A new resource developed by the American College of Radiology’s Harvey L. Neiman Health Policy Institute allows researchers to organize medical imaging data from claim databases into numerous categories.

The Neiman Imaging Types of Service (NITOS) platform is a free, open-source coding system that can be used to categorize data by modality, body region, clinical focus, or whether the procedure was invasive or noninvasive. NITOS was developed by Richard Duszak, MD, chief medical officer of the Harvey L. Neiman Health Policy Institute, and Andrew Rosenkrantz, MD, an affiliate research fellow.

“As medical imaging becomes increasingly subspecialized, a robust, openly available classification system is necessary to better support researchers and policymakers in their efforts,” Duszak said in a statement. Good data, along with this standardized coding system, will help in further demonstrating the role and value of imaging. The NITOS coding system addresses current gaps and inaccuracies and augments existing systems for imaging-focused initiatives.”

“NITOS allows researchers to much more easily and meaningfully mine imaging claims data,” Rosenkrantz said in the same statement. “Our goal is that NITOS will prove itself to be a valuable tool for improved insights for policy-focused, claims-based research.”

NITOS is not meant to be viewed as a replacement for the existing BETOS coding system; it is meant to complement those codes.

To create NITOS, Duszak and Rosenkrantz studied and classified Healthcare Common Procedure Coding System data billed by radiologists by using the new codes.

The system was designed so that it will update as additional information is made available, giving researchers access to the most recent, relevant imaging data possible. Revisions and corrections will also be provided as soon as they become available.

More information about NITOS, including detailed charts and tables, can be found on the Harvey L. Neiman Health Policy Institute’s website.