Binding SNOMED CT Terms to Archetype Elements

Berges, Idoia; Bermúdez, Jesús; Illarramendi, Arantza

doi:10.3414/me13-02-0022

Cited by 5 publications

(1 citation statement)

References 6 publications

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“…On this basis, ontology mapping was delayed until the final stages of modeling. At this late stage, the effort required to map archetype terms to ontology entities is substantial [ 19 ], due in part to the large size of the ontologies [ 20 ]. Furthermore, designing clinical archetypes separately from ontologies may lead to major discrepancies in the meaning of the clinical statements.…”

Section: Introductionmentioning

confidence: 99%

An ontology-aware integration of clinical models, terminologies and guidelines: an exploratory study of the Scale for the Assessment and Rating of Ataxia (SARA)

Maarouf

Taboada

Rodriguez

et al. 2017

BMC Med Inform Decis Mak

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BackgroundElectronic rating scales represent an important resource for standardized data collection. However, the ability to exploit reasoning on rating scale data is still limited. The objective of this work is to facilitate the integration of the semantics required to automatically interpret collections of standardized clinical data. We developed an electronic prototype for the Scale of the Assessment and Rating of Ataxia (SARA), broadly used in neurology. In order to address the modeling challenges of the SARA, we propose to combine the best performances from OpenEHR clinical archetypes, guidelines and ontologies.MethodsA scaled-down version of the Human Phenotype Ontology (HPO) was built, extracting the terms that describe the SARA tests from free-text sources. This version of the HPO was then used as backbone to normalize the content of the SARA through clinical archetypes. The knowledge required to exploit reasoning on the SARA data was modeled as separate information-processing units interconnected via the defined archetypes. Each unit used the most appropriate technology to formally represent the required knowledge.ResultsBased on this approach, we implemented a prototype named SARA Management System, to be used for both the assessment of cerebellar syndrome and the production of a clinical synopsis. For validation purposes, we used recorded SARA data from 28 anonymous subjects affected by Spinocerebellar Ataxia Type 36 (SCA36). When comparing the performance of our prototype with that of two independent experts, weighted kappa scores ranged from 0.62 to 0.86.ConclusionsThe combination of archetypes, phenotype ontologies and electronic information-processing rules can be used to automate the extraction of relevant clinical knowledge from plain scores of rating scales. Our results reveal a substantial degree of agreement between the results achieved by an ontology-aware system and the human experts.Electronic supplementary materialThe online version of this article (10.1186/s12911-017-0568-4) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

An ontology-aware integration of clinical models, terminologies and guidelines: an exploratory study of the Scale for the Assessment and Rating of Ataxia (SARA)

Maarouf

Taboada

Rodriguez

et al. 2017

BMC Med Inform Decis Mak

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Mapping a Nursing Terminology Subset to open EHR Archetypes

Nogueira¹,

Cook²,

Cavalini³

2015

Methods Inf Med

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Summary Background: Healthcare information technologies have the potential to transform nursing care. However, healthcare information systems based on conventional software architecture are not semantically interoperable and have high maintenance costs. Health informatics standards, such as controlled terminologies, have been proposed to improve healthcare information systems, but their implementation in conventional software has not been enough to overcome the current challenge. Such obstacles could be removed by adopting a multilevel model-driven approach, such as the open EHR specifications, in nursing information systems. Objectives: To create an open EHR archetype model for the Functional Status concepts as published in Nursing Outcome Indicators Catalog of the International Classification for Nursing Practice (NOIC-ICNP). Methods: Four methodological steps were followed: 1) extraction of terms from the NOICICNP terminology; 2) identification of previously published open EHR archetypes; 3) assessment of the adequacy of those open EHR archetypes to represent the terms; and 4) development of new open EHR archetypes when required. Results: The “Barthel Index” archetype was retrieved and mapped to the 68 NOIC-ICNP Functional Status terms. There were 19 exact matches between a term and the correspondent archetype node and 23 archetype nodes that matched to one or more NOIC-INCP. No matches were found between the archetype and 14 of the NOIC-ICNP terms, and nine archetype nodes did not match any of the NOIC-ICNP terms. Conclusions: The open EHR model was sufficient to represent the semantics of the Functional Status concept according to the NOICICNP, but there were differences in data granularity between the terminology and the archetype, thus producing a significantly complex mapping, which could be difficult to implement in real healthcare information systems. However, despite the technological complexity, the present study demonstrated the feasibility of mapping nursing terminologies to open EHR archetypes, which emphasizes the importance of adopting the multilevel model-driven approach for the achievement of semantic interoperability between healthcare information systems.

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Is There a Consensus when Physicians Evaluate the Relevance of Retrieved Systematic Reviews?

et al. 2016

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Summary Background: A significant challenge associated with practicing evidence-based medicine is to provide physicians with relevant clinical information when it is needed. At the same time it appears that the notion of relevance is subjective and its perception is affected by a number of contextual factors. Objectives: To assess to what extent physi -cians agree on the relevance of evidence in the form of systematic reviews for a common set of patient cases, and to identify possible contextual factors that influence their perception of relevance. Methods: A web-based survey was used where pediatric emergency physicians from multiple academic centers across Canada were asked to evaluate the relevance of systematic reviews retrieved automatically for 14 written case vignettes (paper patients). The vignettes were derived from prospective data describing pediatric patients with asthma exacerbations presenting at the emer gency department. To limit the cognitive burden on respondents, the number of reviews associated with each vignette was limited to three. Results: Twenty-two academic emergency physicians with varying years of clinical practice completed the survey. There was no consensus in their evaluation of relevance of the retrieved reviews and physicians’ assessments ranged from very relevant to irrelevant evidence, with the majority of evaluations being somewhere in the middle. This indicates that the study participants did not share a notion of relevance uniformly. Further analysis of commentaries provided by the physicians allowed identifying three possible contextual factors: expected speci ficity of evidence (acute vs chronic condition), the terminology used in the systematic reviews, and the micro environment of clinical setting. Conclusions: There is no consensus among physicians with regards to what constitutes relevant clinical evidence for a given patient case. Subsequently, this finding suggests that evidence retrieval systems should allow for deep customization with regards to physi -cian’s preferences and contextual factors, including differences in the micro environment of each clinical setting.

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Binding SNOMED CT Terms to Archetype Elements

Cited by 5 publications

References 6 publications

An ontology-aware integration of clinical models, terminologies and guidelines: an exploratory study of the Scale for the Assessment and Rating of Ataxia (SARA)

An ontology-aware integration of clinical models, terminologies and guidelines: an exploratory study of the Scale for the Assessment and Rating of Ataxia (SARA)

Mapping a Nursing Terminology Subset to open EHR Archetypes

Is There a Consensus when Physicians Evaluate the Relevance of Retrieved Systematic Reviews?

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