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Improving patient adherence to A1c testing

Project status

Pilot/study underway
Pilot/study with results


Marguerite Balasta, MD, FACP

Corinne Rhodes, MD, MPH

Anna Morgan, MD, MSc, MSHP

Gaibriel De Guzman, MHA

Innovation leads


Sam Martin Educational Pilot Award


Care teams use A1c tests that measure average blood sugar levels over time to diagnose prediabetes and diabetes and help patients properly manage diabetes to avoid complications.

Proactive outreach to engage patients in A1c testing is necessary. However, traditional outreach methods such as phone calls, mailers, and messaging via patient portals can be costly, labor-intensive, time-consuming, and yield relatively low results engaging less than a third of patients.


A team of clinicians at Penn Medicine is leveraging Way to Health to test the efficacy of Diabetes Outreach by Text bot (DOTBot), a bi-directional texting program designed to engage patients with uncontrolled diabetes to adhere to A1c testing standards.

For the initial pilot, clinicians placed bulk orders for approximately 650 patients with outstanding A1c labs or uncontrolled diabetes. Then, a non-clinical population health staff member leveraged DOTBot to simultaneously send algorithmic text messages to the entire population – notifying them that they were due for A1c testing and advising them on the next steps. Patients were given the option to walk into any Penn Medicine lab to be tested or have the order mailed to them to fill at a lab of their choosing.


In the fall of 2022, DOTBot was piloted among approximately 650 Penn Medicine patients with uncontrolled diabetes. The team expects to publish results from the initial pilot in the spring of 2023. Early engagement data shows that 40 percent of patients responded to texts compared to only 30 percent of patients reached by phone calls or portal messages – while using 90 percent less staff time to complete outreach. Check back soon for updates.

Way to Health Specs

Learn more about the platform
Activity monitoring
Arms and randomization
Criteria-based rules
Dashboard view
Device integration
EHR integration
Multiple languages
Patient portal messaging
Patient-reported outcomes capture
Photo messaging
Remote patient monitoring
Schedule-based rules
Survey administration
Two-way texting
Vitals monitoring