Data Science at Alley: Building Neiman’s ICE-T radiology visualization tool

Understanding healthcare services and costs is often a jumbled and confusing endeavor. Alley Interactive’s Data Science team worked with the Harvey L. Neiman Health Policy Institute to develop ICE-T (Inpatient Cost Evaluation Tool) to help simplify the process.

The new operational tool enables radiology practices and hospitals to compare internal costs to national benchmark price points to determine if a “bundled payment” — defining costs as “two or more health providers during a single episode of care over a specified time” — would be a more cost-effective route for the patient.

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ICE-T helps radiologists use risk and costs to determine if bundled payment is the best choice. ICE-T aggregates a multitude of data, such as years of national inpatient Medicare data, total hospital reimbursement, and imaging reimbursements by radiology groups, highlighting it in an easy and simple interface.

“It turns fairly complex data into a manageable visualization,” Project Manager Margaret Schneider says. “[Software Developer] Dan Bowles put together a streamlined way to understand the cost of treatment in situations that span multiple providers and situations.”

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ICE-T was also discussed during “The Crossroads of Quality, Data and Informatics in Radiology Practice and Payment Models” during ACR 2016 — The Crossroads of Radiology conference. You can also see the tool currently on the Neiman website.