Creating a Culture of Quality: The Remarkable Transformation of the Department of Veterans Affairs Health Care System

For decades, fairly or unfairly, the Department of Veterans Affairs (VA) health care system had a suboptimal image in the quality of care it provided and in the evaluation of that care. About 10 years ago, the VA leadership began a major national reorganization that has transformed the VA health care system. What was largely an inpatient, subspecialty-based system became a full-service, integrated delivery system committed to a new model of health promotion, disease prevention, and coordination of care. The VA's transformation was 2-part. First, it implemented a sweeping overhaul of service delivery. Second, it created a culture of quality, committed to the systematic, rigorous evaluation of care. Others have documented the first part of the transformation (1, 2). We focus on whether these efforts actually improved care, as carefully studied by Kerr and colleagues in this issue (3), and whether the lessons learned from the VA may apply to care provided to the general U.S. health care population. The culture of quality depended on the successful implementation of several innovations: a uniform data collection system facilitated by nationwide implementation of an electronic medical record system, systematic application of quality standards, and externally monitored local area networks to monitor quality. The VA also committed resources to advancing the science of quality-of-care evaluation. The quality of care at the VA improved (as documented by Kerr and colleagues). The caliber of VA research on quality of care has also improved. Both can be linked to the development of specific programs: the VA Health Services Research and Development (VA HSR&D) program; the VA Quality Enhancement Research Initiative (QUERI); the HSR&D Centers of Excellence, Resource Centers, Research Enhancement Award Program, and Targeted Research Enhancement Program; and the Translating Research into Improved Patient Care initiatives, specifically the Translating Research into Action for Diabetes (TRIAD) study (4, 5). Kerr and colleagues are the first to compare care for chronic disease in the VA to care for similar patients in commercial or Medicare managed care settings. The authors designed the research to anticipate the criticisms that would undermine most comparisons of the VA with commercially insured health care. Protocols for disease identification, sampling procedures and resultant inclusion rates, and performance measures were similar. Comparisons restricted to simliar data sources (that is, electronic medical records) produced equivalent results and addressed the potential confounding of a comparison of quality of care by differences in quality of data recording. Comparison of the men in both delivery systems produced similar results. Kerr and colleagues measured case mix (by race, education, income, diabetes severity, and other comorbid conditions) uniformly across systems and used these measures to adjust for differences other than sex between the VA and commercially insured patient populations. The authors used hierarchical modeling and sensitivity analyses to ensure that the study results were due to differences between the VA and the private sector systems and were not driven by specific sites within those systems. Because of their rigorous attention to methods, Kerr and colleagues convincingly demonstrate that the VA has succeeded in producing diabetes care similar to or possibly better than that of commercially insured, private sector care. Their study highlights 2 broader major contemporary themesone methodologic and one substantivein chronic disease care in the United States. The methodologic approach used by Kerr and colleagues underscores the importance of standardized, equivalent, and uniformly collected measurements in making comparisons across health care systems. Their approach builds on the generative work, discussed later, of the coalitions and collaborative groups that developed a diabetes-specific set of rigorous, empirically sound, patient-level quality-of-care measures and specified how to apply these measures across a health care system. That work began in the early 1990s when several organizations collaborated to construct a set of evidence-based measures to evaluate the quality of diabetes care (6). Participants were the National Institute of Diabetes and Digestive and Kidney Diseases; the American Diabetes Association; the National Committee for Quality Assurance; the Centers for Medicare & Medicaid Services (formerly the Health Care Financing Administration); the American College of Physicians; the American Academy of Family Practice; the American Medical Association; the American Association of Clinical Endocrinologists; the Endocrine Society; Veterans Administration; the Centers for Disease Control and Prevention; the Agency for Healthcare Research and Quality; and the Joint Commission on Accreditation of Healthcare Organizations. The Diabetes Quality Improvement Project (6), now the National Diabetes Quality Improvement Alliance (the Alliance) (7), created consensus-based process and outcome measures for evaluating diabetes care. The Alliance also created detailed data collection specifications for each diabetes quality measure and is continuing to update its work so that diabetes quality measures will reflect state-of-the-art standards of care. These specifications are critical for comparisons such as those made by Kerr and colleagues. Recent methodologic advances in assessing differences between practice settings underscore the importance of adjusting for differences within practice groups (such as clinical sites within the VA) when measuring differences between groups (such as care in the VA vs. commercial health plans). While Kerr and colleagues adjusted for differences between practice sites within the VA, adjustment for differences between practitioners within each site is equally important (8). If most patients are sampled from a single practitioner or a small group of practitioners, then the care provided could be misattributed to the site or system in which care was provided. Researchers must evaluate the potential for confounding of practitioner with the site or system, since hierarchical modeling cannot account for such confounding. Unlike the VA, in which the variation in care among providers is small compared with the variation between VA sites (9), the variation among clinicians in commercially insured care is relatively large. The VA seems to have succeeded in making care relatively homogeneous across providers within sites. No equivalent hierarchical organizational structure exists for solo and small group practice settings. Without this stimulus for homogeneous care, there is substantial variation between providers within sites, as we and others have observed (8). To ensure that efforts to engineer improvements in care aim at the correct target or targets (system vs. provider), we must understand why and by how much care varies across settings and systems in commercially insured care. The substantive theme highlighted by Kerr and colleagues is that major systemwide initiatives can substantially improve both the quality of care and its evaluation. Whether commercially insured care can follow suit is unknown. Integrated or organized health care systems can better implement changes that lead to improved quality, such as those described by the chronic care model (10). These include creating patient registries, employing nurses and other personnel to ensure patient follow-up, implementing training programs to enhance patient participation in care (11-13), using electronic medical record systems, conducting systemwide evaluation and feedback, and working with community organizations to effect behavior change (14). Other organized health care systems have also used similar practice re-engineering to make notable improvements in quality of care (15). The progress made by the VA, other closed health care systems, and the quality assessment community reflects a steady evolution toward optimal management of chronic diseases. In these settings, determined leadership, focused interventions to improve care and programs to advance evaluation science, systematically applied uniform performance standards, and incentives to improve care produced measurable and meaningful benefits for patients. Can the broader, less organized U.S. health care delivery system learn from the experience of these organizations? Extending these mega-system quality improvement programs into the microenvironments of solo and small group practices, where most chronic disease care in the United States occurs, is a more serious challenge. We must identify the appropriate ad-mix of feasible quality interventions that can improve quality in solo or small group practices. We must also find economical, feasible methods to assess and report quality of care in these settings. The Diabetes Physician Recognition Program (8, 16) and the Heart/Stroke Recognition Program (17) may be models for developing these methods. Meeting these challenges will bring us closer to the goal that John Eisenberg so eloquently advocated (18)to translate scientific research into the everyday practice of medicine in ways that improve and support quality care for all patients in every U.S. health care setting.