=Paper= {{Paper |id=None |storemode=property |title=Epistemology and Medical Records: an Applied Evaluation |pdfUrl=https://ceur-ws.org/Vol-938/ontobras-most2012_paper1.pdf |volume=Vol-938 |dblpUrl=https://dblp.org/rec/conf/ontobras/AlmeidaAM12 }} ==Epistemology and Medical Records: an Applied Evaluation== https://ceur-ws.org/Vol-938/ontobras-most2012_paper1.pdf

Epistemology and medical records: an applied evaluation
Maurício B. Almeida1, André Q. Andrade1, Fabrício M. Mendonça1
1
Escola de Ciência da Informação – Universidade Federal de Minas Gerais (UFMG)
Av. Antônio Carlos, 6627 - Campus Pampulha – 31.270-901 – Belo Horizonte – Brazil
mba@eci.ufmg.br, andrade.andreq@gmail.com, fabriciommendonca@gmail.com
Abstract. Medical records are crucial resources for every aspect of health-
care practice. The amount and complexity of the information they bear require
the use of automation. In this paper we propose a method for separating and
classifying the information available in medical records, drawing on Karl
Popper philosophical theories. We test this method by using descriptions of
clinical cases within the scope of a biomedical project that deals with the
human T cell lymphotropic virus. Our goal is to come up with a framework
that allows for the organization and sharing of information in knowledge
representation ontologies according to their epistemological or ontological
nature.

1. Introduction
The medical record is a complex document employed for several purposes in the
healthcare realm. Proper documentation of medical encounters is one of the physician´s
most important activities. Medical records have a myriad of uses in healthcare
processes, such as: to support patient care, to fulfill external obligations, to support
quality management [Haux, Knaup and Leiner 2007]. As a consequence of those
multiple uses, medical information is a mix of facts, impressions, measurements, rules,
and knowledge recording. A classification encompassing different kinds of information
is required in order to represent them in systems.
There are several approaches to organizing and sharing information in medicine:
information models, like HL7 [HL7 2012] and Open EHR [Garde et al. 2007];
terminologies, like MESH [Lowe and Barnett 1994]; and thesaurus, like NCI Thesaurus
[NCI 2012]. An alternative that has been widely accepted for knowledge representation
is the use of formal principles based on philosophical foundations. Under ideal
conditions, the terms in a vocabulary would be defined free of ambiguities and overlaps
in a structure called an “ontology” [Smith 2003] [Guarino 1998]. Ontologies have been
widely adopted in the medical field in order to deal with the massive information
produced in medicine [Rosse and Mejino 2003] [Rector and Rogers 2006].
Within the scope of the research on ontologies, a disseminated approach is the
so-called “realism”. In Philosophy, the term realism is widely used and controversial
[MacLeod and Rubenstein 2005], but taken as a methodology, realism is extensively
employed in biomedicine [Baker et al. 1999] [Grenon, Smith and Goldberg 2004], e. g,
as a guiding methodology for the Open Biomedical Ontologies (OBO) Foundry [Smith
et al. 2007]. Realism advocates that when scientists make claims about the types of
entities that exist in reality, they are referring to entities called universals or natural
kinds [Munn and Smith 2008]. Here, we call these claims “ontological information”.

