Jonathan G Rogg1, Robert Huckman2, Michael Lev3, Ali Raja4, Yuchiao Chang5, Benjamin A White4. 1. Massachusetts General Hospital, Department of Emergency Medicine, Boston, MA 02114, United States. Electronic address: jrogg@alum.mit.edu. 2. Harvard Business School, Boston, MA 02163, United States. 3. Massachusetts General Hospital, Department of Radiology, Boston, MA 02114, United States. 4. Massachusetts General Hospital, Department of Emergency Medicine, Boston, MA 02114, United States. 5. Massachusetts General Hospital, Department of General Medicine, Boston, MA 02114, United States.
Abstract
STUDY OBJECTIVES: Facing increased utilization and subsequent capacity and budget constraints, ED's must better understand bottlenecks and their effect on process flow to improve process efficiency. The primary objective of this study was to identify bottlenecks in obtaining a head CT and investigate patient waiting time based on those bottlenecks. METHODS: This observational study included all patients undergoing a head CT between July 1, 2013 and June 30, 2014 at a large, urban academic ED with over 100,000 visits per year. The primary study outcome was total cycle time, defined as the elapsed time between patient arrival and head CT preliminary report, divided into four components of workflow. RESULTS: 8312 patients who had a head CT were included in this study. The median cycle time from patient arrival to head CT preliminary report was 3h and 13min with 39min of waiting time resulting from bottlenecks. In the 4-step model (time from patient arrival to head CT order, time from head CT order to head CT scheduled, time from head CT scheduled to head CT completed, and time from head CT completed to head CT preliminary report), each process was the bottleneck 30%, <1%, 27%, and 42% of the time, respectively. CONCLUSION: Demand capacity mismatch in head CT scanning has a significant impact on patient waiting times. This study suggests opportunities to improve wait times through future research to understand the causes of delays in CT ordering, CT completion and timeliness of radiology reports.
STUDY OBJECTIVES: Facing increased utilization and subsequent capacity and budget constraints, ED's must better understand bottlenecks and their effect on process flow to improve process efficiency. The primary objective of this study was to identify bottlenecks in obtaining a head CT and investigate patient waiting time based on those bottlenecks. METHODS: This observational study included all patients undergoing a head CT between July 1, 2013 and June 30, 2014 at a large, urban academic ED with over 100,000 visits per year. The primary study outcome was total cycle time, defined as the elapsed time between patient arrival and head CT preliminary report, divided into four components of workflow. RESULTS: 8312 patients who had a head CT were included in this study. The median cycle time from patient arrival to head CT preliminary report was 3h and 13min with 39min of waiting time resulting from bottlenecks. In the 4-step model (time from patient arrival to head CT order, time from head CT order to head CT scheduled, time from head CT scheduled to head CT completed, and time from head CT completed to head CT preliminary report), each process was the bottleneck 30%, <1%, 27%, and 42% of the time, respectively. CONCLUSION: Demand capacity mismatch in head CT scanning has a significant impact on patient waiting times. This study suggests opportunities to improve wait times through future research to understand the causes of delays in CT ordering, CT completion and timeliness of radiology reports.
Authors: Onyinyechi I Ukwuoma; Michael Dingeldein; Johnathan M Sheele; Alexandre T Rotta; Carolyn Apperson-Hansen; Leslie Dingeldein Journal: J Emerg Med Date: 2020-06-24 Impact factor: 1.484
Authors: Edward A Michelson; J Stephen Huff; Mae Loparo; Rosanne S Naunheim; Andrew Perron; Martha Rahm; David W Smith; Joseph A Stone; Ariel Berger Journal: West J Emerg Med Date: 2018-06-13
Authors: Jeffrey J Bazarian; Robert D Welch; Krista Caudle; Craig A Jeffrey; James Y Chen; Raj Chandran; Tamara McCaw; Saul A Datwyler; Hongwei Zhang; Beth McQuiston Journal: Acad Emerg Med Date: 2021-09-07 Impact factor: 5.221