Literature DB >> 25402424

Toward the design of a nursing ontology system.

Peter Benedik1, Uroš Rajkovič, Olga Šušteršič.   

Abstract

The unambiguous and consistent representation of the healthcare domain is the foundation of modernized healthcare (eg, electronic medical records). However, the nursing domain often fails to meet this requirement. In this article, we address this challenge by presenting a three-stage methodological approach that can be used to (1) capture knowledge in a nursing domain; (2) design a nursing ontology, composed of data models linked with terminology concepts in a multirelational property graph; and (3) implement and (4) evaluate the ontology. Through the feasibility, development, and evaluation phases of our methodological approach, we modeled a nursing domain (ontology) and the indices that partition the domain into an efficient, searchable space, where the solution to a nursing problem is seen as abstractly defined traversals through its graph vertices and edges. Thus, the use of the three-phase ontology development process and multirelational property graph was sufficiently comprehensive for achieving the representation of a nursing domain ontology and its instantiation.

Mesh:

Year:  2014        PMID: 25402424     DOI: 10.1097/CIN.0000000000000117

Source DB:  PubMed          Journal:  Comput Inform Nurs        ISSN: 1538-2931            Impact factor:   1.985


  2 in total

1.  The Status of Nursing Documentation in Slovenia: a Survey.

Authors:  Uroš Rajkovič; Marija Milavec Kapun; Dejan Dinevski; Vesna Prijatelj; Marija Zaletel; Olga Šušteršič
Journal:  J Med Syst       Date:  2016-07-26       Impact factor: 4.460

2.  A refined methodology for validation of information models derived from flowsheet data and applied to a genitourinary case.

Authors:  Bonnie L Westra; Kay S Lytle; Luann Whittenburg; Mischa Adams; Samira Ali; Meg Furukawa; Stephanie Hartleben; Mary Hook; Steve Johnson; Sarah Collins Rossetti; Tess Theresa Settergren
Journal:  J Am Med Inform Assoc       Date:  2020-11-01       Impact factor: 4.497

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.