=Paper=
{{Paper
|id=Vol-1747/IT603_ICBO2016
|storemode=property
|title=Improving the Semantics of Drug Prescriptions with a Realist Ontology
|pdfUrl=https://ceur-ws.org/Vol-1747/IT603_ICBO2016.pdf
|volume=Vol-1747
|authors=Jean-Francois Ethier,Ryeyan Taseen,Luc Lavoie,Adrien Barton
|dblpUrl=https://dblp.org/rec/conf/icbo/EthierTLB16
}}
==Improving the Semantics of Drug Prescriptions with a Realist Ontology ==
Improving the Semantics of Drug Prescriptions with a
Realist Ontology
Jean-Francois Ethier, Ryeyan Taseen, Luc Lavoie and Adrien Barton
Département de Médecine & Département d’Informatique
Université de Sherbrooke
Corresponding authors: ethierj@gmail.com, ryeyan.taseen@usherbrooke.ca, adrien.barton@gmail.com
Sherbrooke, Canada
Abstract—Electronic prescriptions are supported as a means In recent years, open source, applied ontologies have
to reduce adverse drug events, but the ambiguities and emerged as a reliable solution to the Tower of Babel problem
overspecificities of prescription semantics along with their lack of in medical informatics [12] as exemplified by ontologies in the
standardization reduce adoption, limit interoperability and are consortium of the Open Biomedical Ontologies (OBO). As a
potential sources of error. Ontologies in the OBO Foundry, whole, OBO aims to prospectively standardize biomedical data
founded on realist methodology, have been successful in fostering by using a shared, tested set of best practices in the building of
the logical, scientifically accurate data standards that the domain ontologies. Each ontology aims at providing a logical,
of drug prescriptions is currently in need of. This paper scientifically accurate and orthogonal representation of each
illustrates some problems regarding the structuration of current
domain [13]. Currently, the OBO Foundry includes ontologies
electronic prescriptions, and demonstrates how the Prescription
for the domains of drug products (DRON: the drug ontology)
of Drugs Ontology (PDRO) addresses these issues with improved
semantics founded on OBO and realist principles. PDRO reuses [14], adverse events (OAE: Ontology of adverse events) [1],
classes and object properties from IAO, OBI, OGMS, OMRSE and potential drug-drug interactions (DIDEO: Drug Interaction
and DRON, introducing new entities within its scope and and Evidence Ontology) [15], but a realist ontology for drug
proposing entities within those of its imported domains that may prescriptions is still missing.
be useful to other health care and information artifact-related Such an ontology could help standardize a key source of
ontologies in the OBO Foundry. PDRO aims at improving the
data for the potential clinical applications that motivated the
semantics of drug prescriptions and prospectively enabling the
afore-mentioned ontologies. Conversely, the adoption of a data
interoperability of prescription data.
standard that is within the fold of the OBO Foundry would
Keywords—Prescription; e-Prescribing; Drug product; Dosing facilitate the development of cross-domain health care
Instructions; Ontological Realism; Informational Entity; Deontic applications, such as those for detecting inappropriate
Entity; OBO Foundry prescriptions by comparing electronic prescriptions against
diagnosis data, demographic data, lab data, and drug-drug
interaction data.
I. BACKGROUND
Modern health care extensively uses pharmaceutical drugs. This paper will introduce a realist ontology for the
But while the administration of a drug can mitigate, prevent, prescription of drugs, the Prescription of Drugs Ontology
treat and cure disease, it can also cause unintended harm. (PDRO: pronounced ‘Pedro’), which is available online and
Adverse drug events 1 (ADE) cause about 5% of all hospital open for discussion at https://www.github.com/openLHS/
admissions [3], [4] and are estimated to be the 4th to 6th leading PDRO. A first part of the article will describe certain
cause of death in the US [4], [5]. challenges in the representation of drug prescriptions based on
problems with current implementations of e-prescribing
Prescription errors that can result in ADE are a compelling platforms. A second part will present the methodology that was
target of patient safety improvement due to their susceptibility adopted. A third part will expose how the PDRO ontology
to interception by health IT systems [6]. There is evidence of addresses those requirements. And finally, a fourth part will
benefit in the use of electronic prescriptions for detecting conclude the article.
