An evaluation of the usefulness of two terminology models for integrating nursing diagnosis concepts into SNOMED Clinical Terms

The case for expressing nursing theories using ontologies

Nursing and informatics share a common strength in their use of structured representations of domains, specifically the underlying notion of 'things' (ie, concepts, constructs, or named entities) and the relationships among those things. Accurate representation of nursing knowledge in machine-interpretable formats is a necessary next step for leveraging contemporary technologies. Expressing validated nursing theories in ontologies, and in particular formal ontologies, would serve not only nursing, but also investigators from other domains, clinical information system developers, and the users of advanced technologies such as artificial intelligence that seek to learn from the real-world data and evidence generated by nurses and others. Such efforts will enable sharing knowledge and conceptualizations about phenomena across the domains of nursing and generating, testing, revising, and providing theoretically-based perspectives when leveraging contemporary technologies. Nursing is well situated for this work, leveraging intentional and focused collaborations among nurse informaticists, scientists, and theorists.

Physician nurse care: A new use of UMLS to measure professional contribution: Are we talking about the same patient a new graph matching algorithm?

BACKGROUND

Physician and nurses have worked together for generations; however, their language and training are vastly different; comparing and contrasting their work and their joint impact on patient outcomes is difficult in light of this difference. At the same time, the EHR only includes the physician perspective via the physician-authored discharge summary, but not nurse documentation. Prior research in this area has focused on collaboration and the usage of similar terminology.

OBJECTIVE

The objective of the study is to gain insight into interprofessional care by developing a computational metric to identify similarities, related concepts and differences in physician and nurse work.

METHODS

58 physician discharge summaries and the corresponding nurse plans of care were transformed into Unified Medical Language System (UMLS) Concept Unique Identifiers (CUIs). MedLEE, a Natural Language Processing (NLP) program, extracted "physician terms" from free-text physician summaries. The nursing plans of care were constructed using the HANDS© nursing documentation software. HANDS© utilizes structured terminologies: nursing diagnosis (NANDA-I), outcomes (NOC), and interventions (NIC) to create "nursing terms". The physician's and nurse's terms were compared using the UMLS network for relatedness, overlaying the physician and nurse terms for comparison. Our overarching goal is to provide insight into the care, by innovatively applying graph algorithms to the UMLS network. We reveal the relationships between the care provided by each professional that is specific to the patient level.

RESULTS

We found that only 26% of patients had synonyms (identical UMLS CUIs) between the two professions' documentation. On average, physicians' discharge summaries contain 27 terms and nurses' documentation, 18. Traversing the UMLS network, we found an average of 4 terms related (distance less than 2) between the professions, leaving most concepts as unrelated between nurse and physician care.

CONCLUSION

Our hypothesis that physician's and nurse's practice domains are markedly different is supported by the preliminary, quantitative evidence we found. Leveraging the UMLS network and graph traversal algorithms, allows us to compare and contrast nursing and physician care on a single patient, enabling a more complete picture of patient care. We can differentiate professional contributions to patient outcomes and related and divergent concepts by each profession.

Standardizing Physiologic Assessment Data to Enable Big Data Analytics

Disparate data must be represented in a common format to enable comparison across multiple institutions and facilitate Big Data science. Nursing assessments represent a rich source of information. However, a lack of agreement regarding essential concepts and standardized terminology prevent their use for Big Data science in the current state. The purpose of this study was to align a minimum set of physiological nursing assessment data elements with national standardized coding systems. Six institutions shared their 100 most common electronic health record nursing assessment data elements. From these, a set of distinct elements was mapped to nationally recognized Logical Observations Identifiers Names and Codes (LOINC®) and Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT®) standards. We identified 137 observation names (55% new to LOINC), and 348 observation values (20% new to SNOMED CT) organized into 16 panels (72% new LOINC). This reference set can support the exchange of nursing information, facilitate multi-site research, and provide a framework for nursing data analysis.

