Harmonising Nursing Terminologies Using a Conceptual Framework.

The International Classification for Nursing Practice (ICNP®) and the Clinical Care Classification (CCC) System are standardised nursing terminologies that identify discrete elements of nursing practice, including nursing diagnoses, interventions, and outcomes. While CCC uses a conceptual framework or model with 21 Care Components to classify these elements, ICNP, built on a formal Web Ontology Language (OWL) description logic foundation, uses a logical hierarchical framework that is useful for computing and maintenance of ICNP. Since the logical framework of ICNP may not always align with the needs of nursing practice, an informal framework may be a more useful organisational tool to represent nursing content. The purpose of this study was to classify ICNP nursing diagnoses using the 21 Care Components of the CCC as a conceptual framework to facilitate usability and inter-operability of nursing diagnoses in electronic health records. Findings resulted in all 521 ICNP diagnoses being assigned to one of the 21 CCC Care Components. Further research is needed to validate the resulting product of this study with practitioners and develop recommendations for improvement of both terminologies.

Identifying Care Coordination Interventions Provided to Community-Dwelling Older Adults Using Electronic Health Records.

Although care coordination is a popular intervention, there is no standard method of delivery. Also little is known about who benefits most, or characteristics that predict the amount of care coordination needed, especially with chronically ill older adults. The purpose of this study was to identify types and amount of nurse care coordination interventions provided to 231 chronically ill older adults who participated in a 12-month home care medication management program in the Midwest. For each participant, the nurse care coordinator spent an average of 134 min/mo providing in-person home care, 48 min/mo of travel, and 18 min/mo of indirect care occurring outside the home visit. This accounted for 67.2%, 23.8%, and 9.0% of nursing time, respectively, for home visits, travel, and indirect care. Four of 11 nursing interventions focused on medication management were provided to all participants. Seven of the 11 main interventions were individualized according to each person's special needs. Wide variations were observed in time provided with in-person home care and communications with multiple stakeholders. Study findings indicate the importance of individualizing interventions and the variability in the amount of nursing time needed to provide care coordination to chronically ill older adults.

Toward a Global eHealth Observatory for Nursing.

This poster summarizes a review of existing health observatories and proposes a new entity for nursing. A nursing eHealth observatory would be an authoritative and respected source of eHealth information that would support nursing decision-making and policy development and add to the body of knowledge about professional nursing and client care outcomes.

Harmonizing Nursing Terminologies.

In this paper, the authors report on a study aimed at harmonising two nursing terminologies, the Clinical Care Classification (CCC) and the International Classification for Nursing Practice (ICNP®). As the electronic health record evolves and the need for interoperability extends beyond local and national borders, a degree of standardisation across healthcare terminologies become essential. Harmonising across terminologies results in a) increased consensus relating to domain content and b) improvements in the terminologies involved. Findings from this study suggest that there is much overlap of content in nursing terminologies. The continued harmonisation between nursing terminologies and other healthcare terminologies are recommended to achieve international interoperability.

Modeling a Nursing Guideline with Standard Terminology and Unified Modeling Language for a Nursing Decision Support System: A Case Study.

In recent years, Decision Support Systems (DSSs) have been developed and used to achieve "meaningful use". One approach to developing DSSs is to translate clinical guidelines into a computer-interpretable format. However, there is no specific guideline modeling approach to translate nursing guidelines to computer-interpretable guidelines. This results in limited use of DSSs in nursing. Unified modeling language (UML) is a software writing language known to accurately represent the end-users' perspective, due to its expressive characteristics. Furthermore, standard terminology enabled DSSs have been shown to smoothly integrate into existing health information systems. In order to facilitate development of nursing DSSs, the UML was used to represent a guideline for medication management for older adults encode with the International Classification for Nursing Practice (ICNP®). The UML was found to be a useful and sufficient tool to model a nursing guideline for a DSS.

Recent development of informatics nurses displayed in investigation by US HIMSS / 中华医学图书情报杂志

The status quo of American informatics nurses investigated 4 times by US HIMSS from 2004 to 2014 was analyzed.The following characteristics of American informatics nurses were summarized in terms of their educa-tion level, income, qualification authentication, occupation satisfaction, work experience and duties, including high education level and interdisciplinary background, high income and occupation satisfaction, necessary clinical background, and systematic professional development, which may provide reference for nursing staff in China to have a better understanding of informatics nurse.

Inter-terminology mapping of nursing problems.

