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insurance and employment status, and OOP premiums, among other topics. A separate employer survey collected information on employer premium contributions.
To analyze these data, AHRQ groups services into broad categories: hospital inpatient stays, emergency room visits, outpatient services (i.e., physician and non-physician office-based provider visits), prescribed medicine fills and refills, dental visits, home health care, and supplies and equipment. Dr. Banthin recognized these categories as less detailed than the categories used to analyze claims data, but said the level of detail is a function of the information collected. For instance, MEPS collects information on the reason for a visit, but it does not collect data on the type of provider.
Relevant Findings from MEPS
Next, Dr. Banthin described relevant trends in the 2001 through 2005 MEPS data. For these analyses, she considered individuals who live in families with high total OOP financial burden (i.e., spending 10 percent or more of their income on health care):
From 2001 through 2005, the percent of individuals in the U. S. nonelderly population who live in families with high financial burden rose from 15.9 percent to 19.1 percent.
While poor families (under 100 percent of the FPL) are the most likely to have high financial burdens (29 percent of poor families have a high financial burden), one in five low-income (families between 100 and 200 percent of the FPL) and low-middle-income families (families between 200 and 300 percent of the FPL) also reach this level of spending.
A greater proportion of women ages 50-64 (30 percent) live in a family with a high financial burden than females 18-50 years or males 18-64 years (Banthin, 2011).
In addition to these findings, Dr. Banthin described the financial burden of individuals both with and without employer-sponsored insurance (ESI). Compared with the uninsured and individuals with ESI or public insurance, individuals with private non-group coverage spend significantly more of their income on total OOP expenses (see Figure 14-1). This result, Dr. Banthin said, is because the total OOP spending includes premiums. Comparatively, she said, the uninsured have a lower financial burden because they do not pay premiums and because “they may restrict their health care services in order to avoid having to pay out-of-pocket.” However, when Dr. Banthin separated the uninsured into those with a chronic condition and the uninsured without a chronic condition, the uninsured with a chronic condition had a much higher level of burden (27 percent vs. 9 percent, respectively).
Committee member Mr. Michael Abroe noted that Figure 14-1 provides an apt opportunity to compare the private non-group insurance group with the uninsured group; both groups, he pointed out, are likely comprised of families without access to the ESI market. In 2005, 53 percent of families with private non-group insurance had a high financial burden, whereas in this same year, only 15 percent of uninsured families had a high financial burden. Mr. Abroe asked whether this 38 percent difference results from income differences between these two groups, because the uninsured individuals forego care, or because having insurance “induces” increased use of medical care. Dr. Banthin said all of his hypotheses likely factor into the 38 percent difference and cited research that explored the incomes and assets of people who did not have access to the ESI market (Bernard et al., 2009). People who purchased private non-group insurance “tend to have considerably higher wealth, even holding income constant,” she said. “But ignoring wealth for a minute, the uninsured definitely have lower incomes on average than the private non-group [individual],” and they use much less care (Bernard et al., 2009).
Committee member Mr. Schaeffer noted that the graph depicted in Figure 14-1 shows a distinct trend: the percent of families with a high financial burden increased from 2001 through 2003 and then decreased or remained steady from 2003 to 2005 (Banthin, 2011). Dr. Banthin commented that these trends are likely the result of trends in the MEPS data, which reflects activity in the economy.
Next, Dr. Banthin explored the distribution of OOP expenses for individuals with a “very high financial burden,” which she defined as spending more than 20 percent of family income on OOP health care expenses. In 2003, these individuals spent, on average, $1,528 in OOP expenses; approximately 50 percent was spent on