body and producing analytical results accompanied by diagnostic judgments.
The basic staff of a public biomedical laboratory obviously depends on its size (volume of examinations), its location within the NHS, and its aims. Therefore, the professional
gures that work in it include a director, a team of health
managers (doctors, biologists, chemists, pharmacists, and
other graduates with a specialization that is preparatory to
G. Lippi (*)
Section of Clinical Biochemistry, University Hospital of Verona,
Verona, Italy
e-mail: giuseppe.lippi@univr.it
C. Mattiuzzi
Hospital of Rovereto, Provincial Agency for Social and Sanitary
Services (APSS), Trento, Italy
C. Bovo
Medical Direction, Hospital of Padova, Padova, Italy
employment in this specialty), assisted by a variable number
of biomedical laboratory health technicians), and auxiliary
and administrative staff. Nurses may also be present, but they
are mainly responsible for collecting biological samples.
Even though the specic description of the techniques
and purposes of the analyses are more comprehensively dealt
with in other chapters of this volume, it is convenient to formulate some generalpremises, to better understand the organization of the structure.
Sectors ofaBiomedical Laboratory
Strictly dependent on the size, location, and purpose, the
structure of a biomedical laboratory includes a series of
“diagnostic areas,” which are homogeneous and differentiated on the basis of the biological matrix or the characteristics of the analytical techniques and/or instruments.
• Classication (simplied) according to the biological
matrix:
– Serum and/or plasma area (analysis of serum and/or
lithium heparin and/or plasma ethylenediaminetetraacetic acid (EDTA) tubes and/or plasma anticoagulated with other anticoagulants)
– Hematology area (analysis of test tubes containing
EDTA as an anticoagulant)
– Coagulation area (analysis of test tubes containing
sodium citrate as an anticoagulant)
– Urine and other materials area (analysis of test tubes
and/or containers containing urine, feces, or other uids such as effusions, cerebrospinal uid, pleural uid,
peritoneal uid, pericardial uid, bile uid, etc.)
• Classication (simplied) according to the activities, ana-
lytical techniques, and/or instruments used:
– Sample acceptance area
– Clinical chemistry area
– Immunochemistry area
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
M. Ciaccio (ed.), Clinical and Laboratory Medicine Textbook, https://doi.org/10.1007/978-3-031-24958-7_3
15
16
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G. Lippi et al.
– Complete blood count (CBC) area
– Coagulation examination area
– Standard urine test area
– Protein area
– Toxicology area
– Microbiology area
– Immunohematology area
– Molecular biology and/or cytogenetics area
– Other specic areas (e.g., radioimmunology, allergol-
ogy, autoimmunity, functional testing, etc.)
The connotation of an biomedical laboratory is considerably heterogeneous. There are, indeed, facilities that include
all the described areas (or others called “multidisciplinary”),
whereas the so-called “specialized” or “small-sized” laboratories may consist of only one area or some of them. There
are, for example, laboratories that perform only coagulation
tests, as well as small laboratories that perform only a limited
panel of routine tests (e.g., clinical chemistry prole, immunochemistry, coagulation, and hematology), sending biological samples to other facilities.
