Standardizing Physiologic Assessment Data to Enable Big Data Analytics

Matney, Susan; Settergren, Theresa Tess; Carrington, Jane M.; Richesson, Rachel L.; Sheide, Amy; Westra, Bonnie L.

doi:10.1177/0193945916659471

Cited by 23 publications

(25 citation statements)

References 11 publications

(11 reference statements)

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“…To present the four step approach to utilize existing SNOMED CT subsets for development of subsets that suite a specific clinical use case. (20) USA, 2017 Western Journal of Nursing Research…”

Section: Studies In Health Technology and Informaticsmentioning

confidence: 99%

“…In addition, studies have been developed associating the use of this clinical nomenclature with other standardized languages used by nursing, such as Logical Observation Identifiers, Names, and Codes (LOINC), ICNP ® , NANDA-I, and Omaha System, as well as other health information platforms like Unified Medical Language System (UMLS) (18,(20)(21)25,(27)(28)(29)(30) . This demonstrates an effort that the discipline, in different countries, has made in an attempt to find a system that better contemplates its practice.…”

Section: Journal Of Biomedical Informaticsmentioning

confidence: 99%

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

Silva

Vega

Córdova

et al. 2020

Rev. Gaúcha Enferm.

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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.

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Section: Studies In Health Technology and Informaticsmentioning

confidence: 99%

Section: Journal Of Biomedical Informaticsmentioning

confidence: 99%

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

Silva

Vega

Córdova

et al. 2020

Rev. Gaúcha Enferm.

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“…Consistent with 2016 Interoperability Standards 13 and the American Nurses Association’s position on use of Nursing Terminologies, 14 assessments and outcomes will be coded with Logical Observation Identifiers Names and Codes (LOINC) and Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT) will be used to code the value sets for assessments, problems, and interventions. Both LOINC and SNOMED-CT terminologies are evolving for physiological concepts, 15 such as those in our information model which will be used and expanded as a result of our work. Research is needed to create additional information models as this study addressed only a portion of flowsheet data.…”

Section: Future Researchmentioning

confidence: 99%

Modeling Flowsheet Data to Support Secondary Use

Westra

Christie

Johnson

et al. 2017

CIN: Computers, Informatics, Nursing

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The purpose of this study was to create information models from flowsheet data using a data-driven consensus based method. Electronic health records contain a large volume of data about patient assessments and interventions captured in flowsheets that measure the same “thing,” but the names of these observations often differ, according to who performs documentation or the location of the service (e.g., pulse rate in an intensive care, the emergency department, or a surgical unit documented by a nurse or therapist or captured by automated monitoring). Flowsheet data are challenging for secondary use due to the existence of multiple semantically equivalent measures representing the same concepts. Ten information models were created in this study: five related to quality measures (falls, pressure ulcers, venous thrombosis embolism, genitourinary system including catheter associated urinary tract infection, and pain management) and five high volume physiological systems: cardiac, gastrointestinal, musculoskeletal, respiratory, and expanded vital signs/anthropometrics. The value of the information models is that flowsheet data can be extracted and mapped for semantically comparable flowsheet measures from a clinical data repository regardless of the time frame, discipline, or setting in which documentation occurred. The 10 information models simplify the representation of the content in flowsheet data, reducing 1,552 source measures to 557 concepts. The amount of representational reduction ranges from 3% for Falls to 78% for the Respiratory System. The information models provide a foundation for including nursing and interprofessional assessments and interventions in common data models, to support research within and across health systems.

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“…One demonstration of this happening is a group who worked across six health systems to align a minimum set of physiologic nursing assessment data with national standardized coding to support the exchange and aggregation of comparable nursing data. 11 Considerably more work of this type is needed to facilitate a systematic approach to comparing nursing data. Mobile health technologies allow for clinicians to access data documented by patients for real-time use in clinical care.…”

Section: How Cardiovascular Nurse Scientists Can Contribute To the Usmentioning

confidence: 99%