Tax Hike Not Needed to Pay for Universal Health Care Plans
Fixing Errors in Claims Can Save as Much as $250 Billion
(Austin, Texas) – April 5, 2007
Scientists at S3 Matching Technologies, who have been studying data problems for major corporations, have reached some startling conclusions regarding health care spending in the U.S. Using TeraMatch®, the company’s advanced data matching technology, S3 researchers found that improving database accuracy had the potential to reduce or even eliminate the need for tax increases to fund a Universal Health Care Plan. “Universal health care for all Americans is just not going to get done unless it is financially feasible,” said Jack Holt, CEO of S3 Matching Technologies. “And cleaning up data problems is the simplest way to find the money without new taxes. When our company applied sophisticated data matching software models to both hospitals and insurance claims processing, we projected a cost reduction that easily paid for a health care plan for everyone in our country.”
According to PNC Financial Services Group’s Healthcare Industry Study “Reducing U.S. Health Care Costs Through Electronic Claims and Payment Processing” about 30 percent of the U.S.’ $2.1 trillion annual spend on health care is consumed by administrative expense, which is more than $600 billion. Based upon analyses by its own researchers and its experience with Fortune 50 corporations, S3’s experts estimate as much as 50 percent of administrative expenses is due to bad data produced by poor claims processing.
“Even the most conservative interpretation of our analyses means there is about $250 billion annually being lost due to bad data in provider and payer claims,” said Andi Gillentine, director of the health care vertical for S3. “That’s far more than what is needed to pay for presidential candidate John Edwards’ $180 billion estimate for universal health care.”
The PNC study offers evidence of how money is lost to bad health care data. According to the findings, a health care provider like a hospital has to submit a claim to an insurance company an average of 11 times before receiving payment, and insurance companies go back to providers at least twice to acquire all necessary information.
“Bad data used to be an acceptable part of business,” Holt explained. “Just like dropped calls were tolerated during the evolution of the cell phone industry. But the technology is now available to fix the data problem.”
According to Holt, a culture of inefficiency developed in the health care industry and bad claims processing has been viewed as an insurmountable problem. New technology, however, means the financial losses from bad data can be confronted in a manner that benefits patients, providers, and insurance companies.
“Claims processing errors have not been adequately addressed in the past,” CEO Holt added, “The data technology was not sufficiently evolved and an unrealistic investment was required of hospitals and insurers. But we can now address this problem very quickly with something like a national clearinghouse for claims data.”
About S3 Matching Technologies (www.S3.com)
S3 is an Austin, Texas based company focused on providing data quality management software for the IT, telecom, financial services, and healthcare industries. S3 invented TeraMatch®, a rules-based matching engine which uses algorithmic scoring based on industry-specific best practices. S3’s software may be deployed as licensed software or as a managed solution.