inappropriate prescriptions and thereby reducing the incidence
of ADE [7]–[9], but important challenges remain in the II. CHALLENGES
implementation and adoption of these systems. Among the
most frequently cited of these issues is the lack of data A. Levels of generality in drug product specifications
standardization [10]. This reduces system quality, hinders
adoption and limits interoperability [11]. Consider two prescriptions2 for metoprolol:
DAS1 = ‘Metoprolol 50 mg PO bid’
DAS2 = ‘Apo-Metoprolol 50 mg tab, 1 tab PO bid’
1
An adverse drug event is a pathological bodily process that occurs after a
2
drug administration and results in unintended harm to the patient [1], [2, p. More specifically, DAS1 and DAS2 are parts of a prescription specifying the
37]. We use this term in preference to ‘adverse drug reaction’, which has administration of a drug, that we will later call Drug administration
more variable definitions in drug safety literature [2, p. 38]. specification – see IV.A.
Certain e-prescribing platforms can only prescribe a NCPDP [19] and in the province-wide electronic prescribing
uniquely registered drug (e.g., Apo-Metoprolol3 50 mg tab) as system implemented in Quebec, Canada [16]. Electronic
in DAS2, which artificially restricts the collection of drugs that prescribing systems accommodate this inadequacy by allowing
satisfy the intention of the prescriber (e.g., any drug product free-text instructions, however there is often a discrepancy
containing the active ingredient metoprolol and suitable for an between these instructions (assumed to comprise the
administration by mouth of 50 mg of active ingredient at a prescriber’s actual intent) and their structured counterparts (the
time) [16]. This inability of the prescriber to specify a drug at formalization of that intent) [24]. This reduces the validating
different levels of generality poses several problems for ability of CPOE systems, and could potentially result in ADE
different users. For the pharmacist, it means having to contact [25], [26].
the prescriber and/or modify the prescription when the drug
that was specified is not in stock or when it does not match We will now present the OBO Foundry methodology used
patient insurance claims. This reduces efficiency and increases by our ontology of drug prescriptions, PDRO, in order to
the risk of error [11], [17], [18]. For prescribers, it is frustrating address the above-mentioned issues.
to have to deal with the mismatch between the initial
prescription and what appears on the prescription returned III. METHODS
from the pharmacy, since there may not be any resemblance PDRO uses BFO 2.0 as a top ontology and classes from
between the written names of the drug product specified and IAO, OBI, DRON, OMRSE and VO were imported. 167
the drug product dispensed [16]. For the patient, if the classes were created and classified in accordance with these
medication that is prescribed is not covered by their insurance, ontologies as per the OBO principle of orthogonality [13].
it can increase out-of-pocket costs [18]. BFO makes the distinction between Independent continuant,
To address these issues, a representation of drug which encompasses e.g. Material object – like an aspirin 81mg
prescriptions should formalize the specification of a drug tablet; Occurrent, which encompasses e.g. Process – like the
product such that the informational entity referring to the process of Mr. Martin taking aspirin 81 mg once a day for the
collection of drug products acceptable to dispense and rest of his life; and Dependent continuant, which encompasses
administer on a prescription can be as general (or as specific) e.g. Quality – like the shape of an aspirin 81 mg tablet.
as the prescriber’s intention. IAO:Information content entity (abbreviated “ICE”) is a
subclass of BFO:Dependent continuant4 and has the property
B. Homonymy of being about something – for example, the ICE ‘aspirin’ on a
drug product monograph is about the class of aspirin drug
Modelling informational entities that are commonly viewed products [27]. PDRO classifies Prescription5 as a subclass of
as chains of characters, such as prescriptions, requires IAO:Document, defined as an ICE intended to be understood
distinguishing between homonyms: strings that are identical in as a whole.
