Persistent health care disparities are a challenge to efforts to improve quality of care. Disparities demonstrate a continuing failure to address one of the key domains of quality: equity. But, according to emerging evidence, targeted quality measurement and improvement strategies may be able to reduce or even eliminate disparities while improving care for all. With ongoing advances in the science and acceptance of quality measurement and increased transparency through public reporting, it is appropriate to investigate whether major health care providers with large numbers of minority patients can use and adapt existing measurement schemes to detect and reduce disparities in health care. There is evidence that public reporting of quality measures promotes improvement activities by providers. Hence, we sought to investigate whether current public reporting efforts could be used to report data by race or ethnicity and thus spur efforts to reduce disparities.
In particular, we sought to:
- assess the feasibility of using the Hospital Quality Alliance (HQA) framework to collect quality measures by race and ethnicity in major safety net institutions treating large minority populations;
- gauge the usefulness of the HQA measures for measuring disparities in care and supporting hospital quality improvement activities designed to reduce disparities; and
- compare the study hospitals' reported measures by race and ethnicity to the measures now reported in the aggregate by other U.S. hospitals.
We selected six geographically dispersed public hospitals with large African American and/or Hispanic patient populations. These institutions were asked to provide quality data by race and ethnicity using the HQA measures, which are now publicly reported by the Centers for Medicare and Medicaid Services (CMS). We also conducted in-depth interviews with senior clinical and administrative leaders at each site. One hospital was unable to participate, except for an initial interview; the events of Hurricane Katrina precluded its completion of the study.
All of the remaining five study hospitals were able to report data by race or ethnicity. There was little evidence of consistent disparities in care in each institution, although there was some evidence that, for a subset of these hospitals, Hispanic patients fared worse on measures dependent on patient–provider communication (e.g., smoking cessation counseling). On most measures, these public hospitals actually exceeded national norms. Notably, none had conducted analyses of quality data by race or ethnicity using the HQA measures prior to participation in this project. Nevertheless, when interviewed prior to data collection, most hospital leaders were certain—even in the absence of data—that there were no inequities in their care of patients. For many measures, the sample size was low, despite significant numbers of patients receiving services at the hospitals. We surmised that this occurred because many patients with relevant diagnoses were not included in the measures as a result of various exclusion criteria. Thus, our ability to analyze the data and draw conclusions was limited. In addition, due in part to extremely limited information from one of the five hospitals, the race and ethnicity of many patients were not known. Even when reported, race and ethnicity categories were not uniform across the sites, making comparisons by these factors difficult.
Several themes emerged from the data collection process and interviews. Like most hospitals, the study hospitals depend on outside vendors for the software and other tools needed for collecting and reporting quality data. At three of the five hospitals, this analysis required the commissioning of a protracted, ad hoc data analysis at additional cost to the hospital. Hence, any new quality initiative is likely to consume scarce resources, compete with other demands for information, and produce data that are less than timely. Participants at the hospitals also tended to view the issue of disparities as a function of coverage, socioeconomic status, and, in some cases, language. They were less certain that race or ethnicity were important independent determinants of care (though they had no data analysis to support these hypotheses). Finally, respondents were divided on the question of whether quality data should be publicly reported by race and ethnicity. Some welcomed the opportunity to do so, while others believed such reporting "could be misinterpreted" and lead them to "find problems [they] can't fix." Most of the key clinical and quality improvement leaders did not think about quality improvement initiatives from the perspective of racial and ethnic health disparities. Efforts to address disparities in these institutions centered on improving access to care and were not linked to quality improvement activities.
