Study Questions Widely Used Risk-Adjustment Methods
February 27, 2013
Around the country, hospitals are assessed based on the outcomes of their patients. Because one hospital may treat patients who are incredibly ill and more likely to die than other hospitals, risk-adjustment measures factor in discrepancies in patient health to ensure that any given hospital does not appear to perform worse on its assessment solely because it has sicker patients. According to a new study, these risk-adjustment methods often result in some hospitals being overpaid and other hospitals being underpaid, says Kaiser Health News.
- Risk-adjustment models were used by Medicare in determining that 2,217 hospitals should be penalized for having high rates of patient readmissions.
- The new study, conducted by the Dartmouth Atlas Project, criticizes this practice for being short-sighted and inaccurate.
- The Dartmouth authors argue that the more times patients see doctors or get tests, the more new diagnoses they are given which creates the appearance that a patient is not recovering.
The researchers examined 5 million records of beneficiaries in 306 different regions of the country. They assessed each case based on three different formulas, including the hierarchical condition categories that Medicare uses.
- After accounting for the number and nature of diagnoses for patients as well as their age, race and sex, the researchers found that the sickness of patients explained between 10 percent and 12 percent of the discrepancy between places with high mortality rates and those with low mortality rates.
- In Salt Lake City, the mortality rate was 59.3 patients per 1,000 while in Miami the rate was 32.6 patients per 1,000 -- a difference so substantial that the researchers concluded it cannot be from differences in care.
- The researchers then adjusted these numbers to account for the number of physician visits the patients had in the previous year and found that 21 percent to 24 percent of the difference between high-mortality and low-mortality areas was explained.
The results indicate that there is significant unexplained variation that is not accounted for in the different risk-adjustment formulas. Risk-adjustment formulas must be modified to account for other factors besides patient sickness to prevent overpaying or underpaying hospitals.
Source: Jordan Rau, "Dartmouth Study Questions Widely Used Risk-Adjustment Methods," Kaiser Health News, February 21, 2013. John E. Wennberg et al., "Observational Intensity Bias Associated with Illness Adjustment: Cross Sectional Analysis of Insurance Claims," British Journal of Medicine, February 21, 2013.
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