Archetype modeling methodology

Moner, David; Maldonado, José Alberto; Robles, Montserrat

doi:10.1016/j.jbi.2018.02.003

Cited by 17 publications

(24 citation statements)

References 19 publications

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“…This study was performed using the approach suggested by Bacelar-Silva et al [30] Braun et al [31] and Moner et al [32], comprising the following sequential steps ( Fig. 1).…”

Section: Methodsmentioning

confidence: 99%

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Nutrition Information in Oncology — Extending the Electronic Patient-Record Data Set

et al. 2020

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Electronic health records (EHRs) present extensive patient information and may be used as a tool to improve health care. However, the oncology context presents a complex content that increases the difficulties of EHR application. This study aimed at developing openEHR-archetypes representing clinical concepts in cancer nutrition-care, as well as to develop an openEHRtemplate including the aforementioned archetypes. The study involved the following stages: 1) a thorough literature review, followed by an expert's (nutrition guideline authors) survey, aiming to identify the main statements of published clinical guidelines on nutrition in cancer patients that were not included on the Clinical Knowledge Manager (CKM) repository; 2) modelling of the archetypes using the Ocean Archetype Software and submission to the CKM repository; 3) creating an example template with Template Designer; and 4) automatic conversion of the openEHR-template into a readily usable EHR using VCIntegrator. The clinical concepts (among 17 clinical concepts not yet available in the CKM repository) chosen for further development were: body composition, diet plan, dietary nutrients, dietary supplements, dietary intake assessment, and Malnutrition Screening Tool (MST). So far, four archetypes were accepted for review in the CKM repository and a template was created and converted into an EHR. This study designed new openEHR-archetypes for nutrition management in cancer patients. These archetypes can be included in EHR. Future studies are needed to assess their applicability in other areas and their practical impact on data quality, system interoperability and, ultimately, on clinical practice and research.

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“…This study was performed using the approach suggested by Bacelar-Silva et al [30] Braun et al [31] and Moner et al [32], comprising the following sequential steps ( Fig. 1).…”

Section: Methodsmentioning

confidence: 99%

“…Subsequently, the selected concepts were modelled as openEHR archetypes. Archetype modelling has been widely applied in previous studies [30,32,34]. The concepts were discussed by the authors and relevant items were identified from books, journal articles, and guidelines.…”

Section: Archetype Modelling In Openehrmentioning

confidence: 99%

Nutrition Information in Oncology — Extending the Electronic Patient-Record Data Set

et al. 2020

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“…To find relevant archetypes from the open repository, we first had to understand which kinds of terms end users tended to enter. As archetype modeling methodology [23] shows, domain experts identify core clinical concepts and related data elements involved in a particular scenario and organize them into mind maps or design tables. These archetype design specifications are the main source of search keywords.…”

Section: Methodsmentioning

confidence: 99%

“…Archetypes are general purpose, reusable, and composable; therefore, searching for reusable archetypes from archetype repositories is essential throughout the development process [22,23]. Documents with complete archetype design specifications are the input; lists of existing reusable archetypes, either complete or needing modifications, and new archetypes to be developed from scratch are the output [23]. The crucial problem is how to find the relevant ones from open repositories to help identify reusable archetypes.…”

Section: Introductionmentioning

confidence: 99%

Discovering Clinical Information Models Online to Promote Interoperability of Electronic Health Records: A Feasibility Study of OpenEHR

Yang

Huang

2019

J Med Internet Res

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2 For purposes this framework, unless otherwise noted, the term drug refers both to a drug approved under section 505(c) or (j) of the Federal Food, Drug, and Cosmetic Act (FD&C Act) and to biological products licensed under section 351 of the Public Health Service Act (PHS Act) 42 USC 262. 3 In this document, when we refer to the use of RWE to support a regulatory decision, we mean that the evidence provides support for or helps provide support for the regulatory decision. 4 FDA issued the guidance Use of Real-World Evidence to Support Regulatory Decision-Making for Medical Devices on August 31, 2017. Real-World Data (RWD) are data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources. Real-World Evidence (RWE) is the clinical evidence about the usage and potential benefits or risks of a medical product derived from analysis of RWD.

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“…Moner et al [16] define an Archetype Modeling Methodology (AMM). The main phases of the methodology are briefly described below.…”

Section: Archetype Modeling Methodologymentioning

confidence: 99%

Extending Two-level Information Modeling to the Internet of Things

Stacey

Berry

2019

2019 IEEE 5th World Forum on Internet of Things (WF-IoT)

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Interoperability is a major challenge for the Internet of Things (IoT). The real potential of the IoT lies in facilitating largescale sharing of high-quality context-rich information through systems-of-IoT-systems, rather than IoT systems that operate as isolated technology silos. Real large-scale interoperability requires layers of standards, and each layer addresses different interoperability challenges. The SensorThings API data model seeks to tackle data interoperability at the data and informational layers of IoT platforms. SensorThings API is aligned to the ISO/OGC O&M data standard, and like O&M it is semistructured. Semi-structured models allow for variance within implementations for different use-cases, which is both necessary and detrimental to systems interoperability. In this paper we propose that the SensorThings API data model should be defined as a set of archetypes, used to capture extensible domain concepts using a two-level modeling IoT systems design approach. Extending two-level modeling to the IoT using the SensorThings API as a base for domain concepts definition allows for a powerful framework to manage variance within systems implementation and maintaining semantic interoperability within systems-of-IoT-systems across diverse use-cases.

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Archetype modeling methodology

Cited by 17 publications

References 19 publications

Nutrition Information in Oncology — Extending the Electronic Patient-Record Data Set

Nutrition Information in Oncology — Extending the Electronic Patient-Record Data Set

Discovering Clinical Information Models Online to Promote Interoperability of Electronic Health Records: A Feasibility Study of OpenEHR

Extending Two-level Information Modeling to the Internet of Things

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