Has pay-for-performance decreased access for minority patients?

The misalignment of incentives between payers and providers is a common critique of the U.S. health care system (Institute of Medicine [IOM] 2001). Both public quality reporting and pay-for-performance (P4P) represent efforts by payers to align providers behind the objectives of higher quality and, potentially, lower cost care, resulting in higher value (IOM 2006). However, public quality reporting and P4P are subject to their own critiques. In addition to multitasking, the allocation of resources toward a subset of measured activities and away from unmeasured activities (Holmstrom and Milgrom 1991; Eggleston 2005;), patient avoidance is frequently raised as perhaps the most deleterious unintended consequence of public quality reporting and P4P (Werner, Asch, and Polsky 2005; Epstein 2006; Casalino et al. 2007; Chien et al. 2007; Hood 2007;). Patient avoidance, or “cream-skimming,” occurs when providers determine that it is in their interest to avoid treating a patient who is likely to reduce their performance on a publicly reported or financially incentivized quality measure. This behavior has been documented extensively in the public quality reporting literature (Burack et al. 1999; Dranove et al. 2003; Narins et al. 2005; Epstein 2006;). In a survey among surgeons in the New York cardiac report card program, 62 percent of respondents indicated that they did not operate on at least one high-risk coronary artery bypass graft (CABG) patient over the prior year “primarily because of public reporting” (Burack et al. 1999). In a later survey, 83 percent of New York surgeons “agreed or strongly agreed that patients who might benefit from angioplasty may not receive the procedure as a result of public reporting of physician-specific patients' mortality rates” (Narins et al. 2005). Theoretically, the incentives for providers to engage in strategic patient avoidance can be counteracted by risk adjustment, in which case mix severity is held equal across providers through statistical adjustment. However, risk adjustment suffers from a number of potential problems. First, risk adjustment must be based on observable patient characteristics, but providers are likely to have additional information about patients which is not captured by risk adjustment (Dranove et al. 2003). Also, as noted by Dranove et al., risk adjustment, even if “correct in expectation terms but incomplete … may not compensate risk-averse providers sufficiently for the downside of treating sick patients” (Dranove et al. 2003). Supporting this premise, one study of New York surgeons found that “85 percent believed that the risk-adjustment model used in the Percutaneous Coronary Interventions in New York State('s) (sic) 1998–2000 report is not sufficient to avoid punishing physicians who perform higher-risk interventions” (Narins et al. 2005). In the absence of complete risk adjustment, providers may engage in statistical discrimination: the application of perceived group characteristics to individuals. As noted by McGuire et al. (2008), statistical discrimination “appears to be a potent (if more difficult to observe) source of discrimination in health care use” (p. 532). Statistical discrimination may result in provider avoidance of racial and ethnic minority (henceforth “minority”) patients, who may be perceived to have higher unmeasured risk than non-Hispanic white (henceforth “white”) patients, in P4P and public quality reporting programs. Even if unobserved severity is not correlated with race, physicians and hospitals may inaccurately perceive it to be, and thus attempt to avoid patients on that basis. Thus, the combination of two factors, (1) providers' desire to avoid patients on the basis of unmeasured severity and (2) providers' perception that minority patients have greater unmeasured risk, could lead to avoidance of minority patients as a result of the incentives of P4P. The limited empirical evidence on this topic has been conducted in the context of public quality reporting. A study by Werner, Asch, and Polsky (2005) found that disparities in rates of CABG procedures increased for black and Hispanic patients, relative to white patients, after the implementation of the New York CABG public quality reporting program. Because similar increases in disparities were not observed for percutanerous transluminal coronary angioplasty (PTCA) and cardiac catheterization, which were not publicly reported, the study suggests that public quality reporting in New York caused the observed increases in disparities for CABG. Despite concerns raised by several authors (Casalino et al. 2007; Chien et al. 2007; Hood 2007;), there is no empirical evidence on the effect of P4P programs on patient avoidance. Evidence from the United Kingdom's National Health Services P4P program suggests that provider practices that served lower-income patients had lower quality scores (Doran et al. 2006) and that the program has not successfully combated racial and ethnic disparities related to diabetes care (Millett et al. 2007). However, these studies do not examine patient avoidance or other potential unintended consequences of P4P. As noted by (Chin et al. 2007), “Disturbingly, there is essentially no literature evaluating the effectiveness or potential harms of these policies (P4P and other performance incentives) on disparities” (p. 25S). The current investigation addresses this gap in the literature by evaluating whether the CMS and Premier Inc. Hospital Quality Incentive Demonstration (PHQID), a hospital-based P4P and public quality reporting program, caused participating hospitals (1) to avoid treating minority (nonwhite) patients diagnosed with acute myocardial infarction (AMI), heart failure, and pneumonia and (2) to avoid providing CABG to minority patients diagnosed with AMI. The study also examines the mechanisms through which minority patients may have been avoided in the PHQID.