13
Some kinds of information, which are relevant for the medical field, cannot be
properly represented following realistic guidelines. Examples are claims about the
characteristics of signs and symptoms, which we name “epistemological information”
[Bodenreider, Smith and Burgun 2004].
In previous papers [Andrade and Almeida 2011], we proposed a method for
separating and classifying information available in medical records. In this paper, we
extend this framework delving deeper on the theories of Karl Popper, namely the three
worlds and truthlikeness, in order to create an analysis framework to be employed in the
organization of the entities found in medical records. With the latter, we rely on our
proposed framework to extract information from real medical records, both ontological,
regarding those entities that can be represented as universals; and epistemological,
which is relevant for medical practice even though it cannot be represented as
universals. In addition, we rank epistemological information according to its degree of
truth, with the aim of reaching a better characterization of it in ontologies.
We have been conducting the investigation that is the object of this paper,
written within the scope of a biomedical project, specifically focused on human blood.
The goal of this biomedical project is the development of a knowledge base for
scientific and educational applications related to the human T cell lymphotropic virus
(HTLV). The basis of infection by HTLV is not well-established [Verdonck et al. 2007],
making the project a suitable scenario for an investigation of what could and couldn’t be
considered universal and to what degree a theory is close to the truth, which is carried
out in the present paper.
The remainder of this paper is organized as follows: section 2 describes the
theoretical basis of our investigation, presenting Popper´s theories. Section 3 contains
our strategies for analyzing real data and the methodological steps taken. Section 4
presents the results of the application of our framework to real medical records. Finally,
in section 5 we present a discussion and future works.

2. Background
In this section, we present the theoretical background employed as a basis for our
investigation. Section 2.1 describes, briefly, the theory of three worlds of the Karl
Popper and the section 2.2 his theory about truthlikeness and fallibilism.

2.1. Three worlds and medical reality
A useful approach combining reality, cognition and representations was proposed by
Popper in his theory of three worlds. Popper proposes a pluralist view of the universe
that recognizes at least three different but interactive worlds [Popper 1978].
According to Popper, there is a world that consists of physical bodies, such as
stones, plants and animals, which is called world 1. World 1 can be divided into the
world of non-living physical objects and the world of living things or biological objects.
There is the mental and psychological world, called world 2, which includes thoughts,
perceptions and observations, that is, the mental and psychological processes and
subjective experiences. In world 2 we can distinguish conscious experiences from
dreams, or distinguish human consciousness from animal consciousness. There is also
another world, called world 3, which includes all content of world 2 mental processes,
such as languages, scientific theories, mathematical constructions, symphonies and

14
sculptures. While a block of marble pertains to world 1, the creation by an artist of a
sculpture using this block is a manifestation in world 3. From an ontological
perspective, one can claim that world 2 and world 3 are evolutionary products of world
1.
Popper´s three worlds theory has been applied to investigations in health
information science [Bawden 2002]. In the healthcare realm, world 1 consists of entities
such as pains, wounds and bacteria, to mention but a few, all of them defined on the side
of the patient [Ceusters and Smith 2010] [Smith et al 2006]. In world 2 one can find the
cognitive representations of world 1, such as observations, interpretations and beliefs,
defined both on the side of patients and physicians. World 3 is composed of
concretizations of world 2 cognitive representations in diverse information artifacts, for
example, terminologies, categorical systems and medical records. Moreover, diagnoses
in physicians´ minds (world 2) and electronic health record entries (world 3) are related
to disorders and diseases (world 1) through the relation of aboutness [Schulz and
Karlsson 2011].
While Popper´s ontological view allows one to better understand the relation
between entities pertaining to the world, his epistemological view proposes that every
conceptualization reveals mismatches between reality and theories about reality.
Though Popper’s theories have been criticized [Bawden 2002], there are favorable
views in which they are considered a useful model for understanding epistemological
information [Abbott 2004]. Accordingly, one can find additions and improvements to
Popper´s views, which propose additional sub-divisions of the original layers
[Niiniluoto 1999] [Bhaskar 1978] or further subdivision of levels of reality into a
material stratum, psychological stratum and social stratum [Poli 2010].

2.2. Fallibilism and truthlikeness
In addition to the three world’s theory, Popper is also known for his falsifiability
criterion and for his advocacy of fallibilism. According to the falsifiability criterion,
scientific hypotheses are falsifiable and, therefore, scientists are able to state what
empirical findings make such hypotheses false. Fallibilism is the view that no presumed
knowledge, not even scientific knowledge, is absolute certain.
In this line of thought, epistemological searches are fallible. As human
knowledge is incomplete, probable, and conjectural, one should seek truth but expect
truthlikeness. Truthlikeness is a qualitative measure of how a theory can be more or less
close to truth [Bhaskar 1978]. For example, consider these three statements in a
healthcare situation: i) there are four blood groups plus a Rh factor; ii) there are four
blood groups; iii) all blood has the same chemical composition. If the first assertion is
true, then intuitively the second assertion has higher degree truthlikeness and
approximates truth better than the third.
The medical practice is still heavily grounded in the study of signs and
symptoms, which are interpreted by a physician. Medical reasoning is a sum of different
cognitive practices including induction, abduction and deduction [Pottier and Planchon
2011]. In such context, in which no definitive account of truth can be reached in some
cases, the notion of fallible theories being constructed from medical records is aligned
with the need to search for universals.

