4 - Using Business Intelligence Data Analytics to Improve Scheduling of Urgent and Non-Urgent Gastroenterology Clinic and Endoscopies in a Large Safety-Net Hospital
Jared Gloria, MD1, Jason Brown, MD2 1Emory University School of Medicine, J. Willis Hurst Internal Medicine Residency, Atlanta, GA; 2Emory University, Atlanta, GA
Introduction: In a large, 953-bed, urban safety-net hospital that provides care to a diverse population , the gastroenterology (GI) department faces scheduling challenges due to high demand, limited resources, and a burdensome referral process. Microsoft Business Intelligence (BI) analytics dashboard is a tool that can help optimize clinic operations and improve patient care. This study aims to evaluate the effectiveness of using Microsoft BI analytics dashboard to improve GI scheduling.
Methods: We conducted an analysis of scheduling data from Grady Memorial Hospital’s GI department. We used Microsoft BI analytics dashboard to analyze data, identify trends, and develop insights to improve scheduling. We collaborated with hospital administrators, physicians, and staff to design and implement a new electronic medical record (EMR) based referral order set for GI clinic visits and endoscopies.
Results: The previous referral process led to a queue of 4 204 patients awaiting endoscopy and 3286 patients awaiting clinic appointments. The new order set is user-friendly for providers but also has a built-in triage system that allows schedulers to quickly address urgent referrals. After implementing the new referral order set, we tracked the time from appointment request to scheduling across GI clinic and endoscopy referrals. We found decreases in time from request to scheduling for time-sensitive endoscopies (371 days in Jan 2023 to 177 days in April 2023). We also found decreased time between requests and scheduling in urgent and non-urgent clinic referrals (71 days in Sept 2022 to 36 days in April 2023 for urgent and 58 days in Sept 2022 to 20 days in April 2023 for non-urgent). Finally, we show decreased time from referral to scheduling for screening colonoscopy (220 days in Sept 2022 to 19 days in April 2023).
Discussion: Our study demonstrates the power of using Microsoft BI analytics dashboard to improve GI scheduling at GMH. By leveraging data-driven insights, we were able to identify and address several problems in the scheduling process. Also, by creating and implementing a new GI order set that is easy to use and has a streamlined scheduling process overseen by clinic teams, we have improved access to critical medical appointments and procedures in a vulnerable population.
Figure: Average days from order to scheduled screening colonoscopy.
Disclosures:
Jared Gloria indicated no relevant financial relationships.
Jason Brown indicated no relevant financial relationships.
Jared Gloria, MD1, Jason Brown, MD2, 4, Using Business Intelligence Data Analytics to Improve Scheduling of Urgent and Non-Urgent Gastroenterology Clinic and Endoscopies in a Large Safety-Net Hospital, ACG 2023 Annual Scientific Meeting Abstracts. Vancouver, BC, Canada: American College of Gastroenterology.