their composition and order of characters, but have different
meanings. For example, “Metoprolol” in DAS1 would usually Following [27], an ICE can be concretized by some
refer to any drug product containing metoprolol, although in BFO:Quality; for example, a prescription can be concretized by
some cases it might refer to the generic drug product branded the outline of a string of characters on a sheet of paper, by
with the name ‘Metoprolol’ [19]. some pixels on a computer screen or even by some neuronal
configuration inhering in the doctor or the patient. In the
Thus, a representation of drug prescriptions must not only following, when we speak of e.g. the entity 'Amoxicillin'6, we
consider the nominal value of the chains of characters that a refer to an ICE that can be concretized by the string of
prescription may be composed of, but must consider the characters “Amoxicillin” (whereas the class Amoxicillin is a
intention behind them, that is, what these chains of characters subclass of DRON:Active ingredient, subclass of
might refer to. BFO:Independent continuant).
C. Human & Machine Readable Dosing Instructions PDRO focuses on describing various parts of a Drug
prescription, such as Drug administration specification (e.g.
Instructions for administering a drug (e.g. ‘1 tab PO bid’ in ‘Amoxicillin 500 mg PO tid’) or Drug product specification
DAS2), are traditionally termed the “Sig.” (for “signatura”) (e.g. ‘Amoxicillin’). We use the relations BFO:has_part and
[19]. We will refer to this as “dosing instructions”. The BFO:part_of to describe mereological associations between
importance of unambiguous information in this part of a universals that hold for all their instances.
prescription is demonstrated by the medication errors and
adverse drug events that result from unclear dosing instructions
on drug product labeling [20], [21, Ch. 5], [22], [23].
Despite their key role in influencing patient outcomes, 4
More specifically, it is a BFO:Generically dependent continuant: it can
dosing instructions are inadequately captured in electronic migrate from one bearer to another. For example, a prescription can first
prescriptions, including in e-prescribing standards by the inhere in the brain of a doctor, then in the screen of a computer, and finally in
a printed paper.
5
In the following, whenever the ontology name is omitted in an entity name,
3
This is a generic drug brand name. Note that non-generic drugs are often this means that the entity is introduced by PDRO - so we will write e.g.
referred to as “brand name drugs”, yet what is referred to as a “generic drug” “Prescription” instead of “PDRO:Prescription”.
6
is also branded by its production company. We will use single quotes to refer to an ICE.
IV. RESULTS DAS1 also has as part an instance of Dose administration
specification written ‘50 mg PO bid’, which has parts that
A. Drug administration specification as a Normative specify that ‘50 mg’ should be the quantity in a dose (Dose
specification quantification specification) and that ‘PO’ should be the route
While medical prescriptions can have many uses, e.g. of administration (Route of administration specification). The
physiotherapy, we differentiate a Drug prescription as a type part ‘bid’ informs when a dose should be taken; this is covered
of Prescription that has as part a Drug administration in section D.
specification (abbreviated “DAS”) that specifies how to realize The ‘50 mg’ that appears in DAS2, on the other hand,
the administration of a drug. An ontology of the records specifies the strength of the drug product intended by the
pertaining to the dispensing of a drug and the administration of prescriber, i.e., that 50 mg of active ingredient should be
a drug would classify such records under Data item, as they are contained in one pill – and not split, for example, between two
intended to be truthful statements about a process. In contrast, a pills of 25 mg each. Accordingly, it is part of ‘50 mg tab’, an
DAS cannot be considered to be a truthful statement, as it is instance of Drug strength specification, which is a part of the
intended to indicate how to realize a process, which might not Drug product specification, along with ‘Apo-Metoprolol’. The
occur, in case, for example, the patient is not compliant. Dose administration specification in DAS2 is ‘1 tab PO’, where
Therefore, DAS is classified under OBI:Directive information ‘1 tab’ specifies the quantity in a dose and is therefore an
entity (abbreviated “DIE”) which is an ICE that intends to instance of Dose quantification specification.
