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Journal of Digital Imaging

, Volume 32, Issue 2, pp 221–227 | Cite as

A Pilot of Data-Driven Modeling to Assess Potential for Improved Efficiency in an Academic Breast-Imaging Center

  • Tali Amir
  • Bonmyong Lee
  • Ryan W. Woods
  • Lisa A. Mullen
  • Susan C. HarveyEmail author
Article

Abstract

Patient satisfaction and department efficiency are central pillars in defining quality in medicine. Patient satisfaction is often linked to wait times. We describe a novel method to study workflow and simulate solutions to improve efficiency, thereby decreasing wait times and adding value. We implemented a real-time location system (RTLS) in our academic breast-imaging department to study workflow, including measuring patient wait time, quantifying equipment utilization, and identifying bottlenecks. Then, using discrete event simulation (DES), we modeled solutions with changes in staffing and equipment. Nine hundred and ninety-nine patient encounters were tracked over a 10-week period. The RTLS system recorded 551,512 raw staff and patient time stamps, which were analyzed to produce 17,042 staff and/or patient encounter time stamps. Mean patient wait time was 27 min. The digital breast tomosynthesis (DBT) unit had the highest utilization rate and was identified as a bottleneck. DES predicts a 19.2% reduction in patient length of stay with replacement of a full field digital mammogram (FFDM) unit by a DBT unit and the addition of technologists. Through integration of RTLS with discrete event simulation testing, we created a model based on real-time data to accurately assess patient wait times and patient progress through an appointment, evaluate patient staff-interaction, identify system bottlenecks, and quantitate potential solutions. This quality improvement initiative has important implications, potentially allowing data-driven decisions for staff hiring, equipment purchases, and department layout.

Keywords

Patient experience Breast imaging Value Efficiency Real-time location system 

Notes

Acknowledgements

We would like to thank Charlene Tomaselli and the Johns Hopkins (Radiology) Information Technology team.

Sources of Support

This research project was sponsored in part by St. Onge Company, a supply chain engineering company. The RTLS hardware was a donation provided by CenTrak for research purposes only.

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Copyright information

© Society for Imaging Informatics in Medicine 2018

Authors and Affiliations

  1. 1.Memorial Sloan Kettering Cancer CenterNew YorkUSA
  2. 2.Johns Hopkins MedicineBaltimoreUSA
  3. 3.University of Wisconsin School of Medicine and Public HealthMadisonUSA

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