Implications for Nursing Research and Generation of Evidence

A sound informatics infrastructure is essential to optimise the application of evidence in nursing practice. A comprehensive review of the infrastructure and associated research methods is supported by an extensive resource of references to point the interested reader to further resources for more in depth study. Information and communication technology (ICT) has been recognized as a fundamental component of applying evidence to practice for several decades. Although the role of ICT in generating knowledge from practice was formally identified as a nursing informatics research priority in the early 1990s (NINR Priority Expert Panel on Nursing Informatics, 1993), it has received heightened interest recently. In this chapter, the authors summarize some important trends in research that motivate increased attention to practice-based generation of evidence. These include an increased emphasis on interdisciplinary, translational, and comparative effectiveness research; novel research designs; frameworks and models that inform generation of evidence from practice; and creation of data sets that include not only variables related to biological and genetic measures, but also social and behavioral variables. The chapter also includes an overview of the ICT infrastructure and informatics processes required to facilitate generation of evidence from practice and across research studies: (1) information structures (e.g., re-usable concept representations, tailored templates for data acquisition), (2) processes (e.g., data mining algorithms, natural language processing), and (3) technologies (e.g., data repositories, visualization tools that optimize cognitive support). In addition, the authors identify key knowledge gaps related to informatics support for nursing research and generation of evidence from practice.

Exploring the usability of the ISO reference terminology model for nursing actions in representing oriental nursing actions

PURPOSE

This study examined the extent to which the ISO reference terminology model for nursing actions represents oriental nursing actions in a computerized nursing documentation system to share data and foster communication between oriental nursing care and conventional nursing care.

METHODS

The narrative nursing notes of 545 patients retrieved from a nursing documentation system in an oriental medicine teaching hospital were analyzed. Among 49,118 entries, 933 were recorded as nursing actions. Each entry was decomposed in a set of single statements. A total of 1209 nursing action statements were derived and mapped to the components of the model. These processes were reviewed and validated by two domain experts and a nursing terminology expert.

RESULTS

All of the oriental nursing actions documented contained a word or phrase that described the Action and Target in the model. The Recipient of Care was expressed explicitly in 1.2% of statements. The most frequently used Action terms were 'administering' (19.7%), 'teaching' (16.5%), and 'explaining' (13.6%). The Target terms that indicated unique oriental nursing concepts included 'Sasang constitution differentiation', 'removal of acupuncture needles', 'herb moxibustion', 'oriental massage', and 'oriental medication'.

CONCLUSION

The findings demonstrate that oriental nursing actions can be represented using the ISO reference terminology model for nursing actions. Further specification of the components of the model will be useful to achieve consistent mapping across different settings. The addition of component qualifiers should also be taken into consideration to describe nursing actions at a more granular level.

A nursing informatics research agenda for 2008-18: contextual influences and key components

The context for nursing informatics research has changed significantly since the National Institute of Nursing Research-funded Nursing Informatics Research Agenda was published in 1993 and the Delphi study of nursing informatics research priorities reported a decade ago. The authors focus on 3 specific aspects of context--genomic health care, shifting research paradigms, and social (Web 2.0) technologies--that must be considered in formulating a nursing informatics research agenda. These influences are illustrated using the significant issue of healthcare associated infections (HAI). A nursing informatics research agenda for 2008-18 must expand users of interest to include interdisciplinary researchers; build upon the knowledge gained in nursing concept representation to address genomic and environmental data; guide the reengineering of nursing practice; harness new technologies to empower patients and their caregivers for collaborative knowledge development; develop user-configurable software approaches that support complex data visualization, analysis, and predictive modeling; facilitate the development of middle-range nursing informatics theories; and encourage innovative evaluation methodologies that attend to human-computer interface factors and organizational context.

The adequacy of ICNP version 1.0 as a representational model for electronic nursing assessment documentation

OBJECTIVES

The purpose of this study was to evaluate the adequacy of the International Classification of Nursing Practice (1) (ICPN) Version 1.0 as a representational model for nursing assessment documentation.

DESIGN AND MEASUREMENTS

To identify representational requirements of nursing assessments, the authors mapped key concepts and semantic relations extracted from standardized and local nursing admission assessment documentation forms/templates and inpatient admission assessment records to the ICNP. Next, they expanded the list of ICNP semantic relations with those obtained from the admission assessment forms/templates. The expanded ICNP semantic relations were then validated against the semantic relations identified from an additional set of admission assessment records and a set of 300 randomly selected North American Nursing Diagnosis Association defining characteristic phrases. The concept coverage of the ICNP was evaluated by mapping the concepts extracted from these sources to the ICNP concepts. The UMLS Methathesaurus was then used to map concepts without exact matches to other American Nursing Association (ANA) recognized terminologies.

