Duration: | 2014 - current |
Technologies: | C++, Qt, Wt, Redash, PostgreSQL |
Collaborators: | Roy Wiggins |
Website: | yarra-framework.org/logserver |
Yarra LogServer is an add-on component to the Yarra Framework, which allows collecting clinical workflow data from all MRI scanners across the enterprise. After installation of the software in the intranet, the Yarra RDS Clients running on the different MRI scanners send information about all performed exam protocols and sequences to the LogServer, where the data gets aggregated and stored in a central database. The transfer of workflow data happens automatically every hour without impact on the clinical operation.
Because Yarra LogServer stores the collected workflow data in a standard PostgreSQL database, various Business Intelligence (BI) software tools can be used to analyze and visualize the data, such as Tableau or Qlik Sense. In our case, we mostly utilized Redash and Metabase, which are web-based open-source tools that allow rapid generation of dashboards and offer high flexibility for writing custom queries in the SQL language. A key advantage of both tools is that all data remains on the server, which ensures that PHI data stays protected. The web-based approach makes it also very easy to share dashboards within the department through access-restricted URLs.
In addition to the workflow data retrieved from the MRI scanners, the LogServer database can be supplemented with information from complimentary sources, including data from the EHR system, radiology scheduling system, and dictation system. Moreover, we integrated custom-developed devices for tracking the patient-preparation and room-cleaning time, and we integrated patient-pathway tracking using RFID wristbands to identify possible bottlenecks in the workflow surrounding the imaging devices.
Over the years, we developed numerous dashboards based on the LogServer data, both for supporting research projects as well as for making informed decisions regarding the optimization of imaging protocols and examination procedures. Examples include the determination of optimal scheduling strategies, identification of protocol inconsistencies across scanners, comparison of exam efficiency between imaging sites, monitoring of scanner utilization and turnaround times, as well as measurement of efficiency improvements after implementing workflow changes.
To evaluate the efficiency gain of the circuit approach, the Yarra LogServer software was utilized to measure the transition time in thousands of patients. Both scanners with circuit procedure achieved transition times of less than 2 minutes, while the average transition time on a regular reference scanner was around 7 minutes. The 5 minutes saved per exam translate into 3-4 additional exam slots per day, resulting in significant cost savings over time.
Recht MP, Block KT, Chandarana H, et al. Optimization of MRI Turnaround Times Through the Use of Dockable Tables and Innovative Architectural Design Strategies. AJR Am J Roentgenol. 2019; 212(4):855-858