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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Analysis of SNOMED 'bleeding' concepts &amp; terms</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Jonathan Bona</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Selja Seppälä</string-name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Werner Ceusters</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Department of Biomedical Informatics, University at Buffalo</institution>
          ,
          <addr-line>Buffalo, NY</addr-line>
          ,
          <country country="US">USA</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Department of Health Outcomes and Policy, University of Florida</institution>
          ,
          <addr-line>Gainesville, FL</addr-line>
          ,
          <country country="US">USA</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>- We present an analysis of SNOMED CT 'bleeding' concepts - those concepts with descriptions that include 'hematoma', 'hemorrhage', or 'bleeding'; or that are descended from 'Bleeding (finding)' in the Is-a hierarchy; or that have Hematomas or Hemorrhages as their associated morphology - to assess how consistently they are used in the ontology.</p>
      </abstract>
      <kwd-group>
        <kwd>SNOMED CT</kwd>
        <kwd>terminology</kwd>
        <kwd>ontology</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>INTRODUCTION</p>
      <p>SNOMED CT is increasingly used as reference terminology
to encode clinical records in electronic health record systems. In
order to realize their potential and, crucially, avoid causing
lethal mistakes, such systems must support the creation and use
of records that represent, as fully and accurately as possible, the
state of the world as it pertains to the patient’s health. So long as
they do not, clinicians and other humans using these systems
will be unable to access detailed, accurate, and up-to-date
information that may be essential to preserving patients’ health
and lives. Further, the systems themselves will be unable to
provide truly useful decision support.</p>
      <p>It is essential that SNOMED CT be properly understood by
its users and software vendors. As noted by He et al. [1], many
such users do not have the expertise required to make proper use
of the terminology. SNOMED distinguishes between concepts
described with seemingly identical terms, which may lead
nonexpert users to use the wrong concept when encoding medical
records. Other issues, such as errors in the synonyms associated
with each concept may lead to unwanted concept selection with
potentially harmful consequences. To prevent such errors it is
important to assess SNOMED’s quality and provide automated
methods to address potential terminological issues and
discrepancies with respect to the underlying logical definitions.
This work follows previous studies proposing quality review
and auditing methods of SNOMED CT’s concepts with a focus
on their descriptions. Nash [2] examined “concepts in the
Procedure hierarchy of SNOMED CT” to reveal
nonsynonymous synonyms. He et al. [1] “evaluate and
categorize aspects of concept descriptor issues across SCT from
a practical use perspective.” Bodenreider et al. [3] “apply lexical
knowledge to the analysis of biomedical terminologies, with the
aim of assessing the consistency of a terminology.” We present
the results of a preliminary analysis focused on “bleeding”
concepts – those with descriptions that include the terms
‘hemorrhage’, ‘bleeding’, and ‘hematoma’, or that are related in
the ontology to one or more key ‘bleeding’ concepts. Our goal
is to assess how consistently the descriptions composing these
terms match the logical specifications of the corresponding
concepts.</p>
      <p>II.</p>
    </sec>
    <sec id="sec-2">
      <title>SNOMED CLINICAL TERMS (SNOMED CT)</title>
      <p>SNOMED CT is a reference terminology for the clinical
domain centered around concepts [4]. As a reference