direct some process realized7 by some agent(s). For example, a
recipe for chocolate cake is a DIE that directs the process of C. Process of drug administration vs. dose administration
making a chocolate cake by following the instructions
described in this recipe. The administration of a drug aims at fulfilling some health-
related objective such as curing a disease, alleviating a
In modern health care systems there is a background symptom, preventing a disease, etc. In order to fulfill this
prohibition to take any prescribed drug unless explicitly objective, a drug is often administered in several individual
permitted by a prescription. A DAS specifies instructions that doses that will be taken over some period of time. Accordingly,
imply permissions8 overriding this background prohibition. For the administration process of a drug involves two related
example, it may instruct the patient to take nitroglycerine if processual entities: A Dose administration such as the
feeling chest pain, or to take an antibiotic if a certain time has administration of 500 mg of Amoxicillin on February 24th,
elapsed since the previous dose. The nature of entities such as 2016 at 1 PM; and a Drug administration, which is a
permissions has been investigated elsewhere [28], [29]. PDRO mereological sum of one or several instances of Dose
focuses instead on investigating the ontology of DAS, which administration, such as the administration of 500mg of
specify such norms (and DAS is therefore formalized as a Amoxicillin three times a day during 7 days, starting on
subclass of Normative specification 9 , defined as a DIE February 19th, 2016.
specifying such norms).
D. Drug administration and dose administration
B. Drug product specification and dose administration specifications
specification We will now analyze the ontological nature of normative
Each DAS has as part one Drug product specification and specifications in prescriptions, which create permissions that
at least one Dose administration specification: the former override the background prohibition mentioned above [31]. A
specifies the collection of drug product(s) that can be DAS specifies both the condition(s) for permitting a Drug
dispensed and administered, and the latter directs the administration, and the condition(s) for permitting the Dose
administration of a dose. administration(s) of that Drug administration. Consider the
informational parts of the following DAS (Fig. 1):
In DAS1, the chain of characters “Metoprolol” specifies a
class of drug products, namely those who contain the active DAS3: ‘Amoxicillin 500 mg PO q8h start PRN if symptoms
ingredient metoprolol, thus it is a Drug product specification. of bronchitis x 7 days’
7
In common language, DAS3 allows the patient to start a
There are different views about the nature of this connection between a DIE
and a process it directs. See OBI’s definition and Smith & Ceusters (2015)
treatment of Amoxicillin, 500 mg by mouth (‘PO’) in case of
[27] for various positions on what can be concretizations of DIEs and ICEs. symptoms of bronchitis. If the patient decides to start such a
We do not take a stance on this issue. treatment, he or she should continue the treatment for 7 days,
8
The nature of the instructions specified by a DAS can be a matter of debate. and 500 mg of Amoxicillin should be taken every 8 hours
Some of these instructions might be seen as a suggestion, while others might (‘q8h’).
be seen as an obligation. Such an obligation could be ethical (e.g. to continue
a treatment of antibiotics once started in order to avoid antimicrobial In order to analyze the logical structure of DAS3, let us
resistance, which would have negative consequences for society) or even legal introduce the following time-indexed conditions C1, C2 and C3,
(e.g. in some countries, it is compulsory to be treated for tuberculosis). More
all instances of Statement, which is a subclass of ICE:
generally, those instructions may be seen as normative recommendations with
various strengths – from sheer permission to strong obligations. Also, it might
be a matter of debate towards which entity there is an obligation (the society?
the doctor?). We leave those questions open here.
