Evidence map›Paper›PMID 30657248›Full record

ArticleClinical and translational science2019

Access to Routinely Collected Clinical Data for Research: A Process Implemented at an Academic Medical Center.

Susan C Guerrero, Sujatha Sridhar, Cynthia Edmonds, Christina F Solis, Jiajie Zhang, David D McPherson, Elmer V Bernstam

Abstract read
In one paragraph

Article in Clinical and translational science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Confidence-based laboratory test reduction recommendation algorithm.BMC medical informatics and decision making · 2023
    Article
  5. Closing the loop: automatically identifying abnormal imaging results in scanned documents.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  6. Exploring the Hazards of Scaling Up Clinical Data Analyses: A Drug Side Effect Discovery Case Report.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
    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

7 authors.

Susan C GuerreroSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, USA.
Sujatha SridharCenter for Clinical and Translational Sciences, The University of Texas Health Science Center at Houston, Houston, Texas, USA.
Cynthia EdmondsResearch Administration, The University of Texas Health Science Center at Houston, Houston, Texas, USA.
Christina F SolisOffice of Legal Affairs, The University of Texas Health Science Center at Houston, Houston, Texas, USA.
Jiajie ZhangSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, USA.
David D McPhersonCenter for Clinical and Translational Sciences, The University of Texas Health Science Center at Houston, Houston, Texas, USA.
Elmer V BernstamSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, USA.

Funding

University of Pittsburgh Clinical and Translational Science InstituteUL1TR001857 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2016 to 2025
$129.3M
UT Southwestern Center for Translational Medicine (UL1/KL2/TL1)UL1TR001105 · NCATS · UT SOUTHWESTERN MEDICAL CENTER · PI TOTO, ROBERT DANIEL · 2013 to 2017
$24.5M
Center for Clinical and Translational Sciences (CCTS)UL1TR000371 · NCATS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI MCPHERSON, DAVID D · 2012 to 2016
$13.4M
Harnessing the power of CTSA-CDRN data networks: Using social determinants of health, frailty and functional status to identify at-risk patients and improve risk adjustmentU01TR002393 · NCATS · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI SHIREMAN, PAULA K · 2018 to 2021
$3.1M
Patient Medical History Representation, Extraction, and Inference from EHR DataR01LM011829 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI TAO, CUI · 2014 to 2018
$1.7M
NCATS NIH HHS U01 TR002393NCATS NIH HHS UL1 TR000371NCATS NIH HHS UL1 TR001105NCATS NIH HHS UL1 TR001857NLM NIH HHS R01 LM011829
6 · The paper itself

Abstract

Electronic health records are valuable for clinical and translational research. Institutions must protect patient privacy and comply with applicable regulations while allowing appropriate access to clinical data for research. The processes that investigators must follow to access clinical data can be substantially different at different institutions. In this paper, we describe the process developed at our institution that has been active for 5 years and was used to satisfy over 200 requests for access to identified clinical data, usually within 1 day for internal requests and 3 days for visiting researchers.

Indexed as

Academic Medical CentersData CollectionResearchClinical AuditHumansTranslational Research, Biomedical

Identifiers

PMID30657248
PMCPMC6510377

What OpenQuestion holds

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LicenceCC BY-NC
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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.