NITOS coding platform allows users to examine role and value of medical imaging

NewsGuard 100/100 Score

A new free resource allows researchers to use Medicare and other payer claims databases to identify and meaningfully characterize medical imaging by noninvasive or invasive procedures, modality, body region and clinical focus. Developed by the Harvey L. Neiman Health Policy Institute, the Neiman Imaging Types of Service (NITOS) coding platform is an open source classification system, allowing users to readily extract utilization and cost data to examine the role and value of medical imaging.

"As medical imaging becomes increasingly subspecialized, a robust, openly available classification system is necessary to better support researchers and policymakers in their efforts. Good data, along with this standardized coding system, will help in further demonstrating the role and value of imaging," noted Richard Duszak, MD, FACR, chief medical officer and senior research fellow. "The NITOS coding system addresses current gaps and inaccuracies and augments existing systems for imaging-focused initiatives," he added.

NITOS was developed by Duszak and Andrew Rosenkrantz, MD, MPA, affiliate research fellow, who both have experience in Medicare claims-based health services research. They reviewed and classified radiologist-billed Healthcare Common Procedure Coding System (HCPCS) codes from recent years. The common lexicon applies a hierarchical structure for coding diagnostic imaging professional services.

"NITOS allows researchers to much more easily and meaningfully mine imaging claims data," said Rosenkrantz. Updates and revisions will be posted as new information becomes available (such as the next Centers for Medicare & Medicaid Services release of provider claims summary data), he indicated. "Our goal is that NITOS will prove itself to be a valuable tool for improved insights for policy-focused, claims-based research," he added. Additional information may be found in the related report.

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...
Genetic and lifestyle factors linked to brain network aging, study reveals