Mapping Perinatal Nursing Process Measurement Concepts to Standard Terminologies

A State-of-the Art Review of SNOMED CT Terminology Binding and Recommendations for Practice and Research

BACKGROUND

Unambiguous sharing of data requires information models and terminology in combination, but there is a lack of knowledge as to how they should be combined, leading to impaired interoperability.

OBJECTIVES

To facilitate creation of guidelines for SNOMED CT terminology binding we have performed a literature review to find existing recommendations and expose knowledge gaps. The primary audience is practitioners and researchers working with terminology binding.

METHODS

PubMed, Scopus, and Web of Science were searched for papers containing "terminology binding," "subset," "map," "information model" or "implement" and the term "SNOMED."

RESULTS

The search yielded 616 unique papers published from 2004 to 2020, from which 55 papers were selected and analyzed inductively. Topics described in the papers include problems related to input material, SNOMED CT, information models, and lack of appropriate tools as well as recommendations regarding competence.

CONCLUSION

Recommendations are given for practitioners and researchers. Many of the stated problems can be solved by better co-operation between domain experts and informaticians and better knowledge of SNOMED CT. Settings where these competences either work together or where staff with knowledge of both act as brokers are well equipped for terminology binding. Tooling is not thoroughly researched and might be a possible way to facilitate terminology binding.

SNOMED-CT as a standardized language system model for nursing: an integrative review

OBJECTIVE

To describe the use of the Systematized Nomenclature of Medicine - Clinical Terms (SNOMED-CT) as a model for interoperability of the nursing terminology in the national and international contexts.

METHODS

This is an integrative literature review according to Cooper, which searched for articles in Portuguese, English and Spanish, published between September 2011 and November 2018 in the BVS, PubMed, SCOPUS, CINAHL, EMBASE, and Web of Science databases, ending in a sample of 15 articles.

RESULTS

The SNOMED-CT is a multi-professional nomenclature used by nursing in different care contexts, being associated with other standardized languages of the discipline, such as ICNP®, NANDA-I, and the Omaha System.

CONCLUSION

This review has shown that the use of SNOMED- CT is incipient in the national context, justifying the need to develop studies aimed at mapping the interoperability of existing systems of standardized language, especially NANDA-I, ICNP and Omaha System, in order to adapt the implementation of SNOMED-CT.

The use of SNOMED CT, 2013-2020: a literature review

OBJECTIVE

This article reviews recent literature on the use of SNOMED CT as an extension of Lee et al's 2014 review on the same topic. The Lee et al's article covered literature published from 2001-2012, and the scope of this review was 2013-2020.

MATERIALS AND METHODS

In line with Lee et al's methods, we searched the PubMed and Embase databases and identified 1002 articles for review, including studies from January 2013 to September 2020. The retrieved articles were categorized and analyzed according to SNOMED CT focus categories (ie, indeterminate, theoretical, pre-development, implementation, and evaluation/commodity), usage categories (eg, illustrate terminology systems theory, prospective content coverage, used to classify or code in a study, retrieve or analyze patient data, etc.), medical domains, and countries.

RESULTS

After applying inclusion and exclusion criteria, 622 articles were selected for final review. Compared to the papers published between 2001 and 2012, papers published between 2013 and 2020 revealed an increase in more mature usage of SNOMED CT, and the number of papers classified in the "implementation" and "evaluation/commodity" focus categories expanded. When analyzed by decade, papers in the "pre-development," "implementation," and "evaluation/commodity" categories were much more numerous in 2011-2020 than in 2001-2010, increasing from 169 to 293, 30 to 138, and 3 to 65, respectively.

CONCLUSION

Published papers in more mature usage categories have substantially increased since 2012. From 2013 to present, SNOMED CT has been increasingly implemented in more practical settings. Future research should concentrate on addressing whether SNOMED CT influences improvement in patient care.

Mapping frailty concepts to SNOMED CT

BACKGROUND

Frailty is considered an emerging syndrome characterized by a decrease in physiological ability to respond to stressors, leading to increased morbidity and mortality rates. Frailty is distinguished from normal age-associated decline because it is a sharp and often rapid decline rather than a gradual slowing down of general functioning. The comprehensive geriatric assessment is currently considered the gold standard for identifying frailty in older adults. The electronic version of this tool is called the eCGA and is commonly included in electronic medical records (EMR) in primary care settings.

