ArticleJournal of oncology practice2016
Implementing and Improving Automated Electronic Tumor Molecular Profiling.
Article in Journal of oncology practice, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Integrating cancer genomic data into electronic health records.Genome medicine · 2016Review
- Pragmatic precision oncology: the secondary uses of clinical tumor molecular profiling.Journal of the American Medical Informatics Association : JAMIA · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Oncology practice increasingly requires the use of molecular profiling of tumors to inform the use of targeted therapeutics. However, many oncologists use third-party laboratories to perform tumor genomic testing, and these laboratories may not have electronic interfaces with the provider's electronic medical record (EMR) system. The resultant reporting mechanisms, such as plain-paper faxing, can reduce report fidelity, slow down reporting procedures for a physician's practice, and make reports less accessible. Vanderbilt University Medical Center and its genomic laboratory testing partner have collaborated to create an automated electronic reporting system that incorporates genetic testing results directly into the clinical EMR. This system was iteratively tested, and causes of failure were discovered and addressed. Most errors were attributable to data entry or typographical errors that made reports unable to be linked to the correct patient in the EMR. By providing direct feedback to providers, we were able to significantly decrease the rate of transmission errors (from 6.29% to 3.84%; P < .001). The results and lessons of 1 year of using the system and transmitting 832 tumor genomic testing reports are reported.
Indexed as
Identifiers
What 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.