ArticleCureus2026
Tracking Scientific Publications in Non-traditional Academic Medical Centers.
Article in Cureus, 2026. 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
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tracking academic publications is inherently challenging for both academic and non-traditional academic centers. Publications are considered crucial for academic success; however, accurately identifying and reporting them is a resource-intensive process. There is a lack of a standardized, readily available solution that focuses on tracking publications linked to human subject research within a large healthcare network. This report presents a home-grown approach to tracking and reporting publications. The aim was to track publications and calculate the publication rate of studies approved by the institutional review board (IRB) between 2021 and 2023 at a large United States hospital network by surveying principal investigators (PI) via REDCap about resulting publications. This semi-automated approach revealed a 30.5% publication rate with publications including full-text articles, abstracts, posters, and conference presentations. Tracking publications within a complex healthcare network is challenging. While the described method facilitated data collection, it was time- and resource-intensive, and reliance on PI self-reporting could have limited the accuracy of the publication rate calculated. However, with further automation, home-grown approaches such as the one presented here could allow for a user-friendly application that other non-traditional academic medical centers can adopt. A widely acceptable and easily adaptable tool for publication tracking is needed, particularly for non-traditional academic centers. Future research should explore AI and machine learning applications to address this need.
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.