We find a negative association between nonprice managed care competition and quality of care. Three previous studies of HMO price competition and quality of care provide mixed evidence, but the study by Scanlon et al. (2005)
also shows a negative association between HMO competition and three out of six quality domains based on CAHPS and HEDIS measures. The state government sets prices based on a plan's previous cost experience, which is somewhat similar to the Medicare hospital pricing policy before the PPS. However, we do not observe a positive correlation between competition and quality of care as occurred in the hospital industry before 1983, which might be explained by several other potential factors that are worth examination.
Even if we use the 2SLS method with market population as an instrument to address the endogeneity problem, there still exists a concern that it is not sufficient. Simple OLS models show similar negative associations and result in a bias toward zero compared with 2SLS. For “provider communication” and “child immunization,” the coefficients are biased upward, while the coefficients for “problems with getting care needed” and “problems with services” are biased downward because lower scores are preferred for the later two measures. This is exactly what one would expect if competition, as measured by the number of plans, is positively correlated with the error term. We also try the instruments one at a time in the second stage regressions and the results are similar. Compared with 2SLS, the magnitudes of the coefficients of competition slightly increase when population is the only instrument, and slightly decrease when poverty level is the only instrument, but the significances are the same. Moreover, overidentification tests for different quality measures also support the validity of our instruments except for “provider communication.” Therefore, it is unlikely that the endogeneity problem has led to our findings.
Three HEDIS measures are SCHIP specific, while the CAHPS measures are not because the state does not conduct a member satisfaction survey for SCHIP separately. It is interesting that a negative association is observed both for HEDIS and CAHPS measures. There are three potential explanations. First, it is possible that the SCHIP product line quality might result from the spillover effect when health plans set the quality level for other product lines. It is not an easy task for plans to implement these separate decisions because different products often share the same group of providers, which is one of the reasons that the measures of other product lines are highly correlated with those of the SCHIP product line.
Second, SCHIP competition and prices are highly correlated with those of other product lines. Because population is one of the primary determinants of the demand for health insurance, it is highly possible that competition in different product lines is very similar. The state government uses plans' previous cost experience to set prices, and consequently, the prices could also be highly correlated to those of other product lines.
Third, the results could be affected by physician market competition. Health plans can affect physicians' quality of care through different management tools or contractual arrangements, but the extent to which a health plan can affect the physicians' quality at the market level remains largely unknown. In the physician market, competition generally takes the form of price competition, where more competition can lead to either higher or lower quality. Therefore, given the limited extent to which health plans can affect the providers' quality, the negative association between competition and quality in the health plan market might result from the same association in physician markets where more price competition could be associated with lower quality.
In addition to the possible explanations discussed above, there are limitations that would limit our ability to explain the findings. First, the quality measures used in this study are not risk adjusted. In other words, we are not able to tease out the consumers' effect on the quality of care. Second, the sample sizes are relatively small. Although the regressions have a fairly large explanatory power, there are only 62 markets in the first-stage regression and 29 in the second-stage regressions. New York State has been releasing managed care plan quality reports since 1994, and it is possible that we can conduct a longitudinal study. However, there are other issues with these data. For example, the quality measures change from year to year, and some plans have merged during a relatively long time frame.
Although further study is needed, it seems likely that pricing policy is a constraint on quality production, as suggested by the positive correlation between price labor cost ratio and quality of care across pricing regions and the absence of a positive association between nonprice competition and quality as was observed in the hospital industry before 1983. However, we should avoid a causal interpretation, and it is likely that before the state government started its policy, the quality distribution was similar to what we find here, and the policy itself has only been reinforcing this pattern.