Technology | Analytics Software | December 23, 2015

Provides open source classification system for noninvasive diagnostic imaging professional services

Neiman Institute, NITOS, Neiman Imaging Types of Service, medical imaging research tool

December 23, 2015 — 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, M.D., 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, M.D., 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.

For more information: www.acr.org


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