Predicting the future: introducing business analytics to endoscopy units

Abstract

Background and aims: currently, most endoscopy software only provides limited statistics of past procedures, while none allows patterns to be extrapolated. To overcome this need, the authors applied business analytic models to predict future demand and the need for endoscopists in a tertiary hospital Endoscopy Unit. Methods: a query to the endoscopy database was performed to retrieve demand from 2015 to 2021. The graphical inspection allowed inferring of trends and seasonality, perceiving the impact of the COVID-19 pandemic, and selecting the best forecasting models. Considering COVID-19’s impact in the second quarter of 2020, data for esophagogastroduodenoscopy (EGD) and colonoscopy was estimated using linear regression of historical data. The actual demand in the first two quarters of 2022 was used to validate the models. Results: during the study period, 53,886 procedures were requested. The best forecasting models were: a) simple seasonal exponential smoothing for EGD, colonoscopy and percutaneous endoscopic gastrostomy (PEG); b) double exponential smoothing for capsule endoscopy and deep enteroscopy; and c) simple exponential smoothing for endoscopic retrograde cholangiopancreatography (ERCP) and endoscopic ultrasound (EUS). The mean average percentage error ranged from 6.1 % (EGD) to 33.5 % (deep enteroscopy). Overall, 8,788 procedures were predicted for 2022. The actual demand in the first two quarters of 2022 was within the predicted range. Considering the usual time allocation for each technique, 3.2 full-time equivalent endoscopists (40 hours-dedication to endoscopy) will be required to perform all procedures in 2022. Conclusions: the incorporation of business analytics into the endoscopy software and clinical practice may enhance resource allocation, improving patient-focused decision-making and healthcare quality.