ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2014
Using Arden Syntax to identify registry-eligible very low birth weight neonates from the Electronic Health Record.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- A clinical informatics approach to bronchopulmonary dysplasia: current barriers and future possibilities.Frontiers in pediatrics · 2024Review
- Patient Cohort Identification on Time Series Data Using the OMOP Common Data Model.Applied clinical informatics · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Condition-specific registries are essential resources for supporting epidemiological, quality improvement, and clinical trial studies. The identification of potentially eligible patients for a given registry often involves a manual process or use of ad hoc software tools. With the increased availability of electronic health data, such as within Electronic Health Record (EHR) systems, there is potential to develop healthcare standards based approaches for interacting with these data. Arden Syntax, which has traditionally been used to represent medical knowledge for clinical decision support, is one such standard that may be adapted for the purpose of registry eligibility determination. In this feasibility study, Arden Syntax was explored for its ability to represent eligibility criteria for a registry of very low birth weight neonates. The promising performance (100% recall; 97% precision) of the Arden Syntax approach at a single institution suggests that a standards-based methodology could be used to robustly identify registry-eligible patients from EHRs.
Indexed as
Identifiers
25954412PMC4419950What OpenQuestion holds
Registered trials
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