Embedding nursing interventions into the World Health Organization’s International Classification of Health Interventions (ICHI)

Objective: The International Classification of Health Interventions (ICHI) is currently being developed. ICHI seeks to span all sectors of the health system. Our objective was to test the draft classification’s coverage of interventions commonly delivered by nurses, and propose changes to improve the utility and reliability of the classification for aggregating and analyzing data on nursing interventions. Materials and methods: A two-phase content mapping method was used: (1) three coders independently applied the classification to a data set comprising 100 high-frequency nursing interventions; (2) the coders reached consensus for each intervention and identified reasons for initial discrepancies. Results: A consensus code was found for 80 of the 100 source terms: for 34% of these the code was semantically equivalent to the source term, and for 64% it was broader. Issues that contributed to discrepancies in Phase 1 coding results included concepts in source terms not captured by the classification, ambiguities in source terms, and uncertainty of semantic matching between ‘action’ concepts in source terms and classification codes. Discussion: While the classification generally provides good coverage of nursing interventions, there remain a number of content gaps and granularity issues. Further development of definitions and coding guidance is needed to ensure consistency of application. Conclusion: This study has produced a set of proposals concerning changes needed to improve the classification. The novel method described here will inform future health terminology and classification content coverage studies

Clinical coverage of an archetype repository over SNOMED-CT

AbstractClinical archetypes provide a means for health professionals to design what should be communicated as part of an Electronic Health Record (EHR). An ever-growing number of archetype definitions follow this health information modelling approach, and this international archetype resource will eventually cover a large number of clinical concepts. On the other hand, clinical terminology systems that can be referenced by archetypes also have a wide coverage over many types of health-care information.No existing work measures the clinical content coverage of archetypes using terminology systems as a metric. Archetype authors require guidance to identify under-covered clinical areas that may need to be the focus of further modelling effort according to this paradigm.This paper develops a first map of SNOMED-CT concepts covered by archetypes in a repository by creating a so-called terminological Shadow. This is achieved by mapping appropriate SNOMED-CT concepts from all nodes that contain archetype terms, finding the top two category levels of the mapped concepts in the SNOMED-CT hierarchy, and calculating the coverage of each category. A quantitative study of the results compares the coverage of different categories to identify relatively under-covered as well as well-covered areas. The results show that the coverage of the well-known National Health Service (NHS) Connecting for Health (CfH) archetype repository on all categories of SNOMED-CT is not equally balanced. Categories worth investigating emerged at different points on the coverage spectrum, including well-covered categories such as Attributes, Qualifier value, under-covered categories such as Microorganism, Kingdom animalia, and categories that are not covered at all such as Cardiovascular drug (product)

Representing and Retrieving Patients\u27 Falls Risk Factors and Risk for Falls Among Adults in Acute Care Through the Electronic Health Record

Defining fall risk factors and predicting fall risk status among patients in acute care has been a topic of research for decades. With increasing pressure on hospitals to provide quality care and prevent hospital-acquired conditions, the search for effective fall prevention interventions continues. Hundreds of risk factors for falls in acute care have been described in the literature. However, due to variations in the terms utilized to represent each fall risk factor, an effort to compare findings across settings and replicate research is hampered. As the expectations for the effective use of electronic health records increase, an opportunity exists to create infrastructure within clinical information systems, constructed with evidence-based knowledge and standardized terms, that will support interoperability between systems and enable comparative research. The purpose of this study is to identify to what extent selected fall risk factors and the problem, `risk for falls\u27 are represented and retrievable, in patients\u27 electronic health record, in one acute care setting. Specifically, this study sought to answer three questions: 1) How can the selected fall risk factors and the problem, `risk for falls\u27 be represented through selected standardized terminologies? 2) How are the selected fall risk factors and problem, `risk for falls\u27 represented in a clinical information system? and 3) Which of the selected fall risk factors and problem, `risk for falls\u27 can be retrieved from the electronic health record? The study was guided by the Knowledge Based Nursing Initiative (KBNI) framework. The study was conducted at a local health system within the hospital division, utilizing electronic, patient clinical data. Five selected fall risk factors and the problem, `risk for falls,\u27 were mapped to five standardized terminologies utilizing lexical matching. The terms mapped from the five terminologies were compared to the terms, located in discrete fields within the study site\u27s clinical information system. In addition to SNOMED CT and ICD-9 CM terms, a mixture of vendor and site-specific terms that represented the problem, `risk for falls,\u27 and the five selected fall risk factors were located in the study site\u27s clinical information system. The mapped ICD-9 CM terms and fourteen of the twenty-two SNOMED CT terms were located in the `Problem List\u27 and `Medical History\u27 sections of the clinical information system, while the vendor and site-specific terms were located in `Orders,\u27 `Nursing Flow Sheet,\u27 and `Rehabilitation Flow Sheet\u27 sections. Although both the ICD-9 CM and SNOMED CT terminologies were visible to the clinicians, one of the two mapped SNOMED CT terms representing the problem, `risk for falls,\u27 and fourteen of the twenty-two mapped fall risk factors were not visible because they did not correspond to ICD-9 CM terms. Site-specific terms representing `cognitive impairment\u27 and `impaired gait\u27 were located in both the `Nursing Flow Sheet\u27 and `Rehabilitation Flow Sheet\u27 section. While the terms were lexically similar, the terms were not exact matches and the machine-readable codes differed.Data recorded in 995 episodes of care were retrieved from the electronic data warehouse for analysis. While the SNOMED CT terms were not available for retrieval from the electronic data warehouse, the ICD-9 CM, vendor, and site-specific terms were available. As there were not SNOMED CT terms available for retrieval from the electronic data warehouse, the representation of the problem, `risk for falls,\u27 was not retrievable as a standardized term; however, it was retrieved as a Morse Fall Scale score of 40 or greater among 64.7% of the sample. The percentage of the five fall risk factors represented with the ICD-9 CM terms was lower than the percentage of fall risk factors represented with vendor and site-specific terms. While it is promising that two standardized terminologies have been embedded in the study site\u27s system, limiting the SNOMED CT terms to those that have corresponding ICD-9 terms limits the representation of both the problem, `risk for falls,\u27 and the five selected fall risk factors. It is recommended that hospital administrators embed standardized terminologies in their entirety to allow for adequate representation of terms. Accepting terminologies in their entirety would allow for interoperability between health systems and enable comparative research. Additionally, if vendor and site-specific terms are embedded, clinical information analysts in partnership with clinicians should assure that terms representing the same clinical data (e.g., disorientation), match across different sections of the clinical information system or a cross-mapping of those terms exist in order to support interoperability within the system

