Leapfrog unveils way to gauge cost of medical errors

Health insurance purchasers can plug their claims data and rankings for hospitals in their area into a free online calculator to see what The Leapfrog Group estimates as the hidden surcharge they pay because of medical errors in general acute care hospitals.

“The Hidden Surcharge Calculator,” unveiled in late July with a white paper discussing how the tool works, estimates that purchasers pay on average an extra $7,880 for a patient admitted to a hospital that receives a “C,” “D,” or “F” ranking on Leapfrog’s “Hospital Safety Score.” Leapfrog created the safety scores in 2012 based on patient safety efforts and outcomes at more than 2,500 general acute care hospitals in the U.S. and made them available through a website and mobile phone app.

Leapfrog, which for years has issued reports on how well hospitals meet safety standards, said that even “A”-graded hospitals aren’t immune to extra costs because of medical errors and estimated that the average hidden surcharge at these hospitals is $5,935 per patient.

“Because we study patient safety, we were not surprised by the numbers. We think the numbers are probably underestimated,” said Leapfrog President and CEO Leah Binder. “We know patient safety is a huge problem.”

She said physicians in hospitals can help change the culture and advocate to improve patient safety.

“Physicians are looked to as arbitrators of what is right and just in health care,” she said. “When physicians entrust hospitals with their patients, they should expect the highest standards are being met.”

In addition to using the Hospital Safety Scores, the calculator incorporated information from literature available on the costs of errors, accidents and injuries in U.S. hospitals. It also made assumptions based on national data on medical inflation and shifting costs. More detailed information about what they specifically incorporated is available online.

AHA sees mistakes

In a statement, the American Hospital Assn. said the safety tool “makes a number of erroneous assumptions in methodology.” The group said the calculator looks at California infection information and projects it onto the rest of the country “without clearly defining how the methodology adjusts for a variety of factors.” The AHA also took issue with the tool comparing reported data to claims data, “with any differences between the data sets attributed to unreported errors.”

“A number of other factors could be the reason for the differences in the data, so … making this assumption is not methodologically sound,” the AHA said. “Finally, the literature in this area has a wide range of other factors that account for changes in regard to cost, not the narrow definition provided in this tool. Without additional reference points or validation, the methodology of this new tool is seriously flawed.”

The Leapfrog Group rejects those arguments.

“I stand by our methodology,” Binder said. “Employers can go to the spreadsheet and use parts of the data or all of the data. It is customizable.”

She said her group had to make assumptions about certain things because there is so little transparency in errors made at hospitals.

“It would be better if we could have looked at all errors at each hospital, but we don’t have that transparency,” Binder said. “We would like to see that transparency.”

The Massachusetts-based Disease Management Purchasing Consortium, which provides strategy and procurement services to support more than 100 health plans, employers and states, awarded the Hidden Surcharge Calculator “Gold Standard” status, the consortium’s top ranking for groups that show savings when the costs are measured validly.

Al Lewis, the consortium’s president, said in a statement that Leapfrog “used the best available evidence and a rigorous process to build the Hidden Surcharge Calculator. Most importantly for the Gold Standard acceptability, the math is correct, the calculations are transparent and the assumption, all linked to authoritative sources, may nonetheless be changed by a user who prefers different assumptions.”