Through data analysis, hospitals can track denials, improve appeals success rates and recoup revenue losses that threaten their very survival.

Early last year, when Modern Healthcare reported that a deluge of reimbursement claim denials had driven U.S. hospitals toward a “crisis point,” it highlighted an alarming market imbalance between payers and providers. Across the board, MH found that public and private insurers have stepped up the speed and frequency of their denials by relying on AI-assisted algorithms, by adding new claim-submission criteria to online forms, and by tweaking the small print in contracts (which are frequently auto-renewed). Such tactics have enabled payers to deny—at least initially—almost one in 10 claims. The estimated cost to providers? Nearly 2% of patient revenue.

For hospitals, many of which operate at razor-thin 1.6% margins, that’s a life-and-death figure. Indeed, many hospitals’ survival now depends on how swiftly they can integrate data analytics into their revenue cycle management. As an attorney who advises hospitals, I have seen time and again how sound data analytics can act as a counterbalance to insurers’ aggressive denials. Data analytics help providers identify inadequate payments, understand why their claims are being denied, and bolster their appeals. The quality of a provider’s dataset also makes or breaks its chances in achieving a meaningful recovery when disputes advance to litigation or arbitration. In addition, as the U.S. healthcare industry moves toward a value-based reimbursement model for providers and health care plans alike, the ability to produce reliable performance metrics has become increasingly important for everyone involved.

As the late business management guru Peter Drucker observed, “What gets measured gets managed.” Here’s a primer on how hospitals can benefit from data analytics while also delivering top quality value-based care....

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