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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
Journal article   Peer reviewed

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

Carolina M. Gustafson, Traci M. Kazmerski and Theresa A. Koleck
Nursing outlook, Vol.74(5), 102854
09/2026
DOI: 10.1016/j.outlook.2026.102854
PMID: 42508369

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Abstract

Young 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. 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). As such, we have developed a conceptual framework to apply EHR phenotyping to extract developmental markers of transition to adulthood. We aim for our framework to increase research on young adults and other vulnerable/hard-to-access populations. •Developmental transition to adult with severe chronic illness is poorly understood.•Increased research on young adults can target support to improve care.•Young adults are difficult to recruit and retain for primary data collection.•The proposed framework addresses this barrier by using informatics/existing data.•The proposed framework can be adapted to other difficult-to-access populations.
Chronic illness Developmental transition Electronic health record (EHR) phenotyping Young adulthood

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