15
3. Methodology
In order to develop better possibilities for medical record representation, we need to
organize the kinds of information they contain. The method we propose here is
composed of the following four steps.
First, we develop an analysis framework, which draws on inputs from Popper´s
three worlds and we also researched by recent medical ontologies, namely, the Basic
Formal Ontology (BFO) [Grenon, Smith and Goldberg 2004] as upper-level ontology to
organize universals, the Ontology of General Medical Science (OGMS) [Scheuermann,
Ceusters and Smith 2009] and the Information Artifact Ontology (IAO) [IAO 2012].
These ontologies were chosen because the project in which the present investigation is
inserted is based on the top-level ontology BFO. It is also the ontology that provides
grounds for IAO and OGMS.
As a second step, we are testing such framework on real medical records under
evaluation in a biomedical project about blood diseases [Almeida, Proietti and Smith
2011]. In this paper, we will present as an example a clinical case description, which is
considerably clearer than real medical records, while still requiring proper
representation of the full range of medical entities. We use a generic clinical case
available at Connors and Britton (2009) as a test-bed for our methodology.
In order to identify propositions within the clinical case, a domain expert
transcribed the records into sentential fragments that make sense to him. The domain
expert was asked to identify the reason for recording those entities and the information
that is being conveyed by the representation. The transcription draws upon principles of
logic and controlled languages [Fuchs et al. 2005], which allowed the identification of
entities recorded in natural language, outside of the particular context in which the event
took place. In addition, on the classification side, we use the rationale underpinning
OGMS. This rationale is adopted to model the domain. It describes a disease as a
disposition [Scheuermann, Ceusters and Smith, 2009], in which the three major stages
are: etiological process, course of disease and therapeutic response. On the logical side,
we took into account the fact that some parts of speech in natural language have no clear
representation in logical statements.
As a third step, we consider an alternative for measuring truthlikeness, in order
to classify epistemological information that came from the selected records. We took
the position that epistemological information relevant in the context of medical practice
cannot be registered in an ontology as a universal, following the tenets of the adopted
realistic methodology [Grenon, Smith and Goldberg 2004]. It should then be registered
in the form of annotations and classified according to a degree of truthlikeness. As
truthlikeness is a comparative notion, we define situations which are considered true
according to the current knowledge of the virus. Indeed, knowledge about the
pathogenesis of infection by HTLV is fairly recent, even though this virus is endemic in
several regions of the world. Genetic and immunological factors are in general the cause
of the associated clinical manifestations, which may be divided into three categories:
neoplastic, inflammatory and infectious [Romanelli, Caramelli and Proietti 2010]. In
this step, we focus on extracting the epistemological information required to make
correlations between the virus and the etiological suspects in their diverse clinical
manifestations.

16
Finally, as fourth step, we organize the information from the medical records
into four types, which are then employed in order to recommend both a data
arrangement and a scenario for collaboration among different representations.

4. Results
In this section, we present the analysis framework created to organize information
present in a medical record (section 4.1) and, in the section 4.2, we conduct a
preliminary test of the framework by analyzing individual information entities contained
in examples of the medical records.

4.1. Analysis Framework
We propose the analysis framework depicted in Fig. 1, which was created to organize
information present in a medical record according to the best possibility for
representation. This framework is divided into two sub-frameworks, the first one
organizing the kinds of general information present in a medical record based on the
three world’s theory (slightly modified from Andrade and Almeida (2011) and Almeida
and Andrade (2011) – a brief explanation is given for clarity); the second organizing
epistemological information based on truthlikeness.

