ArticleTherapeutic advances in drug safety2025
Automatic tool for the reconciliation of serious adverse events for pharmacovigilance: design and implementation of Reconciliaid.
Article in Therapeutic advances in drug safety, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
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
No grant is acknowledged in the PubMed record.
Abstract
Background: Reporting serious adverse events (SAEs) is crucial to reduce or avoid toxicities that can lead to major consequences for patient's health due to treatments tested in clinical trials. Its exhaustiveness is often inadequate, and we observe discrepancies between data published by pharmacovigilance organizations and clinical databases. Objectives: While the process of reconciliation aims at reducing these differences, it remains a very time-consuming and imprecise task. We propose a tool to automate this process. Design: We have developed and tested Reconciliaid, an application that compares the SAEs of the databases of clinical trials collected according to a standard inspired by the Clinical Data Interchange Standards Consortium, and of pharmacovigilance collected according to the international standards ICH-E2B (R3). It generates a reconciliation file that indicates precisely what information does not coincide in the two databases to facilitate the identification of inconsistencies. Methods: Reconciliaid was tested to create 13 reconciliation files, containing 290 SAEs. We inspected these files to determine their ability in identifying the inconsistencies and compared the manual and semi-automated reconciliation time. Four users answered the System Usability Scale (SUS) to measure its usability. Results: The application identified all variables of interest in all reconciliations. Different formats and libraries were automatically harmonized, allowing a perfect identification of inconsistencies for all variables. The matching of the same SAE in the two databases was correct in 97.2% of the reconciliations. Reconciliaid is six times faster than the manual approach for senior data managers (range = 3-24 times). A novice data manager performed three reconciliations 4.8 faster with the help of Reconciliaid than manually (29 min vs 134 min) and with fewer mistakes. Mean SUS score was 92.5. Conclusion: Reconciliaid has a high level of usability, can increase the quality of reconciliation, and reduces considerably the reconciliation time, allowing to increase the frequency of reconciliation processes and to focus resources on patient safety and medical assessment.
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.