BIG DATA AND THE FUTURE OF MEDICARE AUDITS
Edward M. Roche, Ph.D.,J.D. — Barraclough NY LLC
Part II — Defending Against the Tyranny of Algorithms
In Part I of this series, we reviewed how the number of Medicare audits has increased by almost 1,000% in the past five (5) years, and how virtually no decisions by ALJs are being handed back within the statutory time frame.
We discussed also how RACs have started to rely on big data mining of hospital claims to generate large numbers of Diagnosis-Related Group (DRG) downgrades. This is costing hospitals plenty, not only in the reduction in payment revenue, but also in the constantly increasing cost of defending against audits.
The use of computer algorithms has drastically reduced the cost of conducting audits, but there has been no corresponding reduction in defensive costs for hospitals, and this is an example of what military people call “asymmetric warfare”, where the cost of defense is always disproportionately greater than the cost of offense. It is an impossible game to win.
We will now examine a few of the legal issues that are presented by the need to defend against not an audit, but against an algorithm.
The MPIM specifies that the decision to conduct an audit is “not reviewable” in a hearing. This means that even if a provider is being profiled or targeted through an artificial intelligence algorithm, they are fair game, no matter what the reason.
This lack of review-ability does not extend to the review itself. That is handled by the appeal system. The typical appeal has little success in the first two levels — reconsideration, redetermination — so the grass gets mowed with the Administrative Law Judge (ALJ). Appeals generally are based on a claim-by-claim argument regarding each patient or procedure, combined with a refutation of the statistical extrapolation, which is almost always based on shoddy work.
This litigation profile will change. Why? Rather than challenging the expertise or judgment of the audit reviewer who rejected a claim, the argument instead will be aimed at dis-crediting the algorithm responsible for the claim rejection.
But since these algorithms do not make decisions based on medical logic, but only on a pattern of statistical probabilities, the arguments against them will by necessity be couched in quasi-mathematical terms. To do so will require resort to an entirely different type of expert, and understanding of what we might call “algorithm law”. Yet, for the most part, many of today’s health law attorneys are ill-prepared to litigate this type of case.
This article appeared also in RACmonitor.