Information on quality and disparities can promote understanding of where health care needs and quality gaps exist. In the mid-1960s, the National Halothane Study first indicated how data on variation in performance can advance our understanding of health care and provide opportunities for improvement. The results from the Halothane Study, which principally evaluated mortality rates in the use of anesthesia, revealed unexpected variation in surgical outcomes across hospitals. After adjusting for differences in procedure, age, and physical status, differences in death rates between institutions remained “very much larger” than the differences among anesthetics used (Subcommittee on the National Halothane Study of the Committee on Anesthesia, 1966, p. 128). Looking beyond anesthesia, health care variation by both institution and geographic region remains very much an issue in 2010, including how variation in quality affects the cost of health care (Fisher et al., 2009; Skinner et al., 2010; Weinstein and Skinner, 2010). We now understand that “unwarranted variation” occurs and must be identified in order to be addressed in a “logical and manageable fashion” (Wennberg and Wennberg, 2003, p. 614). Once health care organizations have evaluated and identified the factors contributing to undesirable variation, they are better positioned to develop and implement quality improvement interventions to reduce or eliminate it.
The absence of a national health care data infrastructure hinders the potential for national measurement and reporting to actually improve quality (James, 2003). The development of such an infrastructure has been labeled an “awesome task” (Mechanic, 2007, p. 46) that requires national coordination of performance measures, data aggregation, methodology, and technology (Roski, 2009). Yet AHRQ can play a role in defining the content for such a national health care data infrastructure by identifying and fostering measures and data sources, even if the measures and data are not yet national in scope, and by specifying measurement areas with the greatest potential to improve population health as quality and equity gaps are closed.
Data directly related to care processes and outcomes are needed to comprehensively describe the quality and quantity of care provided by individuals and institutions. Accordingly, data illuminating how care is delivered, who is delivering care, and where care is delivered are necessary to identify opportunities for system change. Electronic health records (EHRs), patient-based registries, and all-payer claims data (APCD) offer long-term potential for comprehensive patient data that can be used to measure the quality of care being provided across settings and time. These data sources have the potential to link use of services, intermediate outcomes, and demographics, and may be large enough to address questions about the quality of care provided to specific subpopulations.
The American Recovery and Reinvestment Act of 20092 authorizes and provides resources for the Office of the National Coordinator for Health Information Technology (ONC) within HHS to guide the “development of a nationwide health information technology infrastructure that allows for the electronic use and exchange of information.” Proposed rules on standards to receive Medicare and Medicaid reimbursement incentives for the implementation of EHRs were issued in December 2009 and describe ways in which EHR systems should be used for purposes that include quality improvement and the elimination of disparities in health and health care (CMS, 2010).
In addition, there is potential for data linkages between health information exchanges (HIEs) and APCD databases (Rogers, 2009). An APCD database would ideally contain information on all covered services, regardless of the setting or the location of the provider, and would include eligibility information and medical, pharmacy, and dental claims. APCD databases may be able to provide data by payers and plans, and could provide the sample size necessary to report on populations and measurement areas where statistical power currently limits quality reporting. Ideally, APCD could be used to define episodes of care and to handle issues of risk and severity adjustment without the need for medical records data. In reality, putting together the requisite data and addressing patient confidentiality concerns require significant investment of time and resources. For instance, Maine, New Hampshire, and Vermont, among others, have APCD databases, but these databases do not always capture care for residents who have out-of-state plans and none of these databases have integrated Medicare data to allow long-term follow-up. Kansas’ APCD database, which is called the Kansas Health Insurance Information System (KHIIS), is a repository for data from group insurers, Medicaid, the Children’s Health Insurance Program (CHIP), and the state employee health plan. It does not include Medicare data and faces budgetary, political, and data quality hurdles (Allison,