This study found that for the dimensions of quality measured by CAHPS, health plans with better quality were more likely to be chosen. The estimate of the CAHPS score was also practically important. If a plan improves its average CAHPS score by a standard deviation (3.57 percentage points), the associated increase in the choice probability would be 9.03 percentage points. However, for the dimensions of quality measured by the HEDIS scores, no relationship between plan quality and plan choice was noted. This is not surprising because consumers are more likely to be influenced by the quality aspects measured by CAHPS than those measured by HEDIS, which are about clinical or “technical” processes. This low-income population could get quality information measured by CAHPS more easily from their relatives, friends, and coworkers, etc. From the perspective of quality improvement, plans have less influence on the interpersonal quality dimensions as measured by CAHPS compared with those of HEDIS, because CAHPS measures are mostly based on provider-level interactions. Nonetheless, plans could improve CAHPS scores through educating providers regarding culture sensitivity, increasing reimbursement on counseling activities, or sending patients' feedback to providers.
Contrary to two previous randomized-controlled trials assessing the effect of CAHPS report cards on choice among Medicaid beneficiaries (Farley et al. 2002a
), we found a positive association between health plan quality as measured by CAHPS and plan choice. One possible reason is that those two trials evaluated the effect of additional quality information, while this study examined whether consumer plan choice was associated with quality, regardless of the sources of quality information. Overall, Farley et al. (2002a
did not find any significant effect of CAHPS report cards, but among some subpopulations, there was an effect of report cards on plan choice if these Medicaid beneficiaries did read the report cards and understand them. Furthermore, even in the absence of CAHPS reports in the control group, the authors (Farley et al. 2002b
) showed that the switching rate from the lower-rated plans was higher than that from the higher-rated plans, suggesting that consumers can perceive some quality dimensions as measured by CAHPS in the absence of report cards.
Individuals with special health care needs do value CAHPS more than those without special health care needs. It is possible that they can perceive quality information better or they put more efforts in collecting quality information. Risk selection behavior could potentially affect this conclusion. In general, this is not a problem due to the pressure of competition because a plan should practice at least an average level of risk selection in order to survive. Further, the SCHIP pricing policy is based on cost experience, which reduces financial incentives for risk selection.
There are several limitations in this study. First, the conditional logit model is subject to the IIA assumption. Because calculating marginal effects from the mixed logit model is computationally infeasible, we used the conditional logit model to interpret the results. Using the conditional logit model would lead to similar marginal effects when the distributions of independent variables of the individuals whose coefficients are close to the means are similar to those of other individuals in the sample or when the distributions of individual characteristics are independent of those of coefficients. In other words, marginal effects from the conditional logit model could be biased if the above conditions are not satisfied.
Second, it is possible that quality and plan choice are endogenous. Plans might selectively enroll or disenroll certain enrollees, which in turn could affect plan quality, because quality measures came from members who stayed in a plan for at least 12 months and they were not risk adjusted. Prior studies have suggested that individual characteristics are associated with plan quality measures (e.g., Zaslavsky et al. 2001
; Carlson et al. 2002
). Several factors, however, might mitigate this issue: (1) SCHIP enrollees only accounted for a small portion of total plan enrollees (on average 7.71 percent) based on the 2000 New York State Managed Care Enrollment Report; (2) compared with the commercial markets, SCHIP has a relatively homogeneous population; (3) plans were reimbursed on a cost basis and their incentives for risk selection were greatly reduced though not necessarily eliminated.
Third, given that the study was based on cross-sectional data, we should be cautious and not interpret the positive relationship between quality of care and plan choice as causal. It is critical to investigate whether there is a causal effect of quality on plan choice among this population because plans have incentives to improve quality only when the relationship is causal, on which policies should be based.
Our results indicate that low-income parents in New York SCHIP do choose managed care plans with better quality (as measured by CAHPS) for their children. Unless the disenrollment rates are higher among high-quality plans, a positive association of quality with plan choice among new enrollees would suggest that average quality in the market could improve overtime. Since more new enrollees would enroll into high-quality plans, the market share of high-quality plans increases over time. However, further study is greatly needed to investigate the structural relationship between quality and plan choice.