Abstract

Kaplan-Meier Curve: Requirement of further therapy in IBD and non-IBD patients. Sa1491 Automating Endoscopy Unit Efficiency Metrics: Leveraging the Electronic Health Record for Process Improvement Ziad Gellad*, David Chermak, Emmanuel Brown, Javad Taheri Duke University Medical Center, Durham, NC; Durham VA Medical Center, Durham, NC; Industrial and Systems Engineering, North Carolina State University, Raleigh, NC Purpose: Improving efficiency in GI endoscopy is both a business mandate and a quality imperative. Meaningful endoscopy unit efficiency metrics have been published but access to reliable time data impedes use of these measures. Methods: We developed a custom query of our electronic health record (Epic, Verona, WI) to obtain time tracking data for gastrointestinal endoscopy procedures occurring in our hospital based endoscopy unit and smaller ambulatory surgical center. Physicians in these units perform a broad array of diagnostic and therapeutic endoscopy with a mix of anesthesia and non-anesthesia sedation. To obtain time stamps, we first mapped the flow of patients through the endoscopy unit as a series of discrete events from check-in to discharge. Secondly, through a process of observation and qualitative analysis, we identified specific nursing and physician activities within the electronic health record that corresponded to the beginning and end of each discrete event. Thirdly, we identified specific data elements in the electronic record that indicated time parameters for these events. Fourth, we queried the electronic record data tables to build a custom dataset of time stamps for each completed patient encounter. Required time stamps were available in over 95% of encounters; missing time stamps were excluded from calculations. Finally, we calculated a set of efficiency metrics from this dataset that included: Procedure Volume, Room Utilization, Overtime, On-Time Start, Room Turnover Time, and Patient Waiting Time. Results: Between July 1, 2013 and June 30, 2014, we collected time stamp data on 3,741 cases in the ambulatory surgical site and 5,743 cases in the hospital based unit. Efficiency metrics, averaged monthly over the time period of collection, are outlined in the table. The ambulatory site was more efficient than the hospital based unit across all metrics. Conclusions: Through careful process mapping and workflow standardization, the electronic health record can be leveraged to collect time data for endoscopy unit efficiency metrics. Collection of these metrics can be used to benchmark against other practices and help guide process improvement activities. Average monthly endoscopy unit efficiency metrics (mean, sd)

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