RESULTS

The authors found that along with the 30 existing ICNP semantic relations, an additional 17 are required for the ICNP to function as a representational model for nursing assessment documentation. Eight hundred and five unique assessment concepts were extracted from all sources. Forty-three percent of these unique assessment concepts had exact matches in the ICNP. An additional 20% had matches in the ICNP classified as narrower, broader, or "other." Of the concepts without exact matches in the ICNP, 81% had exact matches found in other ANA recognized terminologies.

CONCLUSIONS

The broad concept coverage and the logic-based structure of the ICNP make it a flexible and robust standard. The ICNP provides a framework from which to capture and reuse atomic level data to facilitate evidence-based practice.

Interpretation of an international terminology standard in the development of a logic-based compositional terminology

PURPOSE

Version 1.0 of the International Classification for Nursing Practice (ICNP) is a logic-based compositional terminology. International Organization for Standardization (ISO) 18104:2003 Health Informatics-Integration of a reference terminology model for nursing is an international standard to support the development, testing and implementation of nursing terminologies.

METHODS

This study examines how ISO 18104:2003 has been interpreted in the development of ICNP Version 1.0 by identifying mappings between ICNP and the ISO standard. Representations of diagnostic and interventional statements within ICNP are also analyzed according to the requirements mandated by the ISO standard.

RESULTS

All structural components of ISO 18104:2003 i.e. semantic categories, semantic domains, qualifiers and semantic links are represented either directly or in interpreted form within ICNP. The formal representations within ICNP of diagnostic and interventional statements meet the requirement of the ISO standard.

CONCLUSIONS

The findings of this study demonstrate that ICNP Version 1.0 conforms to ISO 18104:2003. More importantly perhaps, this study provides practical examples of how components of a terminology standard might be interpreted and it examines how such a standard might be used to support the definition of high-level schemata in developing logic-based compositional terminologies.

Variation of SNOMED CT coding of clinical research concepts among coding experts

OBJECTIVE

To compare consistency of coding among professional SNOMED CT coders representing three commercial providers of coding services when coding clinical research concepts with SNOMED CT.

DESIGN

A sample of clinical research questions from case report forms (CRFs) generated by the NIH-funded Rare Disease Clinical Research Network (RDCRN) were sent to three coding companies with instructions to code the core concepts using SNOMED CT. The sample consisted of 319 question/answer pairs from 15 separate studies. The companies were asked to select SNOMED CT concepts (in any form, including post-coordinated) that capture the core concept(s) reflected in the question. Also, they were asked to state their level of certainty, as well as how precise they felt their coding was.

MEASUREMENTS

Basic frequencies were calculated to determine raw level agreement among the companies and other descriptive information. Krippendorff's alpha was used to determine a statistical measure of agreement among the coding companies for several measures (semantic, certainty, and precision).

RESULTS

No significant level of agreement among the experts was found.

CONCLUSION

There is little semantic agreement in coding of clinical research data items across coders from 3 professional coding services, even using a very liberal definition of agreement.

Cross-Mapping Between Three Terminologies With the International Standard Nursing Reference Terminology Model

PURPOSE

The International Standards Organization's (ISO) International Standard IS 18104 should assist the nursing profession to integrate their terminologies into computer systems and healthcare reference terminologies. The purpose of this study is to cross-map between different terminologies; that is, to determine if concepts in one terminology are similar to concepts in another terminology.

METHODS

The ISO standard was used to test the degree to which three terminologies could be cross-mapped to each other. Concepts and terms were selected, their equivalence determined by experts, and the specific concepts were dissected or broken down to their constituent parts.

RESULTS

Based on experts' selections from the three classifications, equivalent concepts were identified. Those concepts deemed equivalent were dissected, thus revealing whether the components of the nursing diagnostic concepts such as focus, judgment, and other attributes of the ISO standard matched. Based on the dissection of each diagnosis, the decision was made whether mapping was possible or not.

CONCLUSIONS

The dissection revealed that several nursing diagnostic concepts can easily be interchanged, while others cannot or can be mapped only for specific purposes (e.g., clinical or aggregate use). This implies that for some concepts it does not matter which terminology is used, and in other cases it does because of different meanings.