9
This can be considered as a kind of “speech act” [30].
x C1(t): ‘at t, symptoms of bronchitis are present’ C1 is an instance of Drug administration starting
condition12. Moreover, C1 is here an instance of Presence of
x C2(t): ‘at t, less than 7 x 24h have elapsed since the symptom statement, but in another instance of DAS, the
administration of a first dose or no first dose has been condition for starting the drug administration might be e.g., an
administered’ instance of Current time statement (such as ‘at t, it is July 2nd,
x C3(t): ‘at t, 8 hours have elapsed since the 2016’).
administration of the last dose during the current drug If C2(t) and C3(t) are both true at some time t, subsequent
administration or no first dose has been administered’ dose administration(s) should occur as part of a drug
DAS3 is synonymous 10 with DAS3 ′ , which reads as administration. However, once the drug administration has
follows: begun, C2 remains true until it becomes false, playing the role
of an upper bound for the drug administration, whereas C3 can
DAS3′: ‘for every t0, if C1(t0), complete the administration alternate truth values with some periodicity during the drug
of Amoxicillin as directed by PDS′(t0), in case such a drug administration. This is why C2 is classified as a Drug
administration is not already ongoing’ administration continuing condition and C3 as a Dosing
condition.
Where PDS′(t0) is an instance of Prescribed dosing
specification, defined as a normative specification that directs Here, C2 is an instance of Time elapsed since first dose
the dosing of a drug product: statement and C3 is an instance of Time elapsed since previous
dose statement. In another instance of DAS, the condition for
PDS′(t0): ‘for every t>t0, if C2(t) and C3(t) then administer
continuing a drug administration might be e.g., an instance of
a dose of 500 mg PO of drug at t’
Number of doses statement (such as ‘at t, less than 21 doses of
The action11 guided by DAS3′ is a drug administration over this drug have been given’) or Current time statement (such as
seven days in order to achieve some health-related objective, ‘at t, it is before July 2nd, 2016’), and the dosing condition
specifically that of treating an acute bronchitis. By contrast, might be e.g., an instance of Presence of symptom statement
PDS′(t0) guides an action whose extension in time is much (such as ‘at t, the patient has chest pain’) or Total dosage
more limited, namely a dose administration at time t. When statement (such as ‘at t, less than 4 grams of this drug have
such a dose administration is not permitted, it is prohibited by been administered in the last 24 hours’).
the background prohibition.
Fig. 1. Mereology of particulars and corresponding universals in DAS3. Note that the labels of Drug administration starting condition and Drug administration
continuing condition have been truncated.
12
Note that C1(t) is a Drug administration starting condition only because it is
used in some way in the prescription. Therefore, Drug administration starting
10
Note that DAS3 is not the same ICE as DAS3′: they are different entities as condition can be seen as equivalent to an ICE that is BFO:bearer_of a Drug
they are concretized by different chains of characters. For more on synonymy, administration starting condition role (and similar considerations could hold
see section V.B. for C2(t) and C3(t) defined above). Since the use of roles has not yet been
11
We refer here informally to an ‘action’, without taking a position on systematized in BFO and IAO for ICEs, we have not defined these role
whether an action is a process or some other entity. classes in PDRO yet.
Although PDS′(t0) specifies here the administration of forward by [35]). Another problem is raised concerning what
some dose at some time t, other specifications may be more prescriptions are about. Since parts of prescriptions are DIEs,
temporally extended in their instruction. For example, if a DAS they are not about some future processes, as such process may
were to specify to take a medication “bid” (i.e. twice per day), never occur, as stated earlier. In this respect, future work would
it would be synonymous with a DIE having as part the include articulating PDRO with the Document Acts Ontology
condition: ‘less than two doses have been administered during [28] by linking a Normative specification with the deontic
the day of which t is part’, which, if true, would instruct the entity it gives rise to.
administration of two doses during the day of which t is part,
without specifying the time at which these dose administrations Note also that a doctor’s prescription does not only permit
should occur. the administration of a drug to a patient: it also permits a
pharmacist to distribute those drugs. A pharmacist may also
Note that a DAS will only have prescriptive power and further specify the original prescription, for example, by
specify authentic instructions in case the current time is during selecting a particular brand of drug product intended to be
the period of validity of the prescription. For example, in dispensed to the patient.
