Stop Blaming the Weatherman! A Retrospective Study of Endoscopy Show Rates at a Midwest Urban Safety-Net Hospital

Background: Weather patterns are well-known to affect human health and behavior and are often arbitrarily blamed for high no-show rates (NSRs). The NSR for outpatient gastrointestinal procedures ranges from 4% to 41% depending on the population and procedure performed. Identifying potential causes will allow for the optimization of endoscopy resource utilization. Aim: The aim of this study was to evaluate the effects of a day of the year and weather conditions have on NSRs for outpatient endoscopic procedures at a safety-net hospital in Cleveland, Ohio, United States. Methods: A 12-month, retrospective cohort study of the NSR for outpatient endoscopic procedures was performed using local weather data from January 1, 2017 to December 31, 2017. Data was assessed by analysis of variance/ttest, and the chi(2)test was used to analyze weather impact on NSR. Results: A total of 7935 patients had an average overall NSR of 11.8%. Average NSR for esophagogastroduodenoscopies (EGDs) were 9.9%, colonoscopies 12.3%, and advanced endoscopy procedures 11.1%. The NSR was highest in April (15.3%,P=0.01) and lowest in September (9.0%,P=0.04). There is a greater likelihood of procedural no-show for colonoscopies compared with EGDs when mean temperatures were at or below freezing (P=0.02) and with snowfall (P=0.03). NSR were also high for EGDs on federal holidays (25%,P=0.03) and colonoscopies on days following federal holidays (25.3%,P<0.01). Day of the week, wind speed, presence of precipitation, wind chill, the temperature change from the prior day, and temperature (high, low, and mean) had no significant impact on NSR. Conclusions: Our study demonstrates that scheduling adjustments on federal holidays, days when temperatures are below freezing, and snowfall may improve department resource utilization. These data, along with other variables that affect NSR for endoscopic procedures, should be taken into consideration when attempting to optimize scheduling and available resources in a safety-net hospital.