An ontology-based approach for detecting and classifying inappropriate prescribing

Guilherme Alfredo Redeker; Juliana Kuster Filipe Bowles

An ontology-based approach for detecting and classifying inappropriate prescribing

Guilherme Alfredo Redeker^*
, Juliana Kuster Filipe Bowles^*

^*Corresponding author for this work

School of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The Beers Criteria, widely used by healthcare professionals, list so-called Potentially Inappropriate Medications (PIMs) which older adults in certain circumstances should avoid. Manually identifying medications that belong to the Beers Criteria can be time-consuming and error-prone, as the criteria are complex and subject to frequent updates. Moreover, it is not available in a (formal) representation that health systems can interpret and reason with automatically. This paper proposes an ontology as a formal representation of the Beers Criteria, and describes the elements and the taxonomy underlying the ontology. We include inference rules to enable automated detection and categorisation of drugs classified as PIMs. By automatically detecting drugs that belong to the Beers Criteria, the ontology, once linked with decision support systems, can be used to support healthcare providers in ensuring that older adults receive safe and effective medical care.

Original language	English
Title of host publication	RuleML+RR’23
Subtitle of host publication	17th International Rule Challenge and 7th Doctoral Consortium, September 18–20, 2023, Oslo, Norway
Editors	Jan Vanthienen, Tomáš Kliegr, Paul Fodor, Davide Lanti, Dörthe Arndt, Egor V. Kostylev, Theodoros Mitsikas, Ahmet Soylu
Publisher	CEUR-WS
Chapter	7459
Number of pages	15
Publication status	Published - 15 Sept 2023

Publication series

Name	CEUR Workshop Proceedings
Volume	3485
ISSN (Electronic)	1613-0073

Keywords

Ontology
Inference rules
Potentially inappropriate medications
Clinical decision support systems

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Redeker, G. A., & Kuster Filipe Bowles, J. (2023). An ontology-based approach for detecting and classifying inappropriate prescribing. In J. Vanthienen, T. Kliegr, P. Fodor, D. Lanti, D. Arndt, E. V. Kostylev, T. Mitsikas, & A. Soylu (Eds.), RuleML+RR’23: 17th International Rule Challenge and 7th Doctoral Consortium, September 18–20, 2023, Oslo, Norway (CEUR Workshop Proceedings; Vol. 3485). CEUR-WS. https://ceur-ws.org/Vol-3485/paper7459.pdf

Redeker, Guilherme Alfredo ; Kuster Filipe Bowles, Juliana. / An ontology-based approach for detecting and classifying inappropriate prescribing. RuleML+RR’23: 17th International Rule Challenge and 7th Doctoral Consortium, September 18–20, 2023, Oslo, Norway. editor / Jan Vanthienen ; Tomáš Kliegr ; Paul Fodor ; Davide Lanti ; Dörthe Arndt ; Egor V. Kostylev ; Theodoros Mitsikas ; Ahmet Soylu. CEUR-WS, 2023. (CEUR Workshop Proceedings).

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title = "An ontology-based approach for detecting and classifying inappropriate prescribing",

abstract = "The Beers Criteria, widely used by healthcare professionals, list so-called Potentially Inappropriate Medications (PIMs) which older adults in certain circumstances should avoid. Manually identifying medications that belong to the Beers Criteria can be time-consuming and error-prone, as the criteria are complex and subject to frequent updates. Moreover, it is not available in a (formal) representation that health systems can interpret and reason with automatically. This paper proposes an ontology as a formal representation of the Beers Criteria, and describes the elements and the taxonomy underlying the ontology. We include inference rules to enable automated detection and categorisation of drugs classified as PIMs. By automatically detecting drugs that belong to the Beers Criteria, the ontology, once linked with decision support systems, can be used to support healthcare providers in ensuring that older adults receive safe and effective medical care.",

keywords = "Ontology, Inference rules, Potentially inappropriate medications, Clinical decision support systems",

author = "Redeker, \{Guilherme Alfredo\} and \{Kuster Filipe Bowles\}, Juliana",

note = "Funding: Bowles is partially supported by Austrian FWF Meitner Fellowship M-3338 N.",

year = "2023",

month = sep,

day = "15",

language = "English",

series = "CEUR Workshop Proceedings",

publisher = "CEUR-WS",

editor = "Jan Vanthienen and Tom{\'a}{\v s} Kliegr and Paul Fodor and Davide Lanti and D{\"o}rthe Arndt and Kostylev, \{Egor V.\} and Theodoros Mitsikas and Ahmet Soylu",

