SmarterDx Debuts AI Tool to Combat Hospital Payer Denials

Clinical artificial intelligence firm SmarterDX introduced a tool to help hospitals deal with payer denials.

SmarterDenials helps hospitals craft stronger appeal letters using the company’s AI to identify evidence more quickly, according to a Monday (Oct. 28) press release.

“The stakes are high,” the company said in the release. “Today, 15% of all claims are initially denied, and hospitals spend over $20 billion annually trying to overturn them. Payers often send denials via fax or traditional mail, and after receipt, it can take hospital denials staff hours, sometimes days, to review these denials and compose clinical appeal letters. SmarterDenials streamlines this burdensome administrative process, cutting the time it typically takes to craft an appeal down to minutes, saving hospitals time and money.”

The tool uses SmarterDx’s proprietary clinical AI platform to deal with “complex denials” such as diagnosis-related group (DRG) downgrades and level-of-service disputes, the release said.

Hospitals can upload denied claims, and SmarterDenials analyzes the patient record, identifying documentation that justifies the care the hospital provided to produce an appeal letter backed up by “case-specific clinical evidence” and coding references, according to the release.

“As payers tighten approval criteria, SmarterDenials empowers hospitals to fight back more efficiently, reducing administrative burden and improving outcomes,” the release said.

SmarterDenials is the latest example of the healthcare industry employing AI to streamline operations. Last week saw Amazon One Medical introduce AI tools designed to reduce the time family physicians spend on paperwork.

These tools can take notes, summarize medical records, respond to patient messages and route tasks to the most suitable person, reducing the time spent on administrative tasks by 40% compared to industry standards.

At the same time, the Food and Drug Administration (FDA) is advocating for continuous monitoring of AI tools used in healthcare.

“Given the capacity for ‘unlocked’ models to evolve and AI’s sensitivity to contextual changes, it is becoming increasingly evident that AI performance should be monitored in the environment in which it is being used,” Dr. Haider J. Warraich and colleagues from the FDA said. “This need for postmarket performance monitoring of AI has profound implications for the management of information by health systems and clinical practices.”

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