ArticleApplied clinical informatics2011
Implementing SNOMED CT for Quality Reporting: Avoiding Pitfalls.
Article in Applied clinical informatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Using Artificial Intelligence With Natural Language Processing to Combine Electronic Health Record's Structured and Free Text Data to Identify Nonvalvular Atrial Fibrillation to Decrease Strokes and Death: Evaluation and Case-Control Study.Journal of medical Internet research · 2021Article
- SNOMED CT Concept Hierarchies for Computable Clinical Phenotypes From Electronic Health Record Data: Comparison of Intensional Versus Extensional Value Sets.JMIR medical informatics · 2019Article
- Methods and applications for visualization of SNOMED CT concept sets.Applied clinical informatics · 2014Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo implement the SNOMED CT electronic specifications for reporting quality measures and to identify critical issues that affect implementation.
backgroundThe Centers for Medicare and Medicaid (CMS) have issued the electronic specifications for reporting quality measures requiring vendors and hospital systems to use standardized data elements to provide financial incentives for eligible providers.
methodsThe electronic specifications from CMS were downloaded and extracted. All SNOMED CT codes were examined individually as part of the creation of a mapping table for distribution by a vendor for incorporation into electronic health record systems. A qualitative and quantitative evaluation of the SNOMED CT codes was done as a follow up to the mapping project.
resultsA total of 10643 SNOMED codes were examined for the 44 measures. The approved SNOMED CT code sets contain aberrancies in content such as incomplete IDs, the use of description IDs instead of concept IDs, inactive codes, morphology and observable codes for clinical findings and the inclusion of non-human content.
conclusionImplementers of these approved specifications must do additional rigorous review and make edits in order to avoid incorporating errors into their EHR products and systems.
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Registered trials
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