New ACR Dose Index Registry allows imaging community to measure effectiveness of dose lowering efforts

Medical imaging facilities can now submit anonymized dose information for all CT exams performed to the Dose Index Registry (DIR) — allowing them to compare their dose indices to other facilities of similar size or geographic area and to national benchmarks. Participating facilities receive periodic feedback comparing their dose levels to these benchmarks, enabling them to make any necessary adjustments to lower dose received from scans.

"The new ACR registry allows imaging providers and the imaging community to measure the effectiveness of dose lowering efforts over time. The imaging community is committed to optimizing CT dose and ensuring that patients receive only the amount necessary to get an effective medical image," said Richard L. Morin, PhD, chair of the ACR Dose Index Registry. "The Registry is a significant new tool to ensure proper CT dose use and that patients receive safe, quality imaging care moving forward."

The DIR is a new component of the ACR National Radiology Data Registry (NRDR). To participate in the new registry, a facility enrolls through the NRDR portal (https://nrdr.acr.org). Software is installed at the facility to receive dose information from the CT scanner or PACS for every CT exam performed. Data is anonymized and transmitted to the registry. Periodic reports are provided to the facility through the NRDR portal.

"The registry allows facilities to understand their dose index relative to other institutions in their area and nationwide. Right now, many facilities may know their dose levels, but not how those relate to other practices or national benchmarks," said John A. Patti, MD, FACR, chair of the ACR Board of Chancellors. "The Dose Index Registry helps imaging providers gauge how effective their dose optimization efforts are by continuously supplying measurement of their dose over time. At the national level, it provides a big picture view of how dose reduction policies are working in the clinical setting. This is a great step forward for medicine."

To overcome software compatibility issues between vendors and facilities, the ACR worked with Integrating the Healthcare Enterprise (IHE) — a global initiative that creates framework for passing vital health information seamlessly. IHE established a Radiation Exposure Monitoring Profile which allows vendors to collect and transmit information related to CT dose in a similar format. To maintain patient privacy, patient identifiers are removed at the facility before data is transmitted to the DIR.

"Dose optimization is paramount to the ACR and the larger imaging community. This registry is a leap forward in the process of optimizing patient dose and the practice of safe, quality imaging care for patients. We are proud to offer this groundbreaking medical tool to the benefit of Americans and the American healthcare system," said Harvey L. Neiman, MD, ACR Chief Executive Officer.

The Dose Index Registry is part of the overall ACR approach to medical radiation reduction, which includes mandatory accreditation of all medical imaging providers and adoption of computerized decision support/imaging ordering systems based on ACR Appropriateness Criteria®.

Source:

ACR

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Camouflage detection boosts neural networks for brain tumor diagnosis