ArticleClinical trials (London, England)2009
The automation of clinical trial serious adverse event reporting workflow.
Article in Clinical trials (London, England), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Article
- Serious Adverse Events Reporting in Phase III Randomized Clinical Trials of Colorectal Cancer Treatments: A Systematic Analysis.Frontiers in pharmacology · 2021Article
- The potential of the internet.British journal of clinical pharmacology · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundThe reporting of serious adverse events is a requirement when conducting a clinical trial involving human subjects, necessary for the protection of the participants. The reporting process is a multi-step procedure, involving a number of individuals from initiation to final review, and must be completed in a timely fashion. PURPOSE: The purpose of this project was to automate the adverse event reporting process, replacing paper-based processes with computer-based processes, so that personnel effort and time required for serious adverse event reporting was reduced, and the monitoring of reporting performance and adverse event characteristics was facilitated.
methodsUse case analysis was employed to understand the reporting workflow and generate software requirements. The automation of the workflow was then implemented, employing computer databases, web-based forms, electronic signatures, and email communication.
resultsIn the initial year (2007) of full deployment, 588 SAE reports were processed by the automated system, eSAEy. The median time from initiation to Principal Investigator electronic signature was <2 days (mean 7 +/- 0.7 days). This was a significant reduction from the prior paper-based system, which had a median time for signature of 24 days (mean of 45 +/- 5.7 days). With eSAEy, reports on adverse event characteristics (type, grade, etc.) were easily obtained and had consistent values based on standard terminologies.Limitation The automated system described was designed specifically for the workflow at Thomas Jefferson University. While the methodology for system design, and the system requirements derived from common clinical trials adverse reporting procedures are applicable in general, specific workflow details may not be relevant at other institutions.
conclusionThe system facilitated analysis of individual investigator reporting performance, as well as the aggregation and analysis of the nature of reported adverse events.
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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.