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Improvements in MR Quality Assurance Workflow and Outcomes with a Web-Based Quality Control Database

X Yang*, K Little , X Jiang , D Hintenlang , The Ohio State University, Columbus, OH


(Saturday, 3/30/2019)  

Room: Exhibit Hall

Purpose: To describe a custom-built, web-based MR Quality Control (QC) database, and to make a preliminary assessment of its impact on the Quality Assurance (QA) process in a large U.S. hospital.

Methods: The MR QC database was built with Microsoft Access 2010 and published on a Microsoft Sharepoint website owned and maintained by the authors’ institution. Authorized users can access the database remotely with mainstream web browsers. QC technologists were granted access to add, review, and print daily and weekly QC records. Qualified medical physicists (QMPs) were granted additional access to edit, review, and approve existing QC records, and to change tolerance limits. A macro was utilized to conduct an automatic weekly review of QC status, and to email the results to a QMP. This web-based QC database were implemented on five clinical MRIs at the authors’ institution. Weekly ACR QC findings within five months before and after implementation were compared.

Results: Retrospective review of the conventional QC records before implementation revealed 26 QC issues. After the adoption of the new web database, the number of QC issues reduced by 38% to 16. Since only a small fraction of these issues were reported at the time of occurrence, the web-based database permitted the QMPs to more quickly identify a QC issue (before/after: 7.6±7.5/1±0 weeks, P=0.0002). Among the 26 QC issues occurred before the implementation, 8 issues (31%) would have been handled differently had they been identified earlier. The time to corrective actions was also found to be slightly shorter with the web-based system, although the difference is not statistically significant (before/after: 3.2±2.7/1.7±2.1 weeks, P=0.3).

Conclusion: The web-based QC database provides a positive impact on our MR QA process. It enables early detection and facilitates resolution of potential issues that may affect the quality of clinical MRI studies.

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