terminology, it includes machine-readable description logic
definitions of its concepts that can be used for logical inference,
for example, in decision-support systems. SNOMED concepts
are organized into a hierarchy of ‘Is-a’ relations. Each concept
is associated with one or more short textual descriptions,
including a primary description known as the Fully Specified
Name (FSN) and synonyms (SYNs). Each FSN ends with a
semantic tag in parentheses to help disambiguate it from other
concepts with similar descriptions. Many concepts are linked
through non-hierarchical associative relations such as ‘has
finding site’. For example, ‘Gastrointestinal hemorrhage
(disorder)’ has as its finding site ‘Gastrointestinal tract
structure (body structure)’, and has as its associated
morphology ‘Hemorrhage (morphologic abnormality)’.</p>
      <p>III.</p>
    </sec>
    <sec id="sec-3">
      <title>ANALYSIS</title>
      <p>We analyzed SNOMED CT concepts whose descriptions use the
terms ‘hematoma’, ‘hemorrhage’, and ‘bleeding’ to see how the
terminological use of these words and their lexical variants in
concept descriptions reflects real ontological distinctions in the
concept model. We assembled a set of SNOMED CT concepts
(“bleeding-concepts”) and terms related to bleeding, focusing
on findings and disorders, and excluding other types of concepts
(e.g. procedures). For each bleeding-concept, we also gathered
any body structure concept (descendant of ‘Body structure
(body structure)’) asserted to be its finding site, along with any
associated morphology concepts descended from ‘Hematoma
(morphologic abnormality)’ or ‘Hemorrhage (morphologic
abnormality)’. This set of concepts and terms was organized
into two tables, described below.</p>
      <p>
        The TERMS table was constructed using the SNOMED CT
Descriptions and Relationships tables, by collecting (
        <xref ref-type="bibr" rid="ref1">1</xref>
        ) all terms
for every concept that has a term with ‘bleeding’, ‘hematoma’,
or ‘hemorrhage’ as a substring; (
        <xref ref-type="bibr" rid="ref2">2</xref>
        ) all terms for all concepts that
have either ‘Hematoma (morphologic abnormality)’ or
‘Hemorrhage (morphologic abnormality)’ as their associated
morphology; and (
        <xref ref-type="bibr" rid="ref3">3</xref>
        ) all terms for all concepts that are
descendants of ‘Bleeding (finding)’ in the Is-a hierarchy.
      </p>
      <p>
        The TERMS table has a row for each of the items collected
in (
        <xref ref-type="bibr" rid="ref1">1</xref>
        ) – (
        <xref ref-type="bibr" rid="ref3">3</xref>
        ). Every entry in the table has values in columns for
the concept ID and term, as well as columns indicating whether
the concept is active, and whether the description is active.
Every row that is specifically about a description has entries for
its semantic tag, as well as information about which, if any, of
our three seed terms (‘bleeding’, ‘hematoma’, ‘hemorrhage’) –
or their variants – appears in the description. For this purpose,
we manually curated a list of variants with in-use alternative
spellings or abbreviations for our seed terms (‘hemmorhage’,
‘haemorrhage’, ‘haemmorhage’, etc.). Rows for associated
morphologies have columns for the associated morphology
concept ID, its FSN and semantic tag, and an indication of
whether it is a descendant of either ‘Hemorrhage’ or
‘Hematoma’. Rows for finding sites have the ID, FSN, and
semantic tag of the finding site concept. The CONCEPTS table,
derived from the TERMS table, has one row for each concept in
TERMS with columns for the concept ID, description, semantic
tag, concept active/inactive, and whether that concept is marked
as duplicate. It includes fields with information about which
descriptions for each concept match our seed terms or variants.
For each concept, there are associated morphology counts for
descendants of both ‘Hemorrhage’ and ‘Hematoma’, and
similar values for finding sites associated with the concept.