PURPOSE: The purpose of this study was to determine the degree of overlap between the International Classification for Nursing Practice (ICNP®) and the Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT), with a specific focus on nursing problems, as a first step towards harmonization of content between the two terminologies. METHODS: Work within this study was divided across two ICNP subsets. The first subset (n=238) was made up of ICNP diagnosis/outcome concepts that had been included in previous experimental mapping activities with Clinical Care Classification (CCC) and NANDA-International (NANDA-I). These ICNP concepts and their equivalent concepts within CCC and NANDA-I were used within the Unified Medical Language System (UMLS) framework to derive automatically candidate mappings to SNOMED-CT for validation by two reviewers. The second subset (n=565) included all other ICNP diagnosis/outcome concepts plus those concepts from the first subset where the candidate mappings were rejected. Mappings from the second subset to SNOMED-CT were manually identified independently by the same two reviewers. Differences between the reviewers were resolved through discussion. The observed agreement between the two reviewers was calculated along with the inter-rater reliability using Cohen's Kappa (κ). RESULTS: For the first semi-automated mapping, according to the two reviewers the great majority of ICNP concepts (91.6%) correctly mapped to SNOMED-CT in UMLS. There was a good level of agreement between the reviewers in this part of the exercise (κ=0.7). For the second manual mapping, nearly two-thirds of ICNP concepts (61.4%) could not be mapped to any SNOMED-CT concept. There was only a moderate level of agreement between the reviewers (κ=0.45). While most of the mappings were one-to-one mappings, there were ambiguities in both terminologies which led to difficulties. The absence of mappings was due to a large extent to differences in content coverage, although lexical variations and semantic differences also played a part. CONCLUSIONS: This study demonstrated a degree of overlap between ICNP and SNOMED-CT; it also identified significant differences in content coverage. The results from the semi-automated mapping were encouraging, particularly for 'older' ICNP content. The results from the manual mapping were less favorable suggesting a need for further enhancement of both terminologies, content development within SNOMED-CT and further research on mechanisms for harmonization.

Palliative care nursing interventions in Thailand.

PURPOSE: This study aimed to describe the nursing interventions that nurses in Thailand identify as most important in promoting dignified dying. DESIGN: This study used a cross-sectional descriptive design. METHOD: A total of 247 Thai nurses completed a paper-and-pencil survey written in Thai. The survey included both demographic questions and palliative care interventions, listed with summative rating scales, from the International Classification for Nursing Practice (ICNP) catalogue Palliative Care for Dignified Dying. Descriptive statistics were used to analyze the data. FINDINGS: The five most important nursing interventions to promote dignified dying, ranked by average importance rating, were (a) maintain dignity and privacy, (b) establish trust, (c) manage pain, (d) establish rapport, and (e) manage dyspnea. CONCLUSIONS: This research identified the palliative care nursing interventions considered most important by nurses in Thailand to promote dignified dying. IMPLICATIONS: The ICNP catalogue Palliative Care for Dignified Dying can be used for planning and managing palliative nursing care in Thailand.

Collaborative development and maintenance of health terminologies.

The quest for a standardized terminology that can meet the varying needs of healthcare practice, and requirements for secondary use, is ongoing. The number of potential users and the number of potential uses for standardized terminologies make collaborative development, rather than the traditional de jure approach, an imperative, and there appears to be significant worldwide interest in this area. In this article we describe an initiative of the International Council of Nurses (ICN), ICNP C-Space (Collaborative Space), which utilized a social media platform to encourage and facilitate global collaborative development of its terminology, the International Classification for Nursing Practice (ICNP(®)). We report on several years of experience of managing the platform and provide valuable lessons on collaborative terminology development. Our experience suggests that web-based platforms such as ICNP C-Space certainly offer the promise of a broader, wider-reaching, and more inclusive community of contributors to the terminology development process. However, there are also potential limitations for which we provide practical recommendations.

Measuring elderly care through the use of a nursing conceptual model and the international classification for nursing practice(®).

INTRODUCTION: Nursing models and terminologies can contribute to research the nature of nursing care. AIM: The aim of this study was to describe nursing diagnoses in acute- and long-term elderly care. METHODS: A point prevalence survey was conducted on 240 patients. The International Classification for Nursing Practice was used to describe nursing diagnoses, and a conceptual model was used to categorize them in nursing needs. RESULTS: A total of 2,673 diagnoses were detected. Mean was higher in nursing home than in hospital (t test =-3.688; p = .0003). Prevalent diagnoses were significantly different. DISCUSSION: High complexity, with different issues for nurses, was observed both in acute- and in long-term settings. CONCLUSION: The results could help to comprehend the nature of older persons needs and could contribute to the development of an International Classification for Nursing Practice catalogue for elderly care.

