Evidence map›Paper›PMID 27570651›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2016

Applying a Participatory Design Approach to Define Objectives and Properties of a "Data Profiling" Tool for Electronic Health Data.

Hossein Estiri, Terri Lovins, Nader Afzalan, Kari A Stephens

Abstract read
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2016. 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. Trial
  2. Article
  3. A federated EHR network data completeness tracking system.Journal of the American Medical Informatics Association : JAMIA · 2019
    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

4 authors.

Hossein EstiriInstitute of Translational Health Sciences, University of Washington, Seattle, WA; Department of Biomedical Informatics & Medical Education, University of Washington, Seattle, WA.
Terri LovinsInstitute of Translational Health Sciences, University of Washington, Seattle, WA; Human Centered Design & Engineering, University of Washington, Seattle, WA.
Nader AfzalanDepartment of Geographic Information Science, University of Redlands, Redlands, CA.
Kari A StephensInstitute of Translational Health Sciences, University of Washington, Seattle, WA; Department of Biomedical Informatics & Medical Education, University of Washington, Seattle, WA; Department of Psychiatry & Behavioral Sciences, University of Washington, Seattle, WA.

Funding

Transform Dissemination and Implementation Science in CTSA ProgramsUL1TR002319 · NCATS · UNIVERSITY OF WASHINGTON · PI John K. Amory · 2017 to 2026
$100.0M
Institute of Translational Health SciencesUL1TR000423 · NCATS · UNIVERSITY OF WASHINGTON · PI DISIS, MARY L. · 2012 to 2016
$49.4M
NCATS NIH HHS UL1 TR000423NCATS NIH HHS UL1 TR002319
6 · The paper itself

Abstract

We applied a participatory design approach to define the objectives, characteristics, and features of a "data profiling" tool for primary care Electronic Health Data (EHD). Through three participatory design workshops, we collected input from potential tool users who had experience working with EHD. We present 15 recommended features and characteristics for the data profiling tool. From these recommendations we derived three overarching objectives and five properties for the tool. A data profiling tool, in Biomedical Informatics, is a visual, clear, usable, interactive, and smart tool that is designed to inform clinical and biomedical researchers of data utility and let them explore the data, while conveniently orienting the users to the tool's functionalities. We suggest that developing scalable data profiling tools will provide new capacities to disseminate knowledge about clinical data that will foster translational research and accelerate new discoveries.

Identifiers

PMID27570651
PMCPMC5001743

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.