Literature DB >> 23707417

Interoperability of clinical decision-support systems and electronic health records using archetypes: a case study in clinical trial eligibility.

Mar Marcos1, Jose A Maldonado, Begoña Martínez-Salvador, Diego Boscá, Montserrat Robles.   

Abstract

Clinical decision-support systems (CDSSs) comprise systems as diverse as sophisticated platforms to store and manage clinical data, tools to alert clinicians of problematic situations, or decision-making tools to assist clinicians. Irrespective of the kind of decision-support task CDSSs should be smoothly integrated within the clinical information system, interacting with other components, in particular with the electronic health record (EHR). However, despite decades of developments, most CDSSs lack interoperability features. We deal with the interoperability problem of CDSSs and EHRs by exploiting the dual-model methodology. This methodology distinguishes a reference model and archetypes. A reference model is represented by a stable and small object-oriented model that describes the generic properties of health record information. For their part, archetypes are reusable and domain-specific definitions of clinical concepts in the form of structured and constrained combinations of the entities of the reference model. We rely on archetypes to make the CDSS compatible with EHRs from different institutions. Concretely, we use archetypes for modelling the clinical concepts that the CDSS requires, in conjunction with a series of knowledge-intensive mappings relating the archetypes to the data sources (EHR and/or other archetypes) they depend on. We introduce a comprehensive approach, including a set of tools as well as methodological guidelines, to deal with the interoperability of CDSSs and EHRs based on archetypes. Archetypes are used to build a conceptual layer of the kind of a virtual health record (VHR) over the EHR whose contents need to be integrated and used in the CDSS, associating them with structural and terminology-based semantics. Subsequently, the archetypes are mapped to the EHR by means of an expressive mapping language and specific-purpose tools. We also describe a case study where the tools and methodology have been employed in a CDSS to support patient recruitment in the framework of a clinical trial for colorectal cancer screening. The utilisation of archetypes not only has proved satisfactory to achieve interoperability between CDSSs and EHRs but also offers various advantages, in particular from a data model perspective. First, the VHR/data models we work with are of a high level of abstraction and can incorporate semantic descriptions. Second, archetypes can potentially deal with different EHR architectures, due to their deliberate independence of the reference model. Third, the archetype instances we obtain are valid instances of the underlying reference model, which would enable e.g. feeding back the EHR with data derived by abstraction mechanisms. Lastly, the medical and technical validity of archetype models would be assured, since in principle clinicians should be the main actors in their development.
Copyright © 2013 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Clinical decision support systems; Clinical trials; Electronic health records; SNOMED CT; Systems integration; Terminology

Mesh:

Year:  2013        PMID: 23707417     DOI: 10.1016/j.jbi.2013.05.004

Source DB:  PubMed          Journal:  J Biomed Inform        ISSN: 1532-0464            Impact factor:   6.317


  26 in total

1.  Towards the semantic enrichment of Computer Interpretable Guidelines: a method for the identification of relevant ontological terms.

Authors:  Manuel Quesada-Martínez; Mar Marcos; Francisco Abad-Navarro; Begoña Martínez-Salvador; Jesualdo Tomás Fernández-Breis
Journal:  AMIA Annu Symp Proc       Date:  2018-12-05

2.  A platform for exploration into chaining of web services for clinical data transformation and reasoning.

Authors:  José Alberto Maldonado; Mar Marcos; Jesualdo Tomás Fernández-Breis; Estíbaliz Parcero; Diego Boscá; María Del Carmen Legaz-García; Begoña Martínez-Salvador; Montserrat Robles
Journal:  AMIA Annu Symp Proc       Date:  2017-02-10

Review 3.  Personalization and Patient Involvement in Decision Support Systems: Current Trends.

Authors:  S Quaglini; L Sacchi; G Lanzola; N Viani
Journal:  Yearb Med Inform       Date:  2015-08-13

4.  Patients Decision Aid System Based on FHIR Profiles.

Authors:  Ilia Semenov; Georgy Kopanitsa; Dmitry Denisov; Yakovenko Alexandr; Roman Osenev; Yury Andreychuk
Journal:  J Med Syst       Date:  2018-07-31       Impact factor: 4.460

5.  Measurement and application of patient similarity in personalized predictive modeling based on electronic medical records.

Authors:  Ni Wang; Yanqun Huang; Honglei Liu; Xiaolu Fei; Lan Wei; Xiangkun Zhao; Hui Chen
Journal:  Biomed Eng Online       Date:  2019-10-11       Impact factor: 2.819

6.  iT2DMS: a Standard-Based Diabetic Disease Data Repository and its Pilot Experiment on Diabetic Retinopathy Phenotyping and Examination Results Integration.

Authors:  Huiqun Wu; Yufang Wei; Yujuan Shang; Wei Shi; Lei Wang; Jingjing Li; Aimin Sang; Lili Shi; Kui Jiang; Jiancheng Dong
Journal:  J Med Syst       Date:  2018-06-06       Impact factor: 4.460

Review 7.  Clinical Decision Support Systems.

Authors:  Andreas Teufel; Harald Binder
Journal:  Visc Med       Date:  2021-09-28

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

Authors:  A González-Ferrer; M Peleg; M Marcos; J A Maldonado
Journal:  J Med Syst       Date:  2016-05-21       Impact factor: 4.460

Review 9.  Current applications and future directions for the CDISC Operational Data Model standard: A methodological review.

Authors:  Sam Hume; Jozef Aerts; Surendra Sarnikar; Vojtech Huser
Journal:  J Biomed Inform       Date:  2016-03-02       Impact factor: 6.317

10.  Leveraging electronic healthcare record standards and semantic web technologies for the identification of patient cohorts.

Authors:  Jesualdo Tomás Fernández-Breis; José Alberto Maldonado; Mar Marcos; María del Carmen Legaz-García; David Moner; Joaquín Torres-Sospedra; Angel Esteban-Gil; Begoña Martínez-Salvador; Montserrat Robles
Journal:  J Am Med Inform Assoc       Date:  2013-08-09       Impact factor: 4.497

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