Figure 1. Framework used for analysis.
In this framework, everything begins at the level of cognitive representations
when a physician observes the reality at the patient side (arrow 1). Each of these entities
are filtered by cognition and represented by artifacts (arrow 2). Ontological entities
(entities O) are analyzed according to strict philosophical tenets, and are based on
reality itself rather than on physician´s mental representations. Examples of ontological
entities are cells, anatomical features and chemical substances. These entities are
directly considered in world 1 because in the realistic methodology adopted here
[Grenon, Smith and Goldberg 2004] things exist in reality independently of any human
beliefs. World 1 is the world of every thing that exists, observable or not.
Epistemological entities are recorded in annotations (entities A). They stand for
cognitive representations of reality, and may include entities without a referent in
reality. Examples of these include “severity” of a pain and a sensation of “feeling well”.
Then, the physician creates a record (entity I) to register those representations according
to their practical and theoretical knowledge (arrow 3).
Other physicians can constantly interpret records and reality (arrows 4),
resulting in new cognitive representations. Finally, the physicians involved in healthcare

17
make judgments and process past and current information. Some of this processing of
information (arrow 5) follows medical training rules, which determine the likelihood of
a diagnosis and the correct interpretation of an exam result, to mention but a few. The
representation of this reasoning process is also required for care continuation, which is a
complementary part of the record (entity R). Examples of this include rules for
interpreting lab data, as hemoglobin level < 12 g/dl means “low hemoglobin level”; and
relevant negative information such as “lack of bowel alteration during episodes”.
When performing this sort of analysis, we distinguish ontological information
from epistemological information, the latter represented as entities in Popper´s world 3,
which is equivalent in Fig. 1 to the concretizations of cognitive representations level.
Within this sub-framework we recognize at least four kinds of information to be
separated according to their suitability for information systems: i) information that
represents aspects of reality; ii) information that represents useful constructs for the
medical practice that are not empirically verifiable; iii) information that represents
observations about the reality, not the reality itself; iv) information that represents
observations about the physician´s understanding of the clinical situation, not about the
reality.
According to the aforementioned approach, only information that represents
aspects of reality can be properly represented by universals. The other three sorts
identified are epistemological information. It´s worth mentioning the link between
belonging to one of the three worlds and the degree of truthlikeness. The information
that pertains to worlds 2 and 3 is epistemological information and it will be classified
according to a degree of truthlikeness. We don´t use the notion of truthlikeness to deal
with ontological information pertaining to world 1.
It is clear that (ii) and (iii) are closely related to reality, with (ii) being a surrogate for a
defined state of things on the side of the patient, and (iii) an objective account of its
measures. Relations that allow for proper interpretation of those statements are
particular to each domain. For instance, the examination of the color of the sclera may
indicate jaundice (yellow color, surrogate for liver problems) or anemia (blue color,
surrogate for iron deficiency anemia). The interpretation of what such signs mean
depends on training, cultural practices and subjective characteristics. There are also
specific relationships with regard to lab tests, since statements like “the total bilirubin
level in the blood of patient X is high” requires knowledge of the method of sampling
and analysis, knowledge of the probabilistic distribution of bilirubin concentration in the
normal population, consideration of measurement errors and confusion factors and
understanding of the meaning of measurement units. The last category (iv) requires
more attention, since medical reasoning practices include both ontological relations and
ad hoc heuristic rules that are not guaranteed to hold true in the world. We consider that
the information in (iv) will eventually be registered in medical records as part of a
learning process.
Our proposal also includes a way of characterizing epistemological information
based on its likeness to the truth. Following semantic approaches distinct from Popper´s
account, such as Volpe (1995), Tichý (1978), Hilpinen (1976), we consider sentences
extracted from the medical records. The semantic contents of such sentences are
propositions that can be true or false.

