ArticleNursing outlook2026
Using electronic health record phenotyping to guide extraction of markers of transition to adulthood in young adults with severe chronic illness: A proposed conceptual framework.
Article in Nursing outlook, 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
3 authors.
Funding
Abstract
backgroundYoung adulthood is a crucial and complex developmental period where one cultivates skills necessary to, if necessary, self-manage a severe chronic illness. Currently, minimal research exists on developmental transition in the context of severe chronic illness though, likely because young adults are known to be difficult to recruit/retain from primary data collection. PURPOSE: To increase research on this population, we propose utilizing existing data, including rich electronic health record (EHR) data, and adapting techniques such as EHR phenotyping to extract transition markers. EHR phenotyping is an existing technique that combines structured (e.g., billing/diagnostic codes) and unstructured (e.g., free-text notes) data to create algorithms to represent specific clinical events (e.g., history of pregnancy).
methodsAs such, we have developed a conceptual framework to apply EHR phenotyping to extract developmental markers of transition to adulthood. DISCUSSION/
conclusionWe aim for our framework to increase research on young adults and other vulnerable/hard-to-access populations.
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.