Improving patient retention by optimizing appointment scheduling in an underserved oncology population within a public safety-net health system.

Abstract

193 Background: Cancer patients in underserved populations are at high risk for patient attrition and treatment delay. We theorized that decreased appointment scheduling was contributing to a high no-show rate within an urban safety-net hospital. Clinic appointments were being scheduled in the department-specific record and verify system rather than the hospital-wide electronic health record (EHR). We sought to adopt EHR scheduling with the long-term goal of decreasing the no-show rate. Our aim was to utilize the Lean Six Sigma (LSS) methodologies to increase EHR scheduling of follow-up and rescheduling of no-show appointments to 50%. Methods: While involving the entire clinic staff, we utilized the Lean Six Sigma DMAIC model: define, measure, analyze, improve and control, to improve EHR appointment scheduling. Appointment data was collected for the 3 months prior to and during the intervention time period. We determined the root causes for delinquent scheduling, including lack of staff availability to schedule patients into two electronic systems and to call no-show patients. Interventions included implementation of an electronic order for follow-up scheduling and blocked time for personnel to contact no-show patients and verify scheduling. After the formation of a novel process map, control plan, and Failure Modes Effects Analysis (FMEA), the pilot study ran for 2 months. Results: Follow-up appointment scheduling into the EHR improved from 2% to 98% (p < 0.01). After the first intervention month, the no-show rescheduling rate improved from 0% to 43% (p < 0.01): below goal. The team revised the process map by substituting a no-show EHR order in place of the calendar intervention. This constituted the beginning of month 2 and no-show appointment rescheduling subsequently improved from 43% to 87% (p < 0.01). The patient no-show rate was 19% during the pre-intervention period, 17% for the first intervention cycle and 15% for the second intervention cycle (p = 0.3). Conclusions: Utilization of LSS allowed for successful adoption of EHR appointment scheduling within our department. While not yet significant, the no-show rate appears to be trending downward as a result of improved scheduling, and we expect the no-show rate to continue to decline as the study matures. These findings suggest that optimized appointment scheduling may decrease patient retention in an at-risk population. Future directions include evaluating cancer outcomes and decreased healthcare costs as a result of higher patient retention.