Background: Lean methodology helps maximize value by reducing waste, first by defining what value and waste are in a system. In ophthalmology clinics, value is determined by the number of patients flowing through the clinic for a given time. We aimed to increase value using a lean-methodology guided policy change, then assessed its impact on clinic flow using an automated radiofrequency identification (RFID) based real-time locating system (RTLS).
Methods: A total of 6813 clinical visits occurred at a single academic institution's outpatient glaucoma clinic between January 5, 2018 to July 3, 2018. Over that period, 1589 patients comprising 1972 (29%) of visits were enrolled, with 1031 clinical visits occurring before and 941 visits after a policy change. The original policy was to refract all patients that improved with pinhole testing. The policy change was not to refract patients with a visual acuity ≥20/30 unless a specific request was made by the patient. Pre-post analysis of an automated time-motion study was conducted for the data collected 3 months before and 3 months after the policy change occurred on March 30, 2018. Changes to process and wait times were summarized using descriptive statistics and fitted to linear mixed regression models adjusting for appointment type, clinic volume, and daily clinic trends.
Results: One thousand nine hundred twenty-three visits with 1588 patients were included in the analysis. Mean [SD] age was 65.9 [14.7] years and 892 [56.2%] were women. After the policy change, technician process time decreased by 2.9 min (p < 0.0001) while daily clinical patient volume increased from 51.9 ± 16.8 patients to 58.4 ± 17.4 patients (p < 0.038). No significant difference was found in total wait time (p = 0.18) or total visit time (p = 0.83).
Conclusions: Real-time locating systems are effective at capturing clinical flow data and assessing clinical practice change initiatives. The refraction policy change was associated with reduced technician process time and overall the clinic was able to care for 7 more patients per day without significantly increasing patient wait time.
Keywords: Automated time and motion study; Lean-analysis; Pre-post analysis; Process time.
© 2022. The Author(s).