Using SNOMED CT to Represent Two Interface Terminologies

Rosenbloom, S. Trent; Brown, Steven H.; Froehling, David A.; Bauer, Brent A.; Wahner‐Roedler, Dietlind L.; Gregg, William M.; Elkin, Peter L.

doi:10.1197/jamia.m2694

Cited by 42 publications

(26 citation statements)

References 35 publications

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“…While most concepts were described by one term, some of the concepts were described using as many as 9 terms which provide a wide variety of relevant synonyms that include locally used terms from which clinicians can make selections to accurately describe diagnoses. Content coverage was high; consistent with the study by Rosenbloom et al [24]. In our study, all but two concepts generated from the term-based sources matched SNOMED CT concepts.…”

Section: Discussionsupporting

confidence: 92%

A structured approach to recording AIDS-defining illnesses in Kenya: A SNOMED CT based solution

Oluoch

Keizer

Langat

et al. 2015

Journal of Biomedical Informatics

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Introduction Several studies conducted in sub-Saharan Africa (SSA) have shown that routine clinical data in HIV clinics often have errors. Lack of structured and coded documentation of diagnosis of AIDS defining illnesses (ADIs) can compromise data quality and decisions made on clinical care. Methods We used a structured framework to derive a reference set of concepts and terms used to describe ADIs. The four sources used were: (i) CDC/Accenture list of opportunistic infections, (ii) SNOMED Clinical Terms (SNOMED CT), (iii) Focus Group Discussion (FGD) among clinicians and nurses attending to patients at a referral provincial hospital in western Kenya, and (iv) chart abstraction from the Maternal Child Health (MCH) and HIV clinics at the same hospital. Using the January 2014 release of SNOMED CT, concepts were retrieved that matched terms abstracted from approach iii & iv, and the content coverage assessed. Post-coordination matching was applied when needed. Results The final reference set had 1054 unique ADI concepts which were described by 1860 unique terms. Content coverage of SNOMED CT was high (99.9% with pre-coordinated concepts; 100% with post-coordination). The resulting reference set for ADIs was implemented as the interface terminology on OpenMRS data entry forms. Conclusion Different sources demonstrate complementarity in the collection of concepts and terms for an interface terminology. SNOMED CT provides a high coverage in the domain of ADIs. Further work is needed to evaluate the effect of the interface terminology on data quality and quality of care.

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Section: Discussionsupporting

confidence: 92%

A structured approach to recording AIDS-defining illnesses in Kenya: A SNOMED CT based solution

Oluoch

Keizer

Langat

et al. 2015

Journal of Biomedical Informatics

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“…All the questionnaire elements were manually matched to SNOMED-CT concepts with the exact or closest related concept. While the healthcare enterprise has been slow to adopt the use of standard terminologies, SNOMED-CT has been mandated and effectively used for the encoded collection of patient health information by numerous US federal government panels, committees, and studies, as well as private institutions [12][13][14][15][16][17][18][19]. SNOMED-CT has also become available free of charge for use in the USA through an agreement with the National Library of Medicine's Unified Medical Language System [10].…”

Section: Methodsmentioning

confidence: 99%

Creation and Storage of Standards-based Pre-scanning Patient Questionnaires in PACS as DICOM Objects

2010

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Radiology departments around the country have completed the first evolution to digital imaging by becoming filmless. The next step in this evolution is to become truly paperless. Both patient and non-patient paperwork has to be eliminated in order for this transition to occur. A paper-based set of patient pre-scanning questionnaires were replaced with web-based forms for use in an outpatient imaging center. We discuss this process by which questionnaire elements are converted into SNOMED-CT terminology concepts, stored for future use, and sent to PACS in Digital Imaging and Communications in Medicine (DICOM) format to be permanently stored with the relevant study in the DICOM image database.

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“…Assertional knowledge may be more relevant to clinical users than defi nitional knowledge and may improve their ability to use the terminology effi ciently. For example, in the interface terminology CHISL (Categorical Health Information Structured Lexicon, used for clinical documentation at the Vanderbilt University Medical Center and described further later in this chapter) [ 18 ] , the concept for "chest pain" include links to the normal status modifi er "absent" (e.g., "chest pain" is normally absent in a healthy population), to a list of severity modifi ers (e.g., "mild," "moderate," and "severe"), and to lists of common associated concepts (e.g., nausea, depression, diaphoresis, anxiety).…”

Section: Assertional Knowledge In An Interface Terminologymentioning

confidence: 99%

Interface Terminologies

Rosenbloom¹

2012

Health Informatics

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Using SNOMED CT to Represent Two Interface Terminologies

Abstract: Our findings support using SNOMED CT to provide standardized representations of information created using these two terminologies, but suggest that enriching SNOMED CT semantics would improve representation of the external terms.

Cited by 42 publications

References 35 publications

A structured approach to recording AIDS-defining illnesses in Kenya: A SNOMED CT based solution

A structured approach to recording AIDS-defining illnesses in Kenya: A SNOMED CT based solution

Creation and Storage of Standards-based Pre-scanning Patient Questionnaires in PACS as DICOM Objects

Interface Terminologies

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