The structural articulation of the different areas is
extremely heterogeneous in different laboratories and
depends on the degree of integration and automation. In particular, the organization can vary from a model of total laboratory automation (TLA), in which all (or almost all)
analyzers in the laboratory are physically connected to each
other, to a model of total compartmentalization, in which
the analyzers are all stand-alone, i.e., without any physical
connection between them. In the middle of these two
extremes coexist integration/automation solutions of variable degrees, for homogeneous analytical areas (e.g., integration of all clinical chemistry analyzers), for biological
matrix areas (e.g., all instruments using serum or heparinized plasma), or for simple convenience (e.g., integration
for lack of personnel). The intermediate solutions are generically dened as “islands” of automation, as they have functional autonomy with respect to the remaining laboratory
instrumentation (Fig.3.1). The physical connection between
the different instruments is guaranteed by chains or conveyor belts of various types and articulation, which have the
function of conveying the samples from an entry point to the
different instruments in the chain up to a terminal module
where they are stored for a limited period of time. Modules
intended for the management of pre-analytical activities can
also be part of the automation component (Fig.3.2), in particular for:
• Sample loading (input module or bulk module)
• Sample check-in (verication that the sample and test
schedule have been captured by the laboratory computer
system)
• Centrifugation (separation of serum or plasma from blood
cells)
• Uncorking (removing the stopper from the test tube)
• Aliquoting (creation of secondary aliquots from the primary sample, e.g., intended for other analysis on instruments located outside the chain)
• Recorking of the tube
• Transport chain
• Storage (refrigerators of various sizes to keep the samples
after analysis for a limited period of time)
A strong element characterizing the activity of a labora-
tory is represented by the priority with which the tests must
be performed and reported. Aware that no denition can ever
Stand-alone Automation islands Stand-alone Automation Islands
Clinical Chemistry
Clinical Chemistry
Immunochemistry
Immunochemistry
Haematology
Haematology
Coagulation
Coagulation
Fig. 3.1 Organizational solutions in laboratory medicine. (Copyright EDISES 2021. Reproduced with permission)
Clinical Chemistry
Clinical Chemistry
Haematology Haematology
Coagulation Coagulation
Immunochemistry
Immunochemistry
Total Laboratory Automation (TLA)
Clinical Chemistry
Clinical Chemistry
Haematology Haematology
Coagulation Coagulation
Immunochemistry
Immunochemistry
Flo
3 Elements ofBiomedical Laboratory Organization
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17
Fig. 3.2 Automation in
laboratory medicine.
(Copyright EDISES 2021.
Reproduced with permission)
w
Centrifugation Centrifugation
be all-encompassing, we can simplify the classication
according to the examinations performed in the regime of:
• Routine: These are examinations that usually require a
report within a few hours or even days.
• Urgency: These are examinations that require an accelerated report (1–3hours usually) on the basis of the patient’s
clinical condition (usually serious) or for organizational
reasons (the patient is in a day hospital).
• Emergency: These are typically examinations that have to
be reported in the shortest possible time (within 1hour)
due to the (extremely serious) condition of the patient.
The abovementioned priority classication of examina-
tions also reects the internal organization of a laboratory.
Indeed, there are laboratories in which the majority of routine and emergency examinations are performed using the
same instrumentation (routine–urgency integration) and
those in which routine examinations are performed on instrumentation different from that intended for emergency/
urgency examinations. This depends on many variables of a
technical and organizational nature, specic to the structure
in which the laboratory is located. For example, in large
structures (hospitals or others) where the laboratory is
located at a long distance from the critical departments
(emergency room, emergency medicine, resuscitation), it
may be functional to create a satellite laboratory that can
meet the needs of the critical departments. Another variable
may be represented by the volume of analysis performed by
the laboratory, i.e., when the number of analyses (or test
tubes) under examination is considerable, leading to the
inability to guarantee an effective priority of analysis on the
instruments for the processing of examinations required in
urgency/emergency, it may be functional to allocate a series
Samples
input
Check-in
Opening test tube
Aliquoting
Closing test tube
Clinical Chemistry
Clinical Chemistry
Immunochemistry
Immunochemistry
Protein
Chain
Storage
of dedicated analyzers for this purpose. This can obviously
generate problems of alignment of results performed in routine or in urgency/emergency, especially when the instrumentation is different. It is quite understandable how an
increase in the complexity of the system (in reference to the
presence of a large number of analyzers) involves problems
of an analytical nature for the consistent alignment of the
results generated by the different modules.
The Computer Link
In the modern conception of laboratory activity, computerization plays a fundamental role. In almost all modern laboratories, analyzers are connected to a laboratory management
system (Laboratory Information System, LIS), from which
they receive the programming related to the types of tests to
be performed on biological samples and to which they transmit the results, thus allowing a validation process at multiple
levels (technical/analytical validation, biological, etc.). This
mode of communication is conventionally known as “query
host”. Indeed, the primary samples have a positive and univocal identication by means of a barcode, which is read by
the analyzers and allows the univocal identication of every
single sample under examination. There is still the possibility of manual programming of the analyses, which is, however, limited to instruments that are not connected or
connectable to the LIS, or in undesirable circumstances in
which there are malfunctions in the computer system or its
connections. The results of the examinations, after transfer to
the LIS, are stored in a database from which they can be
extracted for the generation of laboratory reports, whether
paper or digital. Modern programs also have a series of additional modules, which allow analyzing productivity, control
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