Improving the Human Readability of Arden Syntax Medical Logic Modules Using a Concept-oriented Terminology and Object-oriented Programming Expressions

Medical logic modules are a procedural representation for sharing task-specific knowledge for decision support systems. Based on the premise that clinicians may perceive object-oriented expressions as easier to read than procedural rules in Arden Syntax-based medical logic modules, we developed a method for improving the readability of medical logic modules. Two approaches were applied: exploiting the concept-oriented features of the Medical Entities Dictionary and building an executable Java program to replace Arden Syntax procedural expressions. The usability evaluation showed that 66% of participants successfully mapped all Arden Syntax rules to Java methods. These findings suggest that these approaches can play an essential role in the creation of human readable medical logic modules and can potentially increase the number of clinical experts who are able to participate in the creation of medical logic modules. Although our approaches are broadly applicable, we specifically discuss the relevance to concept-oriented nursing terminologies and automated processing of task-specific nursing knowledge.

Use of SNOMED CT to represent clinical research data: a semantic characterization of data items on case report forms in vasculitis research

OBJECTIVE

To estimate the coverage provided by SNOMED CT for clinical research concepts represented by the items on case report forms (CRFs), as well as the semantic nature of those concepts relevant to post-coordination methods.

DESIGN

Convenience samples from CRFs developed by rheumatologists conducting several longitudinal, observational studies of vasculitis were selected. A total of 17 CRFs were used as the basis of analysis for this study, from which a total set of 616 (unique) items were identified. Each unique data item was classified as either a clinical finding or procedure. The items were coded by the presence and nature of SNOMED CT coverage and classified into semantic types by 2 coders.

MEASUREMENTS

Basic frequency analysis was conducted to determine levels of coverage provided by SNOMED CT. Estimates of coverage by various semantic characterizations were estimated.

RESULTS

Most of the core clinical concepts (88%) from these clinical research data items were covered by SNOMED CT; however, far fewer of the concepts were fully covered (that is, where all aspects of the CRF item could be represented completely without post-coordination; 23%). In addition, a large majority of the concepts (83%) required post-coordination, either to clarify context (e.g., time) or to better capture complex clinical concepts (e.g., disease-related findings). For just over one third of the sampled CRF data items, both types of post-coordination were necessary to fully represent the meaning of the item.

CONCLUSION

SNOMED CT appears well-suited for representing a variety of clinical concepts, yet is less suited for representing the full amount of information collected on CRFs.

An ontological approach to support the description of nursing practice in Japan with the ICNP

BACKGROUND

With increasing computerization of nursing records in Japan, standardization of nursing terminology is becoming imperative. Although some efforts have been made to formalize description of nursing practice in Japan with the International Classification of Nursing Practice (ICNP), lack of effective description tools has impacted negatively on the initiatives.

PURPOSE

To develop and evaluate an ontological approach that could be used to facilitate the description of nursing practice in Japan with the ICNP.

METHODOLOGY

An ontology-based support system was developed using Protégé-2000, mainly by the following three steps: (1) representing a standard classification of nursing practice (the Nursing Master) in Japan; (2) representing a Japanese version of the ICNP; (3) designing an ontology-based framework. A heuristic matching algorithm was developed to automatically match the action labels in the Nursing Master with the terms of the eight axes of the ICNP Nursing Actions Classification. A preliminary evaluation was performed to examine the usefulness of the system.

RESULTS

High hit rate was shown on the ICNP axes ActionType, Target, and Location. The evaluation indicated that 51.7+/-5.8% (mean+/-S.D.) of the action labels with only one action type were properly matched, and that in 80+/-4% (mean+/-S.D.) of action labels with more than one action type, at least one valid action type was matched correctly.

CONCLUSION

The ontology-based approach using a frame-based knowledge representation system (e.g., Protégé-2000) is useful for supporting the formal description of nursing practice in Japan with the ICNP.

Developing terminology for documenting perioperative nursing interventions

OBJECTIVE

To develop terminology for documenting perioperative nursing interventions.

METHOD

Nursing documentation of 250 patients was explored by content analysis. The study was conducted to validate further the Perioperative Nursing Data Set (PNDS) in Finland. The data included 3442 terms that were clustered into 104 nursing interventions. A Delphi-panel (N=5) evaluated the relevance of each term on a scale from 1 to 4. The structure of each nursing intervention was checked to meet the minimum requirements of the ISO reference terminology model for nursing action concepts. Finally, the nursing interventions were compared with the original PNDS-interventions.

RESULTS

The Delphi-panel accepted 98 nursing interventions with Content Validity Index from 0.88 to 1.0. Of the 133 nursing interventions in the PNDS, 60% (n=80) were covered by nursing interventions identified in this study. A notable portion of the nursing interventions related to preventive aspects of perioperative care and the patients' coping with perioperative experience.