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Redeker, GA & Kuster Filipe Bowles, J 2023, An ontology-based approach for detecting and classifying inappropriate prescribing. in J Vanthienen, T Kliegr, P Fodor, D Lanti, D Arndt, EV Kostylev, T Mitsikas & A Soylu (eds), RuleML+RR’23: 17th International Rule Challenge and 7th Doctoral Consortium, September 18–20, 2023, Oslo, Norway. CEUR Workshop Proceedings, vol. 3485, CEUR-WS. <https://ceur-ws.org/Vol-3485/paper7459.pdf>

An ontology-based approach for detecting and classifying inappropriate prescribing. / Redeker, Guilherme Alfredo; Kuster Filipe Bowles, Juliana.
RuleML+RR’23: 17th International Rule Challenge and 7th Doctoral Consortium, September 18–20, 2023, Oslo, Norway. ed. / Jan Vanthienen; Tomáš Kliegr; Paul Fodor; Davide Lanti; Dörthe Arndt; Egor V. Kostylev; Theodoros Mitsikas; Ahmet Soylu. CEUR-WS, 2023. (CEUR Workshop Proceedings; Vol. 3485).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - An ontology-based approach for detecting and classifying inappropriate prescribing

AU - Redeker, Guilherme Alfredo

AU - Kuster Filipe Bowles, Juliana

N1 - Funding: Bowles is partially supported by Austrian FWF Meitner Fellowship M-3338 N.

PY - 2023/9/15

Y1 - 2023/9/15

N2 - The Beers Criteria, widely used by healthcare professionals, list so-called Potentially Inappropriate Medications (PIMs) which older adults in certain circumstances should avoid. Manually identifying medications that belong to the Beers Criteria can be time-consuming and error-prone, as the criteria are complex and subject to frequent updates. Moreover, it is not available in a (formal) representation that health systems can interpret and reason with automatically. This paper proposes an ontology as a formal representation of the Beers Criteria, and describes the elements and the taxonomy underlying the ontology. We include inference rules to enable automated detection and categorisation of drugs classified as PIMs. By automatically detecting drugs that belong to the Beers Criteria, the ontology, once linked with decision support systems, can be used to support healthcare providers in ensuring that older adults receive safe and effective medical care.

AB - The Beers Criteria, widely used by healthcare professionals, list so-called Potentially Inappropriate Medications (PIMs) which older adults in certain circumstances should avoid. Manually identifying medications that belong to the Beers Criteria can be time-consuming and error-prone, as the criteria are complex and subject to frequent updates. Moreover, it is not available in a (formal) representation that health systems can interpret and reason with automatically. This paper proposes an ontology as a formal representation of the Beers Criteria, and describes the elements and the taxonomy underlying the ontology. We include inference rules to enable automated detection and categorisation of drugs classified as PIMs. By automatically detecting drugs that belong to the Beers Criteria, the ontology, once linked with decision support systems, can be used to support healthcare providers in ensuring that older adults receive safe and effective medical care.

KW - Ontology

KW - Inference rules

KW - Potentially inappropriate medications

KW - Clinical decision support systems

UR - https://ceur-ws.org/

M3 - Conference contribution

T3 - CEUR Workshop Proceedings

BT - RuleML+RR’23

A2 - Vanthienen, Jan

A2 - Kliegr, Tomáš

A2 - Fodor, Paul

A2 - Lanti, Davide

A2 - Arndt, Dörthe

A2 - Kostylev, Egor V.

A2 - Mitsikas, Theodoros

A2 - Soylu, Ahmet

PB - CEUR-WS

ER -

Redeker GA, Kuster Filipe Bowles J. An ontology-based approach for detecting and classifying inappropriate prescribing. In Vanthienen J, Kliegr T, Fodor P, Lanti D, Arndt D, Kostylev EV, Mitsikas T, Soylu A, editors, RuleML+RR’23: 17th International Rule Challenge and 7th Doctoral Consortium, September 18–20, 2023, Oslo, Norway. CEUR-WS. 2023. (CEUR Workshop Proceedings).

An ontology-based approach for detecting and classifying inappropriate prescribing

Abstract

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Keywords

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A clinical decision support system for detecting and mitigating potentially inappropriate medications

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An ontology-based approach for detecting and classifying inappropriate prescribing

Abstract

Publication series

Keywords

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Student theses

A clinical decision support system for detecting and mitigating potentially inappropriate medications

Cite this