Outpatient portal use among pregnant individuals: Cross-sectional, temporal, and cluster analysis of use

Background Outpatient portal technology can improve patient engagement. For pregnant individuals, the level of engagement could have important implications for maternal and infant outcomes. Objective This study: (1) cross-sectionally and temporally characterized the outpatient portal use among pregnant individuals seen at our academic medical center; and (2) identified clusters of the outpatient portal user groups based on the cross-sectional and temporal patterns of use. Methods We used outpatient portal server-side log files to execute a hierarchical clustering algorithm to group 7663 pregnant individuals based on proportions of outpatient portal function use. Post-hoc analyses were performed to further assess outpatient portal use on key encounter characteristics. Results The most frequently used functions were MyRecord (access personal health information), Visits (manage appointments), Messaging (send/receive messages), and Billing (view bills, insurance information). Median outpatient portal function use plateaued by the third trimester. Four distinct clusters were identified among all pregnant individuals: Schedulers, Resulters, Intense Digital Engagers, and Average Users. Post-hoc analyses revealed that the use of the Visits function increased and the use of the MyRecord function decreased over time among clusters. Conclusions Our identification of distinct cluster groups of outpatient portal users among pregnant individuals underscores the importance of avoiding the use of generalizations when describing how such patients might engage with patient-facing technologies such as an outpatient portal. These results can be used to improve user experience and training with outpatient portal functions and may educate maternal health providers on patient engagement with the outpatient portal.

Automated summary

This study examines the outpatient portal use among pregnant individuals and identifies distinct user groups. The findings highlight the importance of avoiding generalizations when describing patient engagement with patient-facing technologies.