Reducing Patient No-Show Rates in Diabetes Clinic




Jafri, Farzan Haider

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BACKGROUND: Patients missing scheduled appointments, or no-shows, is a pervasive issue across outpatient clinics. The estimated no-show rate among primary care clinics is estimated to be between 14% and 50% (Daggy, Lawley et al. 2010). In addition, no-shows are estimated to cost the US healthcare system $150 billion a year (Toland 2013). At many clinics no-shows have necessitated overbooking clinic slots to maintain efficiency (Muthuraman and Lawley 2008). However, patient no-shows themselves and the overbooking that no-shows necessitate causes problems for both the patient and provider. LOCAL PROBLEM: No-show rates have a number of adverse effects on the clinic, including at the Parkland Diabetes Clinic in Dallas, TX. This leads to longer wait times when all patients show, patient/provider/staff stress and frustration, and reduced clinical efficiency. No-shows and late cancellations can also lead to reduced patient access to care and potential increase in disease progression risk for those patients who fail to receive follow-up care. METHODS: This project used the PDSA cycle from quality improvement methodology. We started by analyzing the current situation at the diabetes clinic to determine the baseline no-show rate and the reasons for patient no-shows. Baseline data on no-shows were provided by Dr. Gunasekaran and Miriam Gomez-Wakeling; data was analyzed by Farzan Jafri. The scheduling process was mapped in an effort to identify inefficiencies in the scheduling process. Phone calls were then conducted with patients who no-showed in which a survey helped pinpoint reasons for no-shows. Using the process map and survey data, we brainstormed interventions to target root causes of no-shows at the clinic. PLANNED OR ACTUAL INTERVENTIONS: Our first intervention is ensuring that every patient receives a phone call reminder for their appointment. Our second intervention is limiting the degree to which the Patient Access Center, a call center, handles scheduling for the Diabetes clinic. RESULTS: Interventions were implemented in August 2020, and subsequent data collected from November 2020 to October 2021 was analyzed to determine changes in the no-show rate. The average no-show rate during this post-intervention period was ~22.2% ± 2.50 (t-test, p <0.05), a significant decrease from the baseline rate of ~31.9% ± 2.19. We predict this reduction will result in more consistent follow-up care, less risk of disease progression, and increased clinical efficiency. Our next step will be to transition our interventions into long-term sustainable solutions to maintain the lower no-show rate. CONCLUSIONS: Our project demonstrates that by following quality improvement methodology and the PDSA cycle, root causes for system inefficiencies can be targeted with site specific interventions. With support from leadership and buy-in from staff, these interventions can go on to positively impact the main problem being studied, or in our case the high no-show rate at the Parkland Diabetes clinic. While our specific interventions may not apply to every clinical context, the methods employed in this study can certainly be reproduced to target high no-show rates at other outpatient centers.

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