Québec, this is by default 24 months after the prescription has
been written [32]. Finally, while PDRO is a reference ontology formalizing
the various parts of a drug prescription, additional requirements
specific to a given jurisdiction might be required to create or
V. CONCLUSION AND FUTURE WORK validate prescriptions in this context. To formalize this, various
application ontologies can be built upon PDRO in order to
A. Conclusion describe how a prescription should be structured according to
By formalizing the informational parts of a prescription, local norms. We will clarify this articulation in a subsequent
PDRO enables the annotation of real-world prescriptions at article.
various levels of mereological granularity. It supports, for
example, the specification of a drug product based on its active ACKNOWLEDGMENT
ingredient(s), its branded name, its strength(s) or its form,
avoiding the ambiguities and overspecificities often We thank Thomas Joly-Mischlich for the invaluable insight
encountered in e-prescribing systems. Complex dosing into the impact of drug prescription semantics on clinical
instructions can be represented in a coherent manner, as pharmacy. We also thank team member Christina Khnaisser
illustrated by the example of Amoxicillin for bronchitis. This is for the useful discussions on e-prescribing platforms. AB’s
achieved by dissociating the instructions for an entire drug research was supported by the “Bourse de fellowship du
administration from the instructions for a single dose Département de médecine de l’Université de Sherbrooke”.
administration. In addition, we distinguish the conditions
determining those normative specifications and illustrate how REFERENCES
interchangeable statements can play the role of these [1] Y. He, S. Sarntivijai, Y. Lin, Z. Xiang, A. Guo, et al., “OAE: The
conditions in order to cover the variety of expressions found on Ontology of Adverse Events.,” J. Biomed. Semant., vol. 5, no. 1, p. 29,
prescriptions. Jan. 2014.
PDRO could both improve the semantics of electronic [2] Institute of Medicine, P. Aspden, J. Wolcott, J. L. Bootman, and L. R.
Cronenwett, Preventing Medication Errors: Quality Chasm Series.
prescriptions and prospectively enable the interoperability of Washington, D.C.: The National Academies Press, 2007.
prescription data. Used in conjunction with other OBO
Foundry ontologies, it can be used to express complex [3] M. Pirmohamed, S. James, S. Meakin, C. Green, A. K. Scott, et al.,
decision-support rules to identify potentially inappropriate “Adverse drug reactions as cause of admission to hospital: prospective
analysis of 18 820 patients.,” BMJ, vol. 329, no. 7456, pp. 15–9, Jul.
prescriptions among hospitalized elderly patients [33]. With 2004.
the introduction of normative specifications and conditions, we
can also envision, for example, smartphone applications that [4] J. Lazarou, B. H. Pomeranz, and P. N. Corey, “Incidence of adverse
drug reactions in hospitalized patients: a meta-analysis of prospective
guide patients with polypharmacy in safely taking their studies.,” JAMA, vol. 279, no. 15, pp. 1200–5, Apr. 1998.
medication as directed, and thereby reduce adverse drug
events. [5] Linda T. Kohn, Janet M. Corrigan, and Molla S. Donaldson, Eds., To
Err Is Human: Building a Safer Health System. Washington, D.C.:
National Academies Press, 2000.
B. Future work
[6] P. G. Shekelle, R. M. Wachter, P. J. Pronovost, K. Schoelles, K. M.
The question of aboutness is currently left open by PDRO. McDonald, et al., “Making health care safer II: an updated critical
The relation IAO:is_about could be used to define synonymy: analysis of the evidence for patient safety practices.,” Evid.
several ICEs are synonyms if they are about the same portion ReportTechnology Assess., no. 211, pp. 1–945, Mar. 2013.
of reality (as defined by [27]). However, some challenges need [7] E. Ammenwerth, P. Schnell-Inderst, C. Machan, and U. Siebert, “The
to be addressed before PDRO can consistently use aboutness. effect of electronic prescribing on medication errors and adverse drug
A first one is a representational issue: a drug product events: a systematic review.,” J. Am. Med. Inform. Assoc. JAMIA, vol.
specification, such as ‘Lopresor’, is an instance of ICE which 15, no. 5, pp. 585–600, Jan. 2008.
is about the class of drug product branded as “Lopresor”. [8] T. K. Nuckols, C. Smith-Spangler, S. C. Morton, S. M. Asch, V. M.
