An Archetype-Based Solution for the Interoperability of Computerised Guidelines and Electronic Health Records

Marcos, Mar; Maldonado, José Alberto; Martínez-Salvador, Begoña; Moner, David; Boscá, Diego; Robles, Montserrat

doi:10.1007/978-3-642-22218-4_35

Cited by 11 publications

(12 citation statements)

References 11 publications

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“…Marcos and Maldonado [6,14] developed a comprehensive approach to deal with DSSs and EHRs interoperability based on archetypes. González-Ferrer and Peleg [15,16] compared vMR, CDA and openEHR by evaluating their support of functional and nonfunctional requirements for interoperability.…”

Section: Related Workmentioning

confidence: 99%

“…This allows the CIG to be executed for a specific patient. To aid in the mapping task, using an intermediate (mediated) schema providing a reconciled, integrated and virtual view of the local repositories is a feasible solution [5,6]. The mediated schema is designed to represent the attributes of the domain relevant to the integration application and does not necessarily represent all of the attributes available in the sources [7].…”

Section: Introductionmentioning

confidence: 99%

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Analysis of the process of representing clinical statements for decision-support applications: a comparison of openEHR archetypes and HL7 virtual medical record

et al. 2016

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Objectives. Delivering patient-specific decision-support based on computer-interpretable guidelines (CIGs) Methods. Using qualitative research methods, we analyzed the encoding of ten representative clinical statements taken from two CIGs used in real decision-support systems into two health information models (openEHR archetypes and HL7 vMR instances) by four experienced informaticians.Results. Discussion among the modelers about each case study example greatly increased our understanding of the capabilities of these standards, which we share in this educational paper.Differing in content and structure, the openEHR archetypes were found to contain a greater level of representational detail and structure while the vMR representations took fewer steps to complete.Conclusions. The use of openEHR in the encoding of CIG clinical statements could potentially facilitate applications other than decision-support, including intelligent data analysis and integration of additional properties of data items from existing EHRs. On the other hand, due to their smaller size and fewer details, the use of vMR potentially supports quicker mapping of EHR data into clinical statements.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis of the process of representing clinical statements for decision-support applications: a comparison of openEHR archetypes and HL7 virtual medical record

et al. 2016

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“…Patients with SNOMED CT classes or subclasses identified in the indicator were retrieved with the help of the SNOMED CT closure. For brevity 12 , the following query-extract shows only a query for archetyped patients with diagnoses of the SNOMED CT concept 93761005, i.e. "Primary malignant neoplasm of colon (disorder)": Table 2 compares our computed indicator results to the results contained in the report generated for our hospital by the DSCA, and the results publicly reported 13 .…”

Section: Constructing Archetyped Sparql Queriesmentioning

confidence: 99%

“…They have been shown to facilitate the integration of data from several sources [15], to empower multi-centre clinical research [7] and to be a solid basis for ubiquitous computing [6]. Also, archetypes have been shown to facilitate the reuse of patient data for clinical trials [9] and guideline systems [3], [12]. In this paper, we focus on the reuse of patient data for the automated computation of quality indicators, which are measurable elements of practice performance for which there is evidence or consensus that they can assess the quality of provided care, and thus also change in quality [10].…”

Section: Introductionmentioning

confidence: 99%

Semantic Integration of Patient Data and Quality Indicators Based on openEHR Archetypes

Dentler

Teije

Cornet

et al. 2013

Lecture Notes in Computer Science

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Abstract. Electronic Health Record (EHRs) contain a wealth of information, but accessing and (re)using it is often difficult. Archetypes have been shown to facilitate the (re)use of EHR data, and may be useful with regard to clinical quality indicators. These indicators are often released centrally, but computed locally in several hospitals. They are typically expressed in natural language, which due to its inherent ambiguity does not guarantee comparable results. Thus, their information requirements should be formalised and expressed via standard terminologies such as SNOMED CT to represent concepts, and information models such as archetypes to represent their agreed-upon structure, and the relations between the concepts. The two-level methodology of the archetype paradigm allows domain experts to intuitively define indicators at the knowledge level, and the resulting queries are computable across institutions that employ the required archetypes. We tested whether openEHR archetypes can represent both elements of patient data required by indicators and EHR data for automated indicator computation. The relevant elements of the indicators and our hospital's database schema were mapped to (elements of) publicly available archetypes. The coverage of the public repository was high, and editing an archetype to fit our requirements was straightforward. Based on this mapping, a set of three indicators from the domain of gastrointestinal cancer surgery was formalised into archetyped SPARQL queries and run against archetyped patient data in OWL from our hospital's data warehouse to compute the indicators. The computed indicator results were comparable to centrally computed and publicly reported results, with differences likely to be due to differing indicator definitions and interpretations, insufficient data quality and insufficient and imprecise encoding. This paper shows that openEHR archetypes facilitate the semantic integration of quality indicators and routine patient data to automatically compute indicators.

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“…Therefore, new standards following a higher abstraction level were developed recently, given the need of stakeholders to manage and interact with data. Some examples are standards based on the HL7 RIM (like HL7 CDA [3] or HL7 vMR), or detailed clinical models like archetypes [4].…”

Section: Introductionmentioning

confidence: 99%

Data Integration for Clinical Decision Support Based on openEHR Archetypes and HL7 Virtual Medical Record

González-Ferrer

Peleg

Verhees³

et al. 2013

Lecture Notes in Computer Science

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Abstract. Clinical Decision Support Systems (CDSS) have gained relevance due to their potential to support patient-centric care, but their deployment still has to overcome barriers to become successful. One of these barriers is the integration of patient data with the CDSS engine, a tough challenge given the need to address interoperability with many different existing systems and medical devices. The MobiGuide project aims to build such a CDSS, providing guideline-based clinical decision support through a Personal Health Record (PHR). This PHR is the main component through which the CDSS could access patient data originating from hospital EMRs and wearable sensors, but it also contains the log of the recommendations provided by the CDSS. Using a case study, we compare data-representation standards through which the PHR could be developed, while considering expressiveness and usability requirements. We propose to develop the PHR by combining openEHR archetypes and the HL7 Virtual Medical Record standard, supported by a service oriented framework for data exchange. This proposal aims to close the gap between the HL7 and the ISO/CEN 13606 by using an openEHR-based approach.

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An Archetype-Based Solution for the Interoperability of Computerised Guidelines and Electronic Health Records

Cited by 11 publications

References 11 publications

Analysis of the process of representing clinical statements for decision-support applications: a comparison of openEHR archetypes and HL7 virtual medical record

Analysis of the process of representing clinical statements for decision-support applications: a comparison of openEHR archetypes and HL7 virtual medical record

Semantic Integration of Patient Data and Quality Indicators Based on openEHR Archetypes

Data Integration for Clinical Decision Support Based on openEHR Archetypes and HL7 Virtual Medical Record

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