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Program Information

Development of An Automated MR Quality Control Program in Compliance with American College of Radiology (ACR) Accreditation Requirements

Kiaran McGee

K McGee*, S Stiving, Z Bao, D Lanners, T Peterson, R Jonsgaard, Mayo Clinic, Rochester, MN

MO-A-Salon BCD-2 Monday 7:30:00 AM - 9:30:00 AM Room: Salon BCD

In 2008, the Medicare Improvement for Patients and Providers Act (MIPPA) was signed into US public law. Amongst its many provisions, the new law required that all providers of CT, MRI, breast MRI, nuclear medicine and PET examinations that bill under part B of the Medicare Physician Fee Schedule be accredited by January 1, 2012 with noncompliance resulting in the loss of Medicare reimbursement for these services. Since that time this requirement has been adopted by at least one major private insurance provider. The insistence of accreditation in return for payment by both government and private payers has resulted in the widespread adoption of accreditation of advanced imaging facilities within the US. By far the largest accreditation program is that run by the American College of Radiology (ACR) and includes two components; 1) an initial application that involves the submission of both clinical diagnostic and phantom image data, and 2) following successful accreditation the establishment of a routine quality control program involving calculation, on a weekly basis, of a variety of metrics from MR images of an ACR-designed image quality phantom. While the ACR provides detailed methods for manually calculating these metrics, they are time consuming, prone to human bias and error. In addition these measurements can take tens of minutes. For centers with more than one MR scanner performing these quality control checks can be a significant time constraint for technologists and other support staff. To address this, we have developed an automated, web-based quality control program. The program involves daily acquisition of ACR MR phantom data, transfer of the data to a remote workstation, processing of these images to extract ACR recommended quality control metrics, and storage of these data in an institutional relational database. Data are then reviewed remotely through an in-house quality control web application. The web application indicates whether or not each test is within user defined limits thereby determining the pass/fail status of the test. Manual data entry is allowed in accord with ACR requirements. The system was first introduced into our clinical practice in 2006 starting with 8 MR scanners and since that time has been expanded to include 38 MR scanners located at the three campuses of the Mayo Clinic (Rochester, MN, Scottsdale, AZ, and Jacksonville, FL). To date, a total of 59,775 phantom studies at field strengths of 1.5T and 3.0T from two MR scanner manufacturers have been processed by this tool. In addition, the application has been successfully commercialized and is offered on a fee-for-service basis by an independent startup company.

Learning Objectives:
1. Describe the process of developing this system,
2. Describe the pitfalls and challenges encountered,
3. Identify the value of such an approach given the increasing financial constraints experienced by many radiology departments,
4. Provide examples of system detected failures and their root cause, and
5. Describe the commercialization process. Finally, recommendations will be provided for those wishing to develop similar systems for compliance with ACR accreditation recommendations.

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