However, an instance cannot be related to a class in OWL Patel, et al., “The effectiveness of computerized order entry at reducing
using an object property [34] (some propositions have been put preventable adverse drug events and medication errors in hospital
settings: a systematic review and meta-analysis.,” Syst. Rev., vol. 3, p. [26] T. K. Gandhi, S. N. Weingart, A. C. Seger, J. Borus, E. Burdick, et al.,
56, Jan. 2014. “Outpatient prescribing errors and the impact of computerized
prescribing.,” J. Gen. Intern. Med., vol. 20, no. 9, pp. 837–41, Sep.
[9] J. Kannry, “Effect of e-prescribing systems on patient safety.,” Mt. Sinai 2005.
J. Med. N. Y., vol. 78, no. 6, pp. 827–33, Jan. 2011.
[27] B. Smith and W. Ceusters, “Aboutness: Towards foundations for the
[10] M.-P. Gagnon, É.-R. Nsangou, J. Payne-Gagnon, S. Grenier, and C. information artifact ontology,” in Proceedings of the Sixth International
Sicotte, “Barriers and facilitators to implementing electronic Conference on Biomedical Ontology (ICBO), 2015.
prescription: a systematic review of user groups’ perceptions,” J. Am.
Med. Inform. Assoc., vol. 21, no. 3, pp. 535–541, 2014. [28] Mathias Brochhausen, Mauricio Barcellos Almeida, and Laura
Slaughter, “Towards a formal representation of document acts and
[11] M.-P. Gagnon, J. Payne-Gagnon, C. Sicotte, J.-A. Langué-Dubé, and A. resulting legal entities,” in Johanssonian Investigations: Essays in
Motulsky, “Connecting primary care clinics and community pharmacies Honour of Ingvar Johansson on His Seventieth Birthday, Walter de
through a nationwide electronic prescribing network: a qualitative Gruyter, 2013.
study,” J. Innov. Health Inform., vol. 2222, no. 3, pp. 359–367, Jan.
2015. [29] B. Smith, “How to Do Things with Documents,” Riv. Estet., vol. 50, no.
50, pp. 179–198, 2012.
[12] R. Arp, B. Smith, and A. D. Spear, Building Ontologies with Basic
Formal Ontology. The MIT Press, 2015. [30] M. Green, “Speech Acts,” The Stanford Encyclopedia of Philosophy.
2015.
[13] B. Smith, M. Ashburner, C. Rosse, J. Bard, W. Bug, et al., “The OBO
Foundry: coordinated evolution of ontologies to support biomedical data [31] S.-E. Öhlund and G. Goldkuhl, “Towards a socio-pragmatic
integration,” Nat. Biotechnol., vol. 25, no. 11, pp. 1251–1255, Nov. understanding of ePrescribing,” in 5th Intl Conference on Action in
2007. Language, Organisations and Information Systems (ALOIS-2008),
Venice, 2008.
[14] J. Hanna, E. Joseph, M. Brochhausen, and W. R. Hogan, “Building a
drug ontology based on RxNorm and other sources,” J. Biomed. [32] 41e Assemblée Nationale du Québec, Règlement sur les normes
Semant., vol. 4, p. 44, Dec. 2013. relatives aux ordonnances faites par un médecin. 2015.
[15] Mathias Brochhausen, Jodi Schneider, Daniel Malone, Philip E. Empey, [33] K. Arvisais, S. Bergeron-Wolff, C. Bouffard, A.-S. Michaud, J.
