ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2009
Laying the groundwork for enterprise-wide medical language processing services: architecture and process.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A systematic and standard process for capturing information within free-text clinical documents could facilitate opportunities for improving quality and safety of patient care, enhancing decision support, and advancing data warehousing across an enterprise setting. At Partners HealthCare System, the Medical Language Processing (MLP) services project was initiated to establish a component-based architectural model and processes to facilitate putting MLP functionality into production for enterprise consumption, promote sharing of components, and encourage reuse. Key objectives included exploring the use of an open-source framework called the Unstructured Information Management Architecture (UIMA) and leveraging existing MLP-related efforts, terminology, and document standards. This paper describes early experiences in defining the infrastructure and standards for extracting, encoding, and structuring clinical observations from a variety of clinical documents to serve enterprise-wide needs.
Indexed as
Identifiers
20351830PMC2815370What 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.