18
In this sense, a simple propositional framework with three primitives (h, r, w)
and the correspondent logical spaces are depicted in Fig. 2 as an example. The sentences
from the associated propositional language are taken to express propositions within
these logical spaces. This framework can be useful for characterizing information and
scientific findings around a virus that has been studied only in the last few years, such
as HTLV.

Figure 2. Three propositions generate eight levels numbered w1 to w8.

4.2. Testing the Framework
Here we conduct a preliminary test of the framework by analyzing individual
information entities contained in medical records. As an example, we present a small
extract of the clinical case available at Connors and Britton (2009), due to clarity and
completeness of this case, and due to explicit description of reasoning processes.
After we obtain a sentential fragment from an evaluation by a domain expert, we
then isolate what could be represented in realism-based ontologies following the
rationale of the BFO, OGMS and IAO. After that, we arrange the information according
to the sub-frameworks mentioned in section 4.1. The final results systematize the
information contained in a medical record based on either their ontological or
epistemological nature. To the second kind, that of an epistemological nature, we add a
classification based on the level of truth.
“A 62-year-old woman presented to the urgent care clinic with gingival bleeding
after periodontal scaling of her lower-right second molar. She had undergone the
procedure 5 hours before presentation, and the bleeding has persisted despite the
application of pressure and ice. [...]
The patient recalled a similar episode that had occurred 6 months earlier, also after a
periodontal procedure, in which bleeding had stopped only after firm pressure had
been applied and held for 6 hours. [...]
She was otherwise in her usual state of good health. She reported no easy bruising,
epistaxis, rectal bleeding, hematuria, weakness, fatigue, arthralgia, dyspnea,
jaundice, abdominal pain, back pain, rash, confusion...” [Connors and Britton 2009]
In the Fig. 3, hereafter, we present samples of data obtained from the medical
record in Fig. 4 and classified it according to the kinds proposed in section 3.
Data representing Data that represent Data that represents Data that represents
aspects of the useful constructs for observations about the observations about the
reality the medical practice reality physicians understanding
Physician Woman State of good health Heart rate: 80 bpm Patient class: "Emergency
patient"
62 years-old Former smoker Blood pressure: 128/76 Bleeding had persisted
mmHg despite the application of
pressure and ice
Patient report No prior episodes of White-cell count = 6,200 Bleeding had stopped only

19
unpredictable after firm pressure had
bleeding been applied and held for 6
hours
Time of bleeding No allergies Lymphocytes = 37 …
Time between … Platelet-count = 352,000 The timing of bleeding
episodes after vascular trauma is
different
Aspirin … Creatinine = 1.4 The patients presentation
suggests platelet disorder
Aspirin taken daily … Albumin = 3.9 …
(rule)
Thiazide diuretic … Prothrombin time = 13 Patient class: "Emergency
sec patient"
Physical exam … … Bleeding had persisted
finding of that despite the application of
encounter pressure and ice
Figure 3: Four kinds of information extracted of an example of a medical history.

This data classification was based on both the levels of representation provided
in section 4.1. From the empirical assessment by physicians, the categories suggested in
figure 3 were created. The relation between the proposed framework and the
organization of data from medical records can be summarized as follows:
a) “Data representing aspects of reality” (column 1) were mapped from processes
(1) and (2) to entities (O) (Fig. 1) - only this information that can be directly
used to populate realist ontologies, since terms in ontologies refer to universals;
b) “Data that represent useful constructs for the medical practice” (column 2)
were mapped from the process (1) and (2) to entities (A) (Fig. 1);
c) “Data that represents observations about the reality” (column 3) were mapped
from process (3) to entities (I) (Fig. 1);
d) “Data that represents observations about the physicians understanding”
(column 4) were from processes (4) mapped to entities (R) (Fig. 1).
Already the information classified in (b), (c) and (d) can to be use to support the
building sets of sentence. For both, we define a set of true sentences about a blood
disease following the orientation of experts. In context of the existence of the HTLV
virus in a patient, a set of related sentences would be: i) HTLV cause neoplastic
manifestation on human being infected by it, which we call proposition n; ii) HTLV
cause inflammatory manifestation on human being infected by it, which we call
proposition f; iii) HTLV cause infectious manifestation on human being infected by it,
which we call proposition i. We can then consider that, in context of HTLV prevention
and treatment, in a patient infected with the virus that presents both a neoplastic, an
inflammatory and an infectious manifestation, those manifestations were cause by the
HTLV virus. This complex situation is considered a true equivalent to the actual world
we name w1. Table 1 depicts combinations of propositions ranging from w2 to w8,
according to the relative closeness to the truth.
Table 1. Logical spaces for the presence of HTLV virus.
neoplasic inflammatory infectious
actual world = w1
manifestation manifestation manifestation
w1 n f i
w2 n f ~i
w3 n ~f i