ICNP Catalogues for supporting nursing content in electronic health records.

The purpose of this study was to describe sets of nursing concepts including, for example, nursing diagnoses and interventions, which are knowledge-based and clinically relevant to support nursing practice. Health information systems using the International Classification for Nursing Practice (ICNP®) provide a platform for standardized nursing documentation for patients' health care, clinical decision support, and repositories for re-use of clinical data for quality evaluation, research, management decisions and policy development. Clinically relevant sets of ICNP concepts can facilitate implementation of health information systems for nursing. Descriptive analysis was used to examine the types of, and relationships among, existing nursing content sets. Findings included the need for various types of content sets, as represented in ICNP catalogues, for nursing documentation. Five types of ICNP Catalogues included Care Plans, Order Sets, Clinical Templates, Nursing Minimum Data Sets, and Terminology Subsets.

Semantic mappings and locality of nursing diagnostic concepts in UMLS.

One solution for enhancing the interoperability between nursing information systems, given the availability of multiple nursing terminologies, is to cross-map existing nursing concepts. The Unified Medical Language System (UMLS) developed and distributed by the National Library of Medicine (NLM) is a knowledge resource containing cross-mappings of various terminologies in a unified framework. While the knowledge resource has been available for the last two decades, little research on the representation of nursing terminologies in UMLS has been conducted. As a first step, UMLS semantic mappings and concept locality were examined for nursing diagnostic concepts or problems selected from three terminologies (i.e., CCC, ICNP, and NANDA-I) along with corresponding SNOMED CT concepts. The evaluation of UMLS semantic mappings was conducted by measuring the proportion of concordance between UMLS and human expert mappings. The semantic locality of nursing diagnostic concepts was assessed by examining the associations of select concepts and the placement of the nursing concepts on the Semantic Network and Group. The study found that the UMLS mappings of CCC and NANDA-I concepts to SNOMED CT were highly concordant to expert mappings. The level of concordance in mappings of ICNP to SNOMED CT, CCC and NANDA-I within UMLS was relatively low, indicating the need for further research and development. Likewise, the semantic locality of ICNP concepts could be further improved. Various stakeholders need to collaborate to enhance the NLM knowledge resource and the interoperability of nursing data within the discipline as well as across health-related disciplines.

Development of the nursing problem list subset of SNOMED CT®.

OBJECTIVE: To create an interoperable set of nursing diagnoses for use in the patient problem list in the EHR to support interoperability. DESIGN: Queries for nursing diagnostic concepts were executed against the UMLS Metathesaurus to retrieve all nursing diagnoses across four nursing terminologies where the concept was also represented in SNOMED CT. A candidate data set was retrieved and included the nursing diagnoses and corresponding SNOMED CT concepts from the UMLS Metathesaurus. The team members identified the concepts that met the semantic selection criteria for inclusion in the nursing problem list. RESULTS: 1320 concepts were returned in the initial UMLS Metathesaurus query of nursing diagnostic concepts. Further analysis was conducted to identify those nursing diagnostic concepts mapped to SNOMED CT and duplicate concepts were removed resulting in 591 unique UMLS Metathesaurus concepts. The query extracted all concepts from two of the nursing terminologies that contained interventions and outcomes. After cleaning the dataset, the final count of SNOMED CT concepts in the nursing problem list subset is 369. CONCLUSIONS: The problem list is a key component of the patient care and has been acknowledged as critical by the EHR Meaningful Use criteria. Nursing diagnoses on the problem list are foundational for constructing a nursing care plan. A multidisciplinary patient problem list will facilitate communication and evaluation of the contribution of nursing care to the patient's clinical care experiences and outcomes.

A dynamic classification approach for nursing.

Nursing has a long tradition of classification, stretching back at least 150 years. The introduction of computers into health care towards the end of the 20(th) Century helped to focus efforts, culminating in the development of a range of standardized classifications. Many of these classifications are still in use today and, while content is periodically updated, the underlying classification structures remain relatively static. In this paper an approach to classification that is relatively new to nursing is presented; an approach that uses formal Web Ontology Language definitions for classes, and computer-based reasoning on those classes, to determine automatically classification structures that more flexibly meet the needs of users. A new proposed classification structure for the International Classification for Nursing Practice is derived under the new approach to provide a new view on the next release of the classification and to contribute to broader quality improvement processes.