      </p>
      <p>RESULTS</p>
      <p>Using these tables we assessed whether the terminological
use of the words ‘hematoma’, ‘hemorrhage’, and ‘bleeding’ – or
any lexical variant thereof in SNOMED CT terms – correlates
with the ontological structure according to which the concepts
described by means of these terms are organized. To that end,
we classified the concepts into eight classes depending on which
of the three words were used, alone or in combinations, in any
description for the concept. The classes, accounting for all
possible combinations, are labeled in Table 1 as follows: N:
None; B: ‘bleeding’; T: ‘hematoma’; R: ‘hemorrhage’; BT:
‘bleeding’ and ‘hematoma’, etc.</p>
      <p>
        We also classified the concepts into four other categories
depending on whether they are asserted in SNOMED CT as
being descendants of (
        <xref ref-type="bibr" rid="ref1">1</xref>
        ) ‘Hematoma’, (
        <xref ref-type="bibr" rid="ref2">2</xref>
        ) ‘Hemorrhage’, (
        <xref ref-type="bibr" rid="ref3">3</xref>
        )
‘Bleeding’, or (
        <xref ref-type="bibr" rid="ref4">4</xref>
        ) are related to a descendant of ‘Bleeding’ by
means of any associative relation. The results in Table 1 are
restricted to those concepts whose FSNs have semantic tags
‘disorder’, ‘finding’, or ‘morphologic abnormality’.
      </p>
      <p>
        Table 1 shows that the terms ‘bleeding’ and ‘hemorrhage’,
synonyms at first sight, do not behave as such in SNOMED CT,
as they appear either in isolation or in combination in many
cases (see columns (
        <xref ref-type="bibr" rid="ref3">3</xref>
        )-No-Act/Inact and (
        <xref ref-type="bibr" rid="ref4">4</xref>
        )-Yes-Inact for B, R,
and BR). Surprisingly, many concepts in which these terms
appear are not bleedings. However, that is because the terms can
be used in negations, such as ‘gastric ulcer without bleeding’, or
in procedures that involve bleeding control, such as ‘Control of
postoperative hemorrhage of bladder (procedure)’.
      </p>
      <p>
        From Table 1, it is also clear that the term ‘hematoma’
(classes T, TR) is used in a very precise way. In only three cases
out of the 213 in which the term is used, the corresponding
concept is not a descendant of the class ‘Hematoma’. Every
concept that is a descendant of that class includes the term
‘hematoma’ in one or more of its descriptions (see column
(
        <xref ref-type="bibr" rid="ref1">1</xref>
        )Yes-Act for T and TR). Furthermore, only eight hematoma
concepts also include the term ‘hemorrhage’ in their
descriptions, including three that are not hematomas
ontologically. For instance, the concept ‘Hemorrhage into
ovary (disorder)’, a descendant of ‘Bleeding (finding)’,
includes as an active synonym ‘Ovarian hematoma’. The other
two non-hematomas with hematoma synonyms are the concepts
‘Epidural intracranial hemorrhage (disorder)’ (‘EDH
Extradural haematoma’), and ‘Retrobulbar hemorrhage
(disorder)’ (‘Retrobulbar haematoma’). In sum, this analysis
reveals discrepancies between the terminological descriptions
and the ontological structure.
      </p>
      <p>V.</p>
    </sec>
    <sec id="sec-4">
      <title>CONCLUSIONS</title>
      <p>We have collected a set of SNOMED CT concepts with
terms related to bleeding, along with information about each of
their descriptions, their placement in the concept hierarchy
relative to high-level concepts like ‘Bleeding (disorder)’ and
‘Hematoma (disorder)’, and related finding sites and
associated morphologies. A preliminary analysis provides some
insight into how these words are systematically used as parts of
descriptions, and reveals a small number of aberrations that
might contribute to the creation of misleading health record
entries. Further analysis based on this work is ongoing.</p>
      <p>TABLE I.</p>
      <p>
        CLASSIFICATION OF CONCEPTS WITH ‘HEMORRHAGE’, ‘BLEEDING’, ‘HEMATOMA’, IN THEIR DESCRIPTIONS. (ACT = ACTIVE; INACT = INACTIVE)
isa_hema (
        <xref ref-type="bibr" rid="ref1">1</xref>
        )
Class
      </p>
      <p>No</p>
      <p>
        isa_hemorr (
        <xref ref-type="bibr" rid="ref2">2</xref>
        )
205
0
0
0
0
5
0
0
0
0
0
0
      </p>
    </sec>
  </body>
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</article>