20
w4 ~n ~f ~i
w5 ~n f i
w6 ~n f ~i
w7 ~n ~f i
w8 ~n ~f ~i
The truthlikeness gives us an objective criteria to evaluate the consequences of
inclusion of such rules of thumb (weakness in HTLV infection is a neurologic
complication) will behave in ontologies. Using this general rationale we can create “n”
systems of spheres representing the situation considered real and other situations
standing a logical distance from the actual world that is the truth (Fig. 4).

Figure 4. Logical spaces corresponding to different sets of conjunctions.

5. Discussion and future works
In this paper we presented a framework that aims to clarify the distinctions between
reality, medical understanding and the recording of it, while maintaining the medical
record as the main information source. Besides, we propose a way of dealing with
epistemological information based on the notion of truthlikeness.
It is now well established that ontologies are an important resource to explicitly
define the meaning of terms, especially when coupled with advances in description
logics. Description logic is a powerful logic for describing the world, but is susceptible
to inconsistencies, particularly when dealing with instance data. We advocate that realist
ontologies provide a robust way of representing entities in reality, ensuring
interoperability and safe inferences. This is possible because epistemological
information, which can cause inconsistencies in inference processes, is not used in the
ontology. Interoperabiliy is favored by the use of the top-level ontology which is the
basis of the methodology adopted in this paper [Grenon, Smith and Goldberg 2004].
However, as we have shown, many entities in medical records do not have a
referent in the world, being representations of epistemological evaluations by physicians
and patient or measurements about real world entities. Ontologies, as pointed by Schulz
in Brochhausen et al. (2011) are not “Swiss army knives for knowledge representation”
and are unable to represent every single bit of knowledge required for correct
interpretation of assertions. Our framework intends to make clearer which kinds of
instance shouldn’t be used in logical inferences, as robustness is not guaranteed. For
instance, “unpredictable bleeding” is an important construct for hematologist
evaluation, but a bleeding process doesn’t change its way of being if someone claims it
could be predicted.

21
Popper’s theories provide a useful perspective on the different levels of reality
and the relationship between theories (the ontology artifact being one of these theories)
and reality per se. Our treatment of epistemological information seems to be an
alternative to dealing with uncertainty common in the medical practice, from a logical
point of view. Popper´s initiative in this regard, while essentially syntactic, entails the
idea that no false theory is closer to the truth than any other. Other authors [Hilpinen
1976] [Volpe 1995] follow a semantic-oriented approach in looking for a plausible
theory of distance between the semantic content of sentences. We believe that this latter
approach fits well to the needs of a still-evolving subject that has to be captured in
ontologies.
The proposed method has been tested in sentences obtained from real medical
records, but the partial results have suggested the need for refinement. The test
presented in this paper deals with a very small number of sentences and the feasibility
of the approach has to be tested in more complex situations. The possibility of dealing
with more complex cases is presented, for example, in Hintikka (1963). However, as a
qualitative measure, truthlikeness can work as a kind of secondary metric which helps to
make sense of the large amount of information in medical records.
In future works, we intend to create clear rules for dividing kinds of information
in a semi-automatic fashion. It will then be possible to test our approach against a
greater sample. In doing so, we aim to explore the best characteristics of different
systems and which representations suitable for each sort of system.

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