William R. Hogan, et al., “Towards a foundational representation of Bergeron, et al., “A Pharmacist-Physician Intervention Model Using a
potential drug-drug interaction knowledge,” in Drug Interaction Computerized Alert System to Reduce High-Risk Medication Use in
Knowledge Management (DIKR 2014), Houston, Texas, 2014. Elderly Inpatients,” Drugs Aging, vol. 32, no. 8, pp. 663–670, Aug.
2015.
[16] A. Motulsky, C. Sicotte, M.-P. Gagnon, J. Payne-Gagnon, J.-A. Langué-
Dubé, et al., “Challenges to the implementation of a nationwide [34] Boris Motik, Peter F. Patel-Schneider, and Bijan Parsia, “OWL 2 Web
electronic prescribing network in primary care: a qualitative study of Ontology Language Structural Specification and Functional-Style
users’ perceptions.,” J. Am. Med. Inform. Assoc. JAMIA, vol. 22, no. 4, Syntax (Second Edition).” [Online]. Available:
pp. 838–48, Jul. 2015. https://www.w3.org/TR/owl2-syntax/. [Accessed: 13-May-2016].
[17] O. Odukoya and M. a. Chui, “Retail pharmacy staff perceptions of [35] S. Schulz, C. Martínez-Costa, D. Karlsson, R. Cornet, M. Brochhausen,
design strengths and weaknesses of electronic prescribing,” J. Am. Med. et al., “An Ontological Analysis of Reference in Health Record
Inform. Assoc., vol. 19, no. 6, pp. 1059–1065, Jan. 2012. Statements.,” in FOIS, 2014, pp. 289–302.
[18] K. L. Lapane, R. K. Rosen, and C. Dubé, “Perceptions of e-prescribing
efficiencies and inefficiencies in ambulatory care.,” Int. J. Med. Inf., vol.
80, no. 1, pp. 39–46, Jan. 2011.
[19] H. Liu, Q. Burkhart, and D. S. Bell, “Evaluation of the NCPDP
Structured and Codified Sig Format for e-prescriptions,” J. Am. Med.
Inform. Assoc., vol. 18, no. 5, pp. 645–651, Sep. 2011.
[20] M. S. Wolf, L. M. Curtis, K. Waite, S. C. Bailey, L. A. Hedlund, et al.,
“Helping Patients Simplify and Safely Use Complex Prescription
Regimens,” Arch. Intern. Med., vol. 171, no. 4, pp. 300–305, Feb. 2011.
[21] Institute of Medicine, P. Aspden, J. Wolcott, J. L. Bootman, and L. R.
Cronenwett, Preventing Medication Errors: Quality Chasm Series.
Washington, D.C.: The National Academies Press, 2007.
[22] T. C. Davis, M. S. Wolf, P. F. Bass, J. A. Thompson, H. H. Tilson, et al.,
“Literacy and misunderstanding prescription drug labels.,” Ann. Intern.
Med., vol. 145, no. 12, pp. 887–94, Dec. 2006.
[23] T. C. Davis, A. D. Federman, P. F. Bass, R. H. Jackson, M.
Middlebrooks, et al., “Improving patient understanding of prescription
drug label instructions.,” J. Gen. Intern. Med., vol. 24, no. 1, pp. 57–62,
Jan. 2009.
[24] M. B. Palchuk, E. A. Fang, J. M. Cygielnik, M. Labreche, M. Shubina,
et al., “An unintended consequence of electronic prescriptions:
prevalence and impact of internal discrepancies,” J. Am. Med. Inform.
Assoc. JAMIA, vol. 17, no. 4, pp. 472–476, 2010.
[25] K. C. Nanji, J. M. Rothschild, C. Salzberg, C. A. Keohane, K. Zigmont,
et al., “Errors associated with outpatient computerized prescribing
systems.,” J. Am. Med. Inform. Assoc. JAMIA, vol. 18, no. 6, pp. 767–
73, Jan. 2011.