Evidence map›Paper›PMID 28815140›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2017

D2Refine: A Platform for Clinical Research Study Data Element Harmonization and Standardization.

Deepak K Sharma, Harold R Solbrig, Eric Prud'hommeaux, Kate Lee, Jyotishman Pathak, Guoqian Jiang

Abstract read
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. HL7 FHIR-based tools and initiatives to support clinical research: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Deepak K SharmaMayo Clinic College of Medicine, Rochester, MN.
Harold R SolbrigMayo Clinic College of Medicine, Rochester, MN.
Eric Prud'hommeauxW3C/MIT, Boston, MA.
Kate LeeWeill Cornell Medicine, New York, NY.
Jyotishman PathakWeill Cornell Medicine, New York, NY.
Guoqian JiangMayo Clinic College of Medicine, Rochester, MN.

Funding

Tools for standardizing clinical research metadata using HL7 FHIRU01HG009450 · NHGRI · MAYO CLINIC ROCHESTER · PI JIANG, GUOQIAN · 2016 to 2018
$1.4M
caCDE-QA: A Quality Assurance Platform for Cancer Study Common Data ElementsU01CA180940 · NCI · MAYO CLINIC ROCHESTER · PI JIANG, GUOQIAN · 2014 to 2016
$1.1M
NCI NIH HHS U01 CA180940NHGRI NIH HHS U01 HG009450
6 · The paper itself

Abstract

In this paper, we present a platform known as D2Refine for facilitating clinical research study data element harmonization and standardization. D2Refine is developed on top of OpenRefine (formerly Google Refine) and leverages simple interface and extensible architecture of OpenRefine. D2Refine empowers the tabular representation of clinical research study data element definitions by allowing it to be easily organized and standardized using reconciliation services. D2Refine builds on valuable built-in data transformation features of OpenRefine to bring source data sets to a finer state quickly. We implemented the reconciliation services and search capabilities based on the standard Common Terminology Services 2 (CTS2) and the serialization of clinical research study data element definitions into standard representation using clinical information modeling technology for semantic interoperability. We demonstrate that D2Refine is a useful and promising platform that would help address the emergent needs for clinical research study data element harmonization and standardization.

Identifiers

PMID28815140
PMCPMC5543382

What OpenQuestion holds

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Registered trials

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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.