We conducted a quality improvement study to improve external imaging access at new patient visits (NPVs). Our goal was to enhance diagnostic workflow, streamline care coordination, and develop a scalable solution.
Timely access to imaging is critical for diagnosis, yet obtaining studies from external institutions remains problematic. This gap causes diagnostic delays, duplicate exams, unnecessary return visits, and added burden on physicians, patients, and staff. Existing solutions, such as EPIC Care Everywhere, provide limited image access, and long-term vendor fixes remain years away. An interim workflow is therefore essential.
Phase 1 consisted of sequential pilots to improve imaging availability at NPVs. Interventions included automated patient text messaging via Penn Medicine's “Switchboard" telecommunications platform, a fake-backend new patient coordinator, and a combined synergistic model. A subsequent pilot tested workflow enhancements such as batching outbound requests. Outcomes included percentage of NPVs with imaging available and time required per patient. In Phase 2, we implemented the pilot-proven synergistic workflow and collected data over a 30-week period.
At baseline, fewer than 40% of NPVs had external imaging available, with 22% requiring a return visit solely due to missing studies. Phase 1 demonstrated that the text-based intervention improved availability to 48% (n=21), while a resource-focused approach using a fake-backend coordinator reached 80% (n=15). Combining both strategies yielded 88% availability (n=28). Workflow refinements, including batching and enhanced system access, reduced time per patient from 20 to 17 minutes (n=12). Phase 2 captured outcomes over 30 weeks, showing that for n=401, image availability remained high at 85% and time per patient was dramatically reduced to 3.5 minutes.
Pilot studies demonstrated that a synergistic workflow integrating patient-focused automation with a dedicated resource markedly improved external imaging availability. The workflow yielded sustained improvements in imaging availability. This approach offers a scalable and broadly applicable model to optimize imaging access.