To encourage hospitals to focus on disparities as part of quality improvement, several developments are necessary. We need to determine whether existing measure sets such as the HQA set can detect disparities. The HQA measures were developed to evaluate the quality of care provided to all Americans across all acute care hospitals in the United States. Thus, they may not be suited to the much narrower task of measuring differences in the care provided to particular subpopulations. The measures capture information on populations that are often too small for meaningful comparison. They include conditions that may or may not be prevalent at many institutions. For instance, the large number of AMI, heart failure, and surgical measures may make these measures less relevant for understanding quality of care for vulnerable populations at hospitals that have relatively small cardiac and surgical service lines (which is often the case at public hospitals). The HQA measures generally focus on a single intervention during a given episode of care. But quality of care for vulnerable populations may be less dependent on whether a given patient received an aspirin after a myocardial infarction, and more dependent on the patient being able to navigate the transition from hospital to home and comply with a complex medication regimen after hospital discharge. Such transitions are especially important for minority patients who are more likely than non-minority patients to experience communication barriers and less likely to have a stable source of primary or specialty care. Measurement of disparities needs to gauge performance over these transitions and multiple care settings.
Hospitals need to be challenged by organizations such as the Joint Commission on Accreditation of Healthcare Organizations, the National Quality Forum, and CMS to think of disparities as problems related to the quality of care, and to believe that accurate collection of patient data on race, ethnicity, and language is worthwhile. Businesses spend billions each year learning about their customers' identities and preferences. It is troubling how little effort hospitals devote to knowing who their patients are.
In addition, disparities reduction efforts will need to be firmly tied to the measurement and quality improvement efforts of the organizations noted above. Finally, as the country moves toward national certification standards for health information systems, there need to be clear standards for the uniform collection and storage of race and ethnicity data.
We offer the following recommendations to link quality improvement efforts with disparities initiatives.
- Identify measures that can detect racial and ethnic health disparities. Health disparities may not manifest themselves as a withheld aspirin, but may instead be visible in whether a patient receives the full range of recommended care while in the hospital and is able to avoid a readmission or emergency department visit after the transition from hospital to community care. The emergence of "bundled" and transition measures that take into account a broader view of care may help, but we do not believe, based on this study and our work in other institutions, that most hospitals are using such measures routinely. More in-depth research is needed to identify a core set of measures that can be used to measure quality of care for vulnerable populations and pinpoint disparities.
- Disparities reduction efforts need to be "hardwired" into quality improvement. It is clear that health disparities and quality improvement are separate issues in the minds of hospital leaders and quality improvement professionals. For meaningful change to occur, administrators and clinicians need to view equity as a domain of quality.
- Wait for further evidence on the determinants of disparities. Some researchers and observers have proposed that racial and ethnic health care disparities do not necessarily result from individual providers delivering lower-quality care to certain patients. Rather, several recent studies suggest that disparities result from minority patients disproportionately seeking care from lower-quality health professionals, who are most likely providing similar quality care to all of their patients. Hence, many observers suggest that quality improvement approaches targeting hospitals that serve large minority populations will address disparities in care. Our work leads us to urge caution. We simply do not know enough yet to dismiss the theory that some disparities are caused by providers treating their patients differently. Our study of five hospitals that serve large minority populations found that these hospitals actually exceed national norms on several performance measures. Quality improvement activities should target hospitals that serve large minority populations and also have demonstrated quality problems or deficiencies. Merely identifying hospitals that serve large minority populations should not serve as a proxy for identifying low-performing institutions.
- Disparities reduction efforts need to take into account patients' socioeconomic status, coverage source, and primary language. According to the hospital leaders we interviewed, factors affecting patients' access to care are much more relevant to health disparities than race and ethnicity. This may be driven in part by their unwillingness to believe that health professionals treat patients differently solely because of their race or ethnicity. Still, it may be important to document differences in recommended care by patients' income, health insurance coverage, and primary language as well as their race and ethnicity.
- The collection of race, ethnicity, and language data should be standardized as part of the standardization of health information technology. In developing standards for electronic health records, the Commission on the Certification of Health Information Technology Standardization must consider collection of race, ethnicity, and language data. It could, for example, mandate that electronic health record systems support collection and storage of information on patients' race, ethnicity, and primary language in order to be certified. Given the current emphasis on accelerating the adoption of health information technology, we must not lose this opportunity to enhance the ability of information systems to provide useful data on measures of health care equity.