In a new study led by Dr. Danielle Mowery, automated bidirectional SMS text messaging is explored as a compelling strategy to facilitate communication between patients and the health system after hospital discharge. Understanding the unique ways in which patients interact with these messaging programs can inform future efforts to tailor their design to individual patient styles and needs.
We identified four distinct subgroups representing patient interaction phenotypes:
- A high engagement, high conformity group (enthusiasts)
- A low engagement, high conformity group (minimalists)
- A low engagement, low conformity group (nonadapters)
- A high engagement with an intense level of need group (high needs responders).
High-needs responders had significantly higher rates of revisits at 7, 30, and 60 days. Enthusiasts had the lowest overall rates if revisits at 30 and 60 days.
For health systems looking to leverage an SMS text messaging approach to engage patients after discharge, this work offers two main takeaways:
- Not all patients interact with SMS text messaging equally, and some may require either additional guidance or a different medium altogether
- The way in which patients interact with this type of program (in addition to the information they communicate through the program) may have added predictive signal toward adverse outcomes.
This work was completed in collaboration with the Center for Health Incentives and Behavioral Economics, the Leonard Davis Institute of Health Economics, the Penn Data and Analytics Center of Excellence, the School of Engineering & Applied Sciences, the Institute for Biomedical Informatics, and the Department of Biostatistics, Epidemiology, & Informatics.