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Improvement in MR quality control workflow and outcomes with a web-based database.

Xiangyu Yang¹, Kevin Little¹, Xia Jiang¹

¹Department of Radiology, The Ohio State University College of Medicine, Columbus, OH, USA.

Journal of Applied Clinical Medical Physics

|April 20, 2020

Summary

This summary is machine-generated.

A new web-based Magnetic Resonance (MR) Quality Control (QC) database streamlined QC workflows. This system significantly reduced technologist errors and accelerated issue resolution, improving the quality of clinical MRI studies.

Keywords:

MRI automated quality control human error web-based database

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Area of Science:

Medical Imaging
Quality Control
Database Management

Background:

Implementing robust Quality Control (QC) is crucial for ensuring the diagnostic accuracy and reliability of Magnetic Resonance (MR) imaging.
Traditional paper-based QC methods can be inefficient, prone to errors, and hinder timely issue identification and resolution.

Purpose of the Study:

To develop and evaluate a custom-built, web-based MR QC database.
To assess the impact of this database on QC workflow efficiency and outcomes at a major academic medical center.

Main Methods:

A web-based database was created using Microsoft Access and SharePoint, accessible remotely by authorized personnel.
QC technologists and Qualified Medical Physicists (QMPs) had distinct access levels for record management and approval.
An automated macro was implemented for weekly QC status reviews and notifications to QMPs.
Weekly American College of Radiology (ACR) QC findings were compared for one year pre- and post-implementation across 17 clinical MRIs.

Main Results:

The web-based database significantly reduced QC issues stemming from technologist error (59 to 24 cases).
Average time for QMPs to identify QC issues decreased dramatically from 177 days to 2 days.
Time to correction for QC issues improved from 81 days to 7 days, with a correction rate increase from 22% to 99%.

Conclusions:

The implemented web-based MR QC database positively impacted workflow and outcomes.
The system simplifies QC processes, facilitates early detection of quality deviations, and enables rapid problem resolution.
This enhances the overall quality and reliability of clinical MRI studies.