ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2015
Identifying the Clinical Laboratory Tests from Unspecified "Other Lab Test" Data for Secondary Use.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
1 citing paper in PubMed.
- Amplifying Domain Expertise in Clinical Data Pipelines.JMIR medical informatics · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Clinical laboratory results are stored in electronic health records (EHRs) as structured data coded with local or standard terms. However, laboratory tests that are performed at outside laboratories are often simply labeled "outside test" or something similar, with the actual test name in a free-text result or comment field. After being aggregated into clinical data repositories, these ambiguous labels impede the retrieval of specific test results. We present a general multi-step solution that can facilitate the identification, standardization, reconciliation, and transformation of such test results. We applied our approach to data in the NIH Biomedical Translational Research Information System (BTRIS) to identify laboratory tests, map comment values to the LOINC codes that will be incorporated into our Research Entities Dictionary (RED), and develop a reference table that can be used in the EHR data extract-transform-load (ETL) process.
Indexed as
Identifiers
26958239PMC4765675What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.