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Disparities in pediatric patient portal adoption and feature use

Cite this dataset

LeLaurin, Jennifer et al. (2021). Disparities in pediatric patient portal adoption and feature use [Dataset]. Dryad.


Objective: Disparities in adult patient portal adoption are well-documented; however, less is known about disparities in portal adoption in pediatrics. This study examines the prevalence and factors associated with patient portal activation and use of specific portal features in general pediatrics.

Materials and Methods: We analyzed electronic health record (EHR) data from 2012-2020 in a large academic medical center that offers both parent and adolescent portals. We summarized portal activation and use of select portal features (messaging, records access and management, appointment management, visit/admissions summaries, and interactive feature use). We used logistic regression to model factors associated with patient portal activation among all patients along with feature use and frequent feature use among ever users (i.e., ≥1 portal use).

Results: Among 52,713 unique patients, 39% had activated the patient portal, including 36% of patients aged 0-11, 41% of patients aged 12-17 and 62% of patients aged 18-21 years. Among activated accounts, ever use of specific features ranged from 28% for visit/admission summaries to 92% for records access and management. Adjusted analyses showed patients with activated accounts were more likely to be adolescents or young adults, white, female, privately insured, and less socioeconomically vulnerable. Individual feature use among ever users generally followed the same pattern.

Conclusions: Our findings demonstrate that important disparities persist in portal adoption in pediatric populations, highlighting the need for strategies to promote equitable access to patient portals.


We obtained patient-level data from the electronic health record (EHR) for all general pediatric patient visits between September 1, 2012 and July 30, 2020. General pediatrics clinics included primary care and associated outpatient clinics. We geocoded patient addresses to identify residential census tract, which was linked to the socioeconomic vulnerability (SEV) measure. All variables were assessed at the time of the most recent visit.

Usage notes

No more than 3% of the data had missing values for race and ethnicity. A total of 2.2% of patients lived outside of Florida and were not geocoded. Among Florida residents, 1,679 gave a postal office box and 31 declined to give a residential address. These records could not be assigned to a census tract or SEV value. The remaining 43,221 records with residential addresses were geocoded to residential street and census tract.