CONCLUSION

The findings supported the need for cross-cultural validation of a nursing language prior to clinical implementation. The ISO reference terminology model is recommended as framework in constructing concepts for nursing interventions in a regular form.

Mapping parish nurse documentation into the nursing interventions classification: a research method

Mapping, or linking like terms that represent the same concept, is a research method increasingly used for testing the reliability and validity of standardized taxonomies. For mapping to be useful, it is critical that the procedure is reliable. One way to maximize reliability is to develop standardized mapping procedures, or rules to follow when linking the terms. This article will present a standardized mapping procedure method in a study that mapped narrative parish nurse documentation (170 health records, 1607 interactions) into the Nursing Interventions Classification (NIC), yielding an intercoder reliability kappa of 0.92. The mapping process identified conceptual issues in the NIC, which also are presented. Because the NIC is included in the Systematic Nomenclature of Medicine of Clinical Terms (SNOMED CT), these conceptual issues raised data aggregation issues in SNOMED CT. Those issues are also presented.

ISO reference terminology models for nursing: applicability for natural language processing of nursing narratives

Natural language processing (NLP) systems have demonstrated utility in parsing narrative texts for purposes such as surveillance and decision support. However, there has been little work related to NLP of nursing narratives. The purpose of this study was to compare the semantic categories of a NLP system (Medical Language Extraction and Encoding [MedLEE] system) with the semantic domains, categories, and attributes of the International Standards Organization (ISO) reference terminology models for nursing diagnoses and nursing actions. All but two MedLEE diagnosis and procedure-related semantic categories mapped to ISO models. In some instances, we found exact correspondence between the semantic structures of MedLEE and the ISO models. In other situations (e.g. aspects of Site or Location), the ISO model was not as granular as MedLEE. For clinical procedure and non-invasive examination, two ISO nursing action model components (Action and Target) mapped to a single MedLEE semantic category. The ISO models are applicable to NLP of nursing narratives. However, the ISO models require additional specification of selected semantic categories for the abstract semantic domains in order to achieve the objective of using NLP to parse and encode data from nursing narratives. Our analysis also suggests areas for extension of MedLEE particularly in regard to represent nursing actions.

Adequacy of evolving national standardized terminologies for interdisciplinary coded concepts in an automated clinical pathway

PURPOSE

The purpose of this analysis was to determine the adequacy of evolving national standardized terminologies with regard to coded data elements (concepts) in an automated clinical pathway designed to drive adherence with the American College of Cardiology (ACC)/American Heart Association (AHA) Guidelines for Evaluation and Management of Chronic Heart Failure.

METHOD

Concepts were identified in a previously developed automated clinical pathway and associated tools. Once identified, concepts were categorized according to the conceptual domains identified by Campbell et al. (1997). A review of evolving national standardized terminologies and coding systems was initiated to determine if the identified concepts had corresponding representation in one of these coding systems. Available codes were then evaluated for adequacy with respect to national guideline adherence measures put forth by the Centers for Medicare/Medicaid Services (CMS) and Joint Commission on Accreditation of Healthcare Organizations (JCAHO).

RESULTS

The concept domain model put forth by Campbell et al. (1997) worked well for organizing concepts and for providing a useful framework for data analysis. Using our method, 260 unique pathway concepts were identified, of which, 91.9% (239) are represented by one or more of the standardized coding systems. Logical Observation Identifiers Names and Codes (LOINC) and SNOMED CT alone represented 86.2% of the concepts. Seventy percent (70%) of the clinical pathway concepts are represented using the Health Insurance Portability and Accountability Act (HIPAA) mandated national terminologies alone. Less than 50% of CMS and JCAHO guideline adherence concepts were found to have representation in the HIPAA mandated terminologies. The addition of Logical Observation Identifier Names and Codes (LOINC) and SNOMED CT improved representation up to 86.4%, but did not include representation of all concepts necessary for complete electronic monitoring of guideline adherence.

CONCLUSIONS

Evolving national standardized terminologies provided matching terms for the majority of the data elements in the automated clinical pathway. Standard clinical terminologies with granular terms such as LOINC and SNOMED CT are required to represent the depth and detail of certain procedures and guideline-based care. Gaps exist in Health Insurance Portability and Accountability Act (HIPAA) mandated terminologies for representing interdisciplinary concepts in national adherence measures.