SNOMED-CT como modelo de sistema de linguagem padronizada à enfermagem: revisão integrativa

RESUMOObjetivo: Descrever a utilização do Systematized Nomenclature of Medicine – Clinical Terms (SNOMED-CT) como modelo de interoperabilidade das terminologias da enfermagem no contexto nacional e internacional.Metodologia: Trata-se de revisão integrativa da literatura segundo Cooper, que buscou artigos em português, inglês e espanhol, publicados entre setembro de 2011 a novembro de 2018 nas bases de dados BVS, PubMed, SCOPUS, CINAHL, EMBASE e Web of Science, finalizando em uma amostra de 15 artigos.Resultados: O SNOMED-CT é uma nomenclatura multiprofissional utilizada pela enfermagem em diferentes contextos de cuidado, sendo associada com outras linguagens padronizadas da disciplina, como CIPE®, NANDA-I e Omaha System.Conclusão: Esta revisão mostrou que o uso do SNOMED-CT é incipiente no contexto nacional, justificando a necessidade de desenvolvimento de estudos visando o mapeamento dos sistemas de linguagem padronizadas existentes, especialmente a NANDA-I, CIPE® e Omaha System, para fins de adequar a implementação do SNOMED-CT.Palavras-chave: Informática em enfermagem. Terminologia padronizada em enfermagem. Systematized Nomenclature of Medicine. Classificação. Interoperabilidade da informação em saúde

Nursing Terminologies as Evolving Large-Scale Information Infrastructures

This paper describes the slowly evolving nature of large-scale terminology-based information infrastructures. The strategic aim of implementing standardized terminologies is to share and compare information within and across domain-specific and organizational boundaries. We are particularly interested in working classification systems focused on specific domains’ and classes, and even more specifically in reference terminologies with the capability to interconnect different existing classification systems. We examine this empirically through a threefold case based on data from three Norwegian university hospitals, where we also track a national recommendation of a reference terminology. The reference terminology, which was initially promoted as a means to achieve integration and harmonization, is increasingly perceived as competing with other terminologies. This “gateway” has been presented as a purely technical and politically neutral system, but may be more complex in reality: such integration processes require considerable adaptations, negotiations, and manual maintenance

Doctor of Philosophy

dissertationThe problem of information transfer between healthcare sectors and across the continuum of care was examined using a mixed methods approach. These methods include qualitative interviews, retrospective case reviews and an informatic gap analysis. Findings and conclusions are reported for each study. Qualitative interviews were conducted with 16 healthcare representatives from 4 disciplines (medicine, pharmacy, nursing, and social work) and 3 healthcare sectors (hospital, skilled nursing care and community care). Three key themes from a Joint Cognitive Systems theoretical model were used to examine qualitative findings. Agreement on cross-sector care goals is neither defined nor made explicit and in some instances working at cross purposes. Care goals and information paradigms change as patients move from hospitalbased crisis stabilization, diagnosis and treatment to a postdischarge care to home or skilled nursing recovery, function restoration, or end of life support. Control of the transfer process is variable across institutions with little feedback and feed-forward. Lack of knowledge, competency and information tracking threatens sector interdependencies with suspicion and distrust. Sixty-three patients discharged between 2006 and 2008 from hospitals to skilled nursing facilities were randomly selected and reviewed. Most notably missing are discharge summaries (30%), nursing assessments or notes (17%), and social work documents (25%). Advanced directives or living wills necessary for end of life support were present in only 6% of the cases. The presence of information on activities of daily living (ADLs), other disabling conditions, and nutrition was associated with positive outcomes at the 0.001, 0.04 and 0.08levels. Consistent geriatric information transfer across the continuum is needed for relevant care management. An interoperability gap analysis conducted on the LINC (Linking Information Necessary for Care) transfer form determined its interoperability to be the semantic level 0. Detailed Clinical Models representing care management processes are challenged by the lack of consensus in terminology standards across sectors. Construction of information transfer solutions compliant with the Centers of Medicare and Medicaid Services (CMS) Stage 2 meaningful use criteria must address syntactic and semantic standards, map sector terminologies within care management processes, and account for the lack of standard terminologies in allied health domains