Plastic and Reconstructive Surgery Resident Indigent Care Clinic Optimization by Improving “No-Show” Rates

Abstract

Abstract Absenteeism among clinical patients is a significant source of inefficiency in the modern American health care system. Routine absenteeism limits access to care for indigent patients, thus providing additional strain on the health care system and timely administration of care. This quality improvement project set out to quantify, understand, and potentially reduce patient absenteeism in our weekly plastic and reconstructive surgery resident indigent care clinic. One year prior to our study was retrospectively reviewed to determine a baseline rate of absenteeism (no shows). The daily and monthly no-show percentages were calculated. Then, three consecutive 2-month Plan, Do, Study, Act (PDSA) cycles were performed and data were recorded. The initial year analysis demonstrated an average no-show rate of 25%. The first PDSA cycle attempted to ascertain factors contributing to absenteeism and to get patients rescheduled. The rate of clinical absenteeism was 27% over this period compared with a rate of 18% in the control period. During this period, we discovered a limitation of our institution's electronic medical record (EMR). Rescheduled patients were removed from the original schedule and were not counted as a missed appointment even though the opportunity for care was missed. The second PDSA cycle attempted to collect raw data while trying to understand the EMR error and rescheduling process. During this period, there was a 33% no-show rate compared with 27% in the control period. The third PDSA cycle attempted again to establish factors contributing to clinical absenteeism with a better understanding of the limitations of our EMR. A 33% no-show rate during this cycle was recorded compared with 22% in the control period. After three PDSA cycles were completed, our clinic had an average no-show rate of 31% compared with 25% during the same months in the previous year. This project brought to realization that our data were initially skewed by our ignorance of an EMR flaw that did not track patients who either canceled or rescheduled their appointments. We also learned that there is a certain subset of patients who are not able to be contacted and who do not follow up.