Y Kim1, H-A Park. 1. Seoul National University , Korea.
Abstract
OBJECTIVES: The aims of this study were to develop detailed clinical models (DCMs) for nursing problems related to perinatal care and to test the applicability of these detailed clinical models. METHODS: First, we extracted entities of nursing problems by analyzing nursing-problem statements from nursing records, reviewing the literature, and interviewing nurse experts. Second, we extracted attributes and possible values needed to describe the entities in more detail by again analyzing nursing statements, reviewing the literature, and consulting nurse experts. Third, DCMs were modeled by linking each entity with possible attributes with value sets and optionalities. Fourth, entities, attributes and value sets in the DCMs were mapped to the International Classification for Nursing Practice (ICNP) version 2. Finally, DCMs were validated by consulting a group of experts and by applying them to real clinical data and nursing care scenarios published in the literature. The adequacy of the entities, attributes, value sets, and optionalities of the attributes were validated. RESULTS: Fifty-eight entities were identified, 41 entities from nursing records, 12 entities from literature review and 5 entities from nurse experts. Sixty-five attributes with values were identified, 25 attributes from nursing records, 34 attributes from literature review, and 6 attributes from nurse experts. In total 58 DCMs were developed and validated. CONCLUSIONS: The DCMs developed in this study can ensure that electronic health records contain meaningful and valid information, and support the semantic interoperability of nursing information.
OBJECTIVES: The aims of this study were to develop detailed clinical models (DCMs) for nursing problems related to perinatal care and to test the applicability of these detailed clinical models. METHODS: First, we extracted entities of nursing problems by analyzing nursing-problem statements from nursing records, reviewing the literature, and interviewing nurse experts. Second, we extracted attributes and possible values needed to describe the entities in more detail by again analyzing nursing statements, reviewing the literature, and consulting nurse experts. Third, DCMs were modeled by linking each entity with possible attributes with value sets and optionalities. Fourth, entities, attributes and value sets in the DCMs were mapped to the International Classification for Nursing Practice (ICNP) version 2. Finally, DCMs were validated by consulting a group of experts and by applying them to real clinical data and nursing care scenarios published in the literature. The adequacy of the entities, attributes, value sets, and optionalities of the attributes were validated. RESULTS: Fifty-eight entities were identified, 41 entities from nursing records, 12 entities from literature review and 5 entities from nurse experts. Sixty-five attributes with values were identified, 25 attributes from nursing records, 34 attributes from literature review, and 6 attributes from nurse experts. In total 58 DCMs were developed and validated. CONCLUSIONS: The DCMs developed in this study can ensure that electronic health records contain meaningful and valid information, and support the semantic interoperability of nursing information.
Entities:
Keywords:
Information sharing, model, standards; data collection; knowledge representation
Authors: Peter L Elkin; David Froehling; Brent A Bauer; Dietlind Wahner-Roedler; S Trent Rosenbloom; Kent Bailey; Steven H Brown Journal: Stud Health Technol Inform Date: 2007