A term extraction tool for expanding content in the domain of functioning, disability, and health: proof of concept

Among the challenges in developing terminology systems is providing complete content coverage of specialized subject fields. This paper reports on a term extraction tool designed for the development and expansion of terminology systems concerned with functioning, disability, and health. Content relevant to this domain is the emphasis of the foci and targets of many nursing terminologies. We extend previously published term extraction algorithms by applying two filters. The first filter is based on the raw frequency of the content words in the lexical string under consideration. The second filter applies the notion of a complete syntactic node to discover relevant noun or verb phrases. While we report on a limited corpus (30,607 words comprising 4103 terms from 60 dismissal note summaries), the recall, precision, and F-measures we observed are encouraging and suggest continued development and testing of the tool is merited.

The Nursing Terminology Summit Conferences: a case study of successful collaboration for change

The Nursing Terminology Summit, a series of invitational conferences and ongoing collaboration, has played both initiating and contributing roles to bring about a second-order change in the development and integration of standards for nursing terminology. What factors enabled this success? What factors made change difficult? This paper examines the structure and process of the Nursing Terminology Summit using concepts, principles, theories, and strategies identified in Lorenzi and Riley [Organizational Aspects of Health Informatics: Managing Technological Change, Springer, 1995]. As a case study, this critical analysis offers practical lessons for informaticians in managing change across disciplinary, organizational, and national boundaries.

Nursing process outcome linkage research: issues, current status, and health policy implications

BACKGROUND

The use of large clinical datasets to assess the effectiveness of health care is of growing interest in continuing efforts to understand the impact of healthcare costs on quality. Correspondingly, there is a greater need to define and measure outcomes that are sensitive to nursing interventions. However, concerns exist about the ability to amass and use large clinical nursing datasets to assess the effectiveness of nursing interventions. Some nursing studies have used large clinical datasets to examine patterns of nursing diagnoses, interventions, and outcomes. Among patient populations, however, systematic effectiveness studies of nursing process and outcome linkages at the individual nurse and patient level of analysis are essentially nonexistent. This is largely the result of slow development of nursing classifications, reference terminologies, and reference information standards. Nursing information systems have an unprecedented potential for documentation of nursing practice, as well as the accumulation and analysis of large clinical datasets, to improve nursing performance, increase nursing knowledge, and provide data and information necessary for nursing to participate in the formulation of healthcare policy.

OBJECTIVES

A literature search shows that a common framework is beginning to evolve that represents nursing's essential information, eg, the Nursing Minimum Data Set, Management Minimum Data Set, and several standardized nursing languages. Extensive research and other initiatives have produced 1) nursing languages and reference terminologies that span healthcare settings; 2) information models; and 3) standards for datasets supporting information systems. A number of issues remain, however, that concern the development of uniform nursing datasets, definitions of outcomes, quality of nursing data, information system design, and methods of data analysis. We review nursing process outcome research, clarify issues inherent in nursing effectiveness research, and discuss implications for nursing and health policy.

Integrating nursing diagnostic concepts into the medical entities dictionary using the ISO Reference Terminology Model for Nursing Diagnosis

OBJECTIVE

The purposes of the study were (1) to evaluate the usefulness of the International Standards Organization (ISO) Reference Terminology Model for Nursing Diagnoses as a terminology model for defining nursing diagnostic concepts in the Medical Entities Dictionary (MED) and (2) to create the additional hierarchical structures required for integration of nursing diagnostic concepts into the MED.

DESIGN AND MEASUREMENTS

The authors dissected nursing diagnostic terms from two source terminologies (Home Health Care Classification and the Omaha System) into the semantic categories of the ISO model. Consistent with the ISO model, they selected Focus and Judgment as required semantic categories for creating intensional definitions of nursing diagnostic concepts in the MED. Because the MED does not include Focus and Judgment hierarchies, the authors developed them to define the nursing diagnostic concepts.

RESULTS

The ISO model was sufficient for dissecting the source terminologies into atomic terms. The authors identified 162 unique focus concepts from the 266 nursing diagnosis terms for inclusion in the Focus hierarchy. For the Judgment hierarchy, the authors precoordinated Judgment and Potentiality instead of using Potentiality as a qualifier of Judgment as in the ISO model. Impairment and Alteration were the most frequently occurring judgments.

CONCLUSIONS

Nursing care represents a large proportion of health care activities; thus, it is vital that terms used by nurses are integrated into concept-oriented terminologies that provide broad coverage for the domain of health care. This study supports the utility of the ISO Reference Terminology Model for Nursing Diagnoses as a facilitator for the integration process.