Over 1100 Total Lots Up For Auction at Two Locations - OK 12/08, UT 12/09

Four ways artificial intelligence is revolutionizing health care

March 01, 2017
Health IT
From the March 2017 issue of HealthCare Business News magazine

2: Revenue cycle management

Machine learning can easily be applied outside the realm of patient care, for example, in claims denial management. Denials are one of the most persistent problems in the revenue cycle, with the health care system devoting tremendous time, resources and money to recoding and resubmitting hundreds of billions of dollars in denied or rejected claims.

New & Refurbished C-Arm Systems. Call 702.384.0085 Today!

Quest Imaging Solutions provides all major brands of surgical c-arms (new and refurbished) and carries a large inventory for purchase or rent. With over 20 years in the medical equipment business we can help you fulfill your equipment needs

The denial of a claim can be due to multiple and complex variables, including patient, procedure, location, doctor, sequencing or payer. This means that uncovering solutions can be scattershot and infrequent. As with clinical variation, query-based approaches are time- and resource-intensive, and often fail to target the root cause of denied claims.

Machine intelligence applications are designed to find the answers by detecting all of the relationships associated with the data. Whereas human investigations into denied claims are slow and inaccurate, machine learning is able to drill down and identify the characteristics of denied or rejected claims holistically and identify changes that can be proactively driven upstream into the claims preparation workflow and potentially into point-of-care guidance.

From a revenue cycle management perspective, the ability to understand, monitor and manage clinical variation for a variety of episodes of care across the care continuum enables health systems to have a clear line of sight to their performance against bundled payments and other value-based arrangements. They will now be able to make the necessary course corrections to minimize an end-of-year shock when payers reconcile performance against contracts.

Next: Population health

You Must Be Logged In To Post A Comment