Representation of nursing terminologies in UMLS.

There are seven nursing terminologies or classifications that are considered a standard to support nursing practice in the U.S. Harmonizing these terminologies will enhance the interoperability of clinical data documented across nursing practice. As a first step to harmonize the nursing terminologies, the purpose of this study was to examine how nursing problems or diagnostic concepts from select terminologies were cross-mapped in Unified Medical Language System (UMLS). A comparison analysis was conducted by examining whether cross-mappings available in UMLS through concept unique identifiers were consistent with cross-mappings conducted by human experts. Of 423 concepts from three terminologies, 411 (97%) were manually cross-mapped by experts to the International Classification for Nursing Practice. The UMLS semantic mapping among the 411 nursing concepts presented 33.6% accuracy (i.e., 138 of 411 concepts) when compared to expert cross-mappings. Further research and collaboration among experts in this field are needed for future enhancement of UMLS.

Nursing interventions to promote dignified dying in South Korea.

PURPOSE: This descriptive study aimed to assess the appropriateness of the International Classification for Nursing Practice (ICNP) catalogue Palliative Care for Dignified Dying for palliative care nursing interventions in South Korea. METHODS: The study surveyed 213 South Korean nurses who might regularly care for dying patients. Nurses were recruited to complete a survey that included interventions from the ICNP catalogue listed with Likert response sets. FINDINGS: All of the interventions were scored as being at least 'slightly important' on average. The following three nursing interventions were ranked as most important when caring for dying patients: establish trust, establish rapport, and administer pain medication. CONCLUSIONS: The study provides new insights into the palliative care provided in South Korea by documenting nurses' views of what are the most important palliative care nursing interventions. It also suggests that the palliative care interventions listed in the ICNP catalogue Palliative Care for Dignified Dying are in congruence with the interventions that nurses in South Korea use.

Mapping evidence-based guidelines to standardized nursing terminologies.

The purpose of this study was to explore how evidence-based practice recommendations for adults with depression were represented in two standardized nursing terminologies. A qualitative concept analysis was used to answer the research question. Concepts were extracted from the recommendations and matched to two standardized nursing terminologies through lexical and semantic concept mapping techniques. Study findings included variability in the lexical mapping to the standardized terminologies. The ability to map semantically was greater than lexical mapping, but the majority of these were partial matches. Findings also raised concerns about the potential for ambiguity of data retrieved when using standardized terminology.

Toward harmonising WHO International Classifications: a nursing perspective.

The WHO Family of International Classifications (FIC) provides a suite of health classifications to promote data exchange and comparisons worldwide. The International Classification of Functioning, Disabilities and Health (ICF) and the International Classification for Nursing Practice (ICNP) are part of WHO-FIC. This study was designed to examine to what extent the ICF and ICNP could be mapped to facilitate unambiguous communication across health settings and professionals. A total of 946 concepts from ICF were mapped to ICNP primitive concepts. Lexical matches generated by machine were examined to find false positive or additional semantic equivalence. Although the semantic mapping increased the number of exact and partial matches by 13%, only less than half of ICF concepts (46%) were able to be mapped to ICNP concepts. ICF concepts were more granular than ICNP concepts in the area of human functioning and body structures. Major challenges in mapping the two classifications resulted from differences in the terminology structure, concept representation and content specificity. A reference terminology model was useful to the mapping effort. The study findings support ongoing advancement in the area of harmonisation of healthcare terminologies. Applications that blend the use of ICF and ICNP concepts in practice should be further tested.

Mapping ICNP Version 1 concepts to SNOMED CT.

The purpose of this study is to evaluate the ability of SNOMED CT to represent concepts of the ICNP Version 1 - the 7-Axis model. We selected the 1568 concepts of the ICNP 7-Axis model. From January 2007 through June 2007, the first author mapped the ICNP Version 1 concepts to the SNOMED CT using CLUE browser 5.0. The second author from the SNOMED Terminology Solutions and the third author from the ICN validated mapping result. In total, SNOMED CT covered 1381 concepts of 1658 (83%) ICNP 7-Axis model concepts ranging from 65% coverage rate of the Actions Axis concepts to 94% coverage rate of the Judgment Axis concepts. SNOMED CT can represent most (83%) of the ICNP Version 1 concepts. Improvements in ICNP Version 1 in terms of concept naming and definition, and adding missing concepts to the SNOMED CT would lead to greater coverage of the ICNP Version 1 concepts.