EDITOR’S NOTE: James Jones, MD, senior medical director of clinical documentation and quality improvement (CDQI) at Mount Sinai Health System in New York, will conduct a webcast on Thursday, Dec. 15, 2016 during which time he will update attendees on Mount Sinai’s battle against diagnosis-related group (DRG) downgrading caused by cyber audits.
Examination of patent data indicates that Recovery Audit Contractors (RACs) likely are using computer algorithms to flood the nation’s healthcare system with audits. In the last five years, the incidence of RAC audits have grown by 936 percent.
Optum, Inc. of Minnesota (associated with UnitedHealthcare) has applied for a patent on “computer implemented systems and methods of healthcare claim analysis.”
The information system envisaged in this patent appears to be specifically designed to downgrade codes. It works by running a simulation that switches out billed codes with cheaper codes, and then measures if the resulting code configuration is within the statistical range averaged from other claims.
These algorithms can be applied to hundreds of thousands of claims in only minutes. The same algorithm can be adjusted to work with different DRGs. This is only one of many patents in this area.
By using artificial intelligence (advanced statistical) methods of reviewing Medicare claims, RACs can bombard hospitals with so many diagnosis-related group (DRG) downgrades (or other claim rejections) that it quickly overwhelms a provider’s defenses.
We should note that the use of these algorithms is not really an “audit.” It is not done by any doctor or healthcare professional. The algorithm could just as well be counting how many bags of potato chips are sold with cans of beer. It doesn’t care.
If the patient is not an average patient, and the disease is not an average disease, and the treatment is not an average treatment, and if everything else is not “average,” then the algorithm will throw out the claim. This has everything to do with statistics and correlation of variables and very little to do with understanding whether the patient was treated properly.
These big data audits are not what they say they are, because they substitute mathematical algorithms for medical judgment.