Multi-level QI interventions in a safety-net academic oncology clinic.
Authors: Aparna Chakravarti Jotwani, Courtney Nicole Miller-Chism, Margaret Griffin Crawford, Claire Mach, LaToya Woods, Jessica Zhang, Kyler Godwin, Daniel Murphy
Journal: Journal of Clinical Oncology (2021)

e18665 Background: Clinic cycle time is a performance metric and prolonged wait times may impact patient satisfaction and/or treatment outcomes. In primary care clinics, studies show prolonged cycle times detract from patient satisfaction. Fewer studies examine specialty clinics such as oncology which require multi-faceted care. Our Harris Health System (HHS) serves a diverse county with high patient volume with physician learners and limited providers due to limited resources. Our patient satisfaction assessments previously identified prolonged wait times as an area for improvement. Our team studied and process mapped operations with the goal of improving clinic efficiency. Our primary objective is to streamline the process for our outpatient oncology appointments measured through patient cycle times. We aimed to decrease the cycle time by 25% and improve patient satisfaction. Methods: From January 2018 through December 2019, the cycle time processes for Smith Thursday Oncology Clinics in the HHS were mapped and analyzed, and sequential PDSA (Plan-Do-Study-Act) cycles were completed to reduce non-value-added time. Six-month cycle times before and after implementation of three process changes implemented were compared with t-test analysis. Next, NRC (National Research Corporation) Health patient satisfaction data for the corresponding time frames was compared with both t-test and chi-square analyses. Results: Patient cycle time from July 2018 – December 2018 was compared to July 2019 – December 2019 with a t-test analysis. Our results showed a significant (p = 0.036) reduction in cycle time. The average percent decrease in cycle time was 19%. NRC patient satisfaction data inquiries, including overall satisfaction, informed regarding appointment delays, and waiting for more than 15 minutes were reviewed for this same time frame. We found trends in all three categories showing improvements in scores with p-values of 0.483, 0.821 and 0.282 respectively. Conclusions: Through multi-level interventions we were able to significantly reduce clinic cycle times. Trends towards improvement were seen as the population assessed was in the hundreds and not thousands needed for significance. Our academic teaching model is meaningful to study as it serves a high patient volume and educates future oncologists, especially pertinent when a shortage of oncologists in anticipated in the future. Additionally, our patients receive high quality care with nursing, education and infusion services. An area for improvement is communication with patients during their cycle times and other early QI work in our clinics show patients are interested in further education. Our underserved patient population is multi-ethnic, has unassessed health literacy, and frequent language barriers. Better efficiency in the clinics and utilization of cycle time can have multiple patient benefits that warrant further work in QI.