OBJECTIVES

We explored the adequacy of SNOMED CT to represent frailty concepts by addressing three research questions: 1) What are the defining characteristics of frailty most commonly used in frailty assessment tools? 2) Are these characteristics captured within one or many frailty assessment tools? 3) Which data elements from existing tool(s) can be reliably mapped to existing SNOMED CT terms?

METHODS

We conducted a literature search to explore the defining characteristics of frailty and the most commonly used assessment tools. We compared these findings to the components of frailty captured within the eCGA. We then used a descriptive study design to manually map concepts from the eCGA to SNOMED CT.

RESULTS

Our literature review demonstrated that the eCGA contains all common defining characteristics of frailty. Unique assessment questions from the eCGA (n = 133) were manually mapped to SNOMED CT, using expert consensus. Of these, 72 % were direct matches, 17 % were one-to-many matches, and the remaining 11 % were non-matches. Two rounds of expert clinician mapping occurred; inter-rater reliability between the two clinicians was 0.75 (kappa).

CONCLUSIONS/IMPLICATIONS

The resulting list of mapped eCGA elements to SNOMED CT terms can inform revisions to existing chronic disease databases to include frailty monitoring and surveillance.

ISO/TR 12300:2016 for clinical cross-terminology mapping: contribution to nursing

This theoretical and reflective study aimed to assess the contribution of the ISO/TR 12300:2016 document for the mapping of nursing terminology. The referred document and related articles were used as an empirical framework. The study analyzed the content of the document, highlighting cardinality and equivalence principles. The standard presents conceptual and operational basis for mapping, with cardinality and equivalence as the support for the categorization of cross-terminology mapping in the area of nursing. Cardinality verifies candidate target terms to represent the source term, while the equivalence degree scale checks semantic correspondence. Among the principles included in the ISO/TR 12300:2016, cardinality and equivalence contribute to the accurate representation of the results of the cross-terminology mapping process and its use should decrease inconsistencies.

Comparison of the Results of Manual and Automated Processes of Cross-Mapping Between Nursing Terms: Quantitative Study

Background

Cross-mapping establishes equivalence between terms from different terminology systems, which is useful for interoperability, updated terminological versions, and reuse of terms. Due to the number of terms to be mapped, this work can be extensive, tedious, and thorough, and it is susceptible to errors; this can be minimized by automated processes, which use computational tools.

Objective

The aim of this study was to compare the results of manual and automated term mapping processes.

Methods

In this descriptive, quantitative study, we used the results of two mapping processes as an empirical basis: manual, which used 2638 terms of nurses’ records from a university hospital in southern Brazil and the International Classification for Nursing Practice (ICNP); and automated, which used the same university hospital terms and the primitive terms of the ICNP through MappICNP, an algorithm based on rules of natural language processing. The two processes were compared via equality and exclusivity assessments of new terms of the automated process and of candidate terms.

Results

The automated process mapped 569/2638 (21.56%) of the source bank’s terms as identical, and the manual process mapped 650/2638 (24.63%) as identical. Regarding new terms, the automated process mapped 1031/2638 (39.08%) of the source bank’s terms as new, while the manual process mapped 1251 (47.42%). In particular, manual mapping identified 101/2638 (3.82%) terms as identical and 429 (16.26%) as new, whereas the automated process identified 20 (0.75%) terms as identical and 209 (7.92%) as new. Of the 209 terms mapped as new by the automated process, it was possible to establish an equivalence with ICNP terms in 48 (23.0%) cases. An analysis of the candidate terms offered by the automated process to the 429 new terms mapped exclusively by the manual process resulted in 100 (23.3%) candidates that had a semantic relationship with the source term.

Conclusions

The automated and manual processes map identical and new terms in similar ways and can be considered complementary. Direct identification of identical terms and the offering of candidate terms through the automated process facilitate and enhance the results of the mapping; confirmation of the precision of the automated mapping requires further analysis by researchers.

Embedding Nursing Interventions into the World Health Organization's International Classification of Health Interventions (ICHI)

OBJECTIVE

The International Classification of Health Interventions, currently being developed, 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 2-phase content mapping method was used: (1) three coders independently applied the classification to a dataset 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.