The simple solution infusion centers are adopting to solve common scheduling challenges

This webinar is on-demand and can be viewed at your convenience.

Scheduling problems are rampant at most infusion centers, with long patient wait times, midday peaks and over burdened nurses. While EHRs are great as a single source of truth for all patient-related information, they won't solve common capacity constraints.

However, these challenges have an uncomplicated solution. Applying mathematical algorithms, machine learning and predictive analytics has enabled hundreds of infusion centers to increase patient access, reduce wait times, reduce overtime hours and boost nurse satisfaction.

During this discussion, clinical oncology leaders from Hartford Healthcare share how they applied predictive analytics and machine learning to EHR data to help:
  • Level out high volumes
  • Manage variabilities and add-ons
  • Navigate the peaks of the COVID-19 waves
  • Improve the staff and patient experience


Abbi Bruce_CX - Carly Xagas

Abbi Bruce RN, MS, OCN

Program Director, Medical Oncology and Infusion Services, Hartford Healthcare Cancer Institute

Shannon Pindar_CX - Carly Xagas

Shannon Pindar RN,BSN,OCN

Nurse Manager, Medical Oncology, Infusion Services and the Innovation Unit at Hartford Hospital

Amanda DiBenedetto_CX - Carly Xagas

Amanda DiBenedetto MSN,RN

Nurse Manager, Medical Oncology/Infusion, Avon Cancer Center, Hartford Healthcare Cancer Institute