Evidence map›Paper›PMID 22907283›Full record

ArticleCurrent oncology reports2012

The automatic clinical trial: leveraging the electronic medical record in multisite cancer clinical trials.

Keith Goodman, Judy Krueger, John Crowley

Abstract readMulticenter Study
In one paragraph

Article in Current oncology reports, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Review
  3. Using electronic health records for clinical trials: Where do we stand and where can we go?CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2019
    Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. 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

3 authors.

Keith GoodmanCancer Research and Biostatistics, 1730 Minor Ave., STE 1900, Seattle, WA 98101, USA. keithg@crab.org
Judy Krueger
John Crowley

Funding

SWOG - Foreign Accrual under UMiU10CA032102 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BLANKE, CHARLES D. · 1985 to 2013
$141.3M
SOUTHWEST ONCOLOGY GROUP--STATISTICAL CENTERU10CA038926 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI LEBLANC, MICHAEL L. · 1985 to 2013
$69.8M
NCI NIH HHS N01 CA032102NCI NIH HHS N01 CA038926NCI NIH HHS U10 CA032102NCI NIH HHS U10 CA038926
6 · The paper itself

Abstract

Submission of data into clinical trial electronic data capture (EDC) systems currently requires redundant entry of data that already exist in the electronic medical record (EMR). Being able to automatically transfer data from the EMR to the EDC system would save many hours of arduous effort, especially for multisite data-intensive oncology trials. Standardization of the way in which data are stored in and retrieved from the EMR and techniques for mining data from the unstructured narrative will provide opportunities for transferring data from the EMR to the EDC system. As different EMRs proliferate, other technology in the form of data mining or middle-tier applications is certain to provide assistance in this effort.

Indexed as

Clinical Trials as TopicData MiningElectronic Health RecordsHumansNeoplasms

Identifiers

PMID22907283
PMCPMC3490046

What OpenQuestion holds

Textmetadata
LicenceTDM
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.