|
Article Excerpt
During the last two decades, enrollment in managed care plans has increased from 27 percent of the employees with employer-based insurance coverage in 1988 to 97 percent in 2007 (Kaiser Family Foundation 2007). The rise in managed care has heightened the importance of measuring and improving quality of managed care plans. Quality measurement tools have been developed since the 1990s, such as the Consumer Assessment of Health Hans Survey (CAHPS) and the Health Plan Employer Data and Information Set (HEDIS). In addition, the federal and state governments have invested in managed care quality improvement, including developing measurement tools. In New York State, all managed care plans have been required to report quality data to the Department of Health since 1994 (NYSDOH 2002). Hans with quality measures lower than the state average have to submit a report including identification of the reasons and actions to be taken (NYSDOH 2000). A quality incentive program has been implemented in Medicaid managed care plans since 2001, where plans can get a premium bonus up to 3 percent depending on whether their quality measures exceed the 75th percentile of the benchmarks (Zuckerman 2007).
In addition to government regulation and other quality improvement methods, market competition based on consumer choice could be one approach to improving managed care quality, which hinges on the consumer's ability to choose managed care plans with higher quality. Quite a few studies have been conducted on the effect of quality on health plan choice. Early studies demonstrated that Medicare beneficiaries with higher incomes and employer-sponsored insurance coverage were more likely to purchase high-quality supplemental insurance using proxies of quality (Rice, McCall, and Boismier 1991), and that noisy quality measures of quality were better than nothing (Harris 1996). More recent studies can be classified into three groups: laboratory experiments; empirical studies on the effect of quality reports; and empirical studies on the effect of plan quality, regardless of the sources of quality information. In experiments, the information on plan quality and other plan features of hypothetical health plans is the only source of information, and they directly test whether quality would affect plan choice. Laboratory experiments consistently showed that better quality led to a higher demand after controlling for other factors (Spranca et al. 2000; Schoenbaum et al. 2001; Harris 2002; Uhrig and Short 2002).
The first study systematically investigating the effect of quality reports (HEDIS 2.0) on plan choice was done by Chernew and Scanlon (1998), where they analyzed the choices of 5,795 active, nonunion employees from a Fortune 100 company. Though some quality measures were positively correlated with the probability of choice, there existed a weak or counterintuitive relationship between quality measures and choice for other measures such as surgical care, physician quality, and preventive care. A similar study by the same authors also demonstrated that employees did not respond strongly to health plan quality ratings (Scanlon and Chernew 1999). The CAHPS demonstration in Washington showed that those state employees who used the CAHPS report were more likely to switch health plans (Guadagnoli et al. 2000). Two randomized-controlled trials conducted among new Medicaid beneficiaries in New Jersey and Iowa did not yield significant overall effect of CAHPS reports (Farley et al. 2002a, b). Several studies made use of natural experiments occurring at Harvard University, General Motors, and in the federal government system and illustrated that quality information did affect the consumer's plan choice (Beanlieu 2002; Scanlon et al. 2002; Wedig and Tai-Seale 2002). Jin and Sorensen (2006) measured the effect of publicized health plan rating information of the National Committee for Quality Assurance (NCQA) after controlling for the effect of nonpublic health plan ratings, and they concluded that publicized information had an effect on plan choice, especially among individuals who were choosing a plan for the first time. Health plan switching behavior, however, was not associated with quality information, according to a study by Abraham et al. (2006). One empirical study by Chernew et al. (2004) directly investigated the effect of plan quality (as measured by CAHPS and HEDIS) on employer's plan choice, finding that large employers were more likely to select health plans with higher quality measures.
More than four million children across the United States are enrolled in the State Children's Health Insurance Program (SCHIP), mostly in managed care plans (Shone and Szilagyi 2005). The New York SCHIP program (1) relies on managed care plans to provide health services for enrollees, and plans receive monthly prepaid premiums from families or the state government or both. In 2005, 28 managed care plans provided SCHIP; this accounted for 74 percent of the managed care organizations operating in the state (NYSDOH 2006). The state government closely monitors managed care quality of care and releases annual plan quality reports.
Few studies have examined the relationship between health plan quality and enrollment in SCHIP plans. This is important because of the implications it has for market-driven improvements in health care quality, either by simply directing more enrollment to high-quality plans or by providing a market advantage to high-quality firms. Of note, price does not play a role in SCHIP plan choice because the premium is determined by family income and is the same across SCHIP plans, suggesting that differences in quality would be central to enrollment choice. Though it is critical to understand the causal effect of quality on plan choice, a positive association of quality with plan choice among new enrollees implies that overall quality could improve over time simply because of the dynamics of enrollment. Despite the policy debates and research focusing on quality of care in the last two decades, it remains unclear whether quality improvement can be better achieved by regulatory approaches or through market competition, and our study could inform policymakers and the SCHIP administration.
CONCEPTUAL MODEL
We based our analysis on the assumption that consumers are rational agents that maximize utilities reflecting preferences across alternatives varying in benefits and costs. There are several plan attributes that could affect consumer's demand, including price, coverage, quality, geographic location, and the information about these attributes, while individual or...
|
