Inpatient portal clusters: identifying user groups based on portal features.

ABSTRACT:

Objective

Conduct a cluster analysis of inpatient portal (IPP) users from an academic medical center to improve understanding of who uses these portals and how.

Methods

We used 18 months of data from audit log files, which recorded IPP user actions, of 2815 patient admissions. A hierarchical clustering algorithm was executed to group patient admissions on the basis of proportion of use for each of 10 IPP features. Post-hoc analyses were conducted to further understand IPP use.

Results

Five cluster solutions were developed for the study sample. Our taxonomy included users with high levels of accessing features that were linked to reviewing schedules, results, tutorials, and ordering food. Patients tended to stay within their clusters over multiple admissions, and the c

SUBMITTER: Fareed N 

PROVIDER: S-EPMC7647162 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature