Primary Prevention of CVD: There Is Much Work Yet To Be Done
Pub Date: Monday, September 21, 2009
Author: Alain G. Bertoni, MD, MPH, FAHA and Gregory L. Burke, MD, MS, FAHA
Redberg RF, Benjamin EJ, Bittner V, et al. ACCF/AHA 2009 performance measures for primary prevention of cardiovascular disease in adults: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Performance Measures (Writing Committee to Develop Performance Measures for Primary Prevention of Cardiovascular Disease). Circulation 2009. Published online before print, September 21, 2009. 10.1161/CIRCULATIONAHA.109.192617
Over the past 40 years remarkable improvements have been observed in the burden from heart disease and stroke. These changes resulted from both improved clinical care and enhanced clinical and population preventive efforts. Despite these improvements, cardiovascular disease (CVD) remains the leading cause of morbidity and mortality in the United States. Recent increases in the prevalence of obesity and diabetes threaten to reverse this downward trend in CVD mortality. Concerted national efforts are urgently needed to improve cardiovascular health. The magnitude of the challenge is demonstrated by an estimate that 78% of U.S. adults are eligible for one or more preventive interventions (e.g., smoking, dyslipidemia, hypertension, inadequate physical activity, unhealthy diet etc.). A comprehensive approach to risk-factor assessment and control is needed. A remarkable 63% of heart attacks and 31% of strokes could be prevented by adherence to appropriate lifestyles and drug therapy. Strategies for smoking cessation, weight control, hypertension and dyslipidemia, and enhancing dietary patterns have been tested. Indeed, these have informed evidence-based guidelines, which address primary prevention of CVD through risk-factor modification and aim to influence care providers. Unfortunately, many at-risk individuals are not screened, risk stratified, counseled, or treated.[4-6] The reasons underlying the lack of action are complex and, undoubtedly, are due to physician, patient, and healthcare-system factors. Given that the knowledge on how to prevent CVD is well established, we must now focus on implementing prevention in clinical practices by assessing the quality of care currently being delivered and by designing, then testing, strategies to optimize the quality of prevention.
The ACCF/AHA 2009 performance measures for primary prevention of cardiovascular disease in adults, by Redberg et al., provides both a blueprint for and the scientific rationale justifying redoubling of our efforts to prevent CVD. The authors thoughtfully reviewed existing practice guidelines and primary prevention recommendations (e.g., JNC7, ATPIII, AHA guidelines, etc.) and proposed 13 performance measures well supported by science (generally Class I or II/ Level A or B). For each performance measure, this document provides specific recommendations on inclusion of patients, the period of assessment, data sources, rationale, underlying clinical recommendations, method of reporting, and challenges to implementation. Not surprisingly, many of the measures focus on clinical assessment and control of CVD risk factors. Perhaps more noteworthy is the inclusion of assessment and counseling regarding health behaviors such as physical activity, healthy diet, and healthy weight. Their inclusion reflect the fact that the underlying health behaviors directly contribute to CVD risk (e.g., diabetes, dyslipidemia, hypertension) and that lifestyle changes can lead to significant improvement in these parameters.[9-11] The comprehensive approach recommended is useful, since many adults simultaneously have two or more risk factors for CVD. An important distinction is made between those measures that may be publicly reported and those measures that would best be used for internal quality assessment and improvement activities. A practical application of this two-pronged approach was how they dealt with the disagreement between different guidelines regarding when to initiate lipid screening. The writing committee adopted the older age thresholds as the minimum standard for accountability/public reporting and the younger age threshold for the internal quality-improvement standard.
There are several novel aspects of either the measures chosen or their definitions. One such feature is to give credit for adequate treatment of patients with hypertension or dyslipidemia who, despite such treatment, have not met therapeutic targets. Clearly the authors appreciate the challenges faced by physicians and patients in achieving ideal control of hypertension or dyslipidemia. Furthermore, such patients are likely deriving benefit from lowering their blood pressure or LDL-cholesterol from higher levels. Finally, giving credit for appropriate treatment, rather than exclusively for control, may reduce unintended consequences of performance measures (such as a reluctance to manage high-risk patients or excluding many patients from the denominator for questionable reasons). Secondly, the inclusion of a performance measure for global risk assessment is noteworthy. The ATPIII guideline explicitly recommends Framingham risk scoring to determine lipid treatment and control levels. It is not clear how often physicians routinely use risk-assessment equations or document global risk, or if doing so is associated with improved quality of care. It is clear, however, that a global risk score can be a target of comprehensive prevention interventions. Finally, as noted by the authors, despite the importance of diet and physical activity, it is difficult to assess this in a standardized fashion in routine clinical practice. Nevertheless, the inclusion of lifestyle assessment as a performance measure may yet spark efforts to develop reliable and brief questionnaires for use in clinical settings.
Physicians are increasingly having their performance (vis-à-vis practice guidelines) assessed, and there is evidence that doing so and reporting the results back to the practice (audit and feedback) can improve quality of care.[15,16] In the United States, efforts to improve performance by assessment of quality via performance measures (such as HEDIS and pay-for-performance) are either already in place or proposed. Some medical societies (e.g. American Board of Internal Medicine) require practice improvement activities to be performed for board certification. However, collecting the data to assess compliance with these recommendations has typically required manual chart review by trained staff, an expensive and time consuming proposition, or assessing quality through imperfect proxies: For example, using only billing and/or laboratory records. There is an increasing adoption of Electronic Health Records (EHR) into most clinical practice settings, which should make data collection more feasible. There is also enthusiasm for using EHRs that provide the capability of incorporating clinical decision support systems (CDSS). Such systems, for example, might assist with identification of at-risk patients or suggest patient-specific management options. A recent primary practice-based intervention designed to improve physician adherence to Dutch national lipid-management guidelines suggested that availability and timing of CDSS may be useful. All practices in this study use an EMR system: Patient-level data was used by the CDSS to determine which patients required cholesterol screening, and which met criteria for lipid-lowering drug treatment. Practices were randomized to receive either the CDSS-generated recommendations automatically when patients were seen (alerting function), or "on-demand" advice (physicians activated the CDSS), or to a control condition with no CDSS. Both CDSS conditions increased screening rates, but only alerts improved appropriate treatment, compared to control.
It is in the context of EHRs, potentially with CDSS, that we believe the ACCF/AHA primary prevention performance measures may best be used. The 13 measures may be seen as a template for a comprehensive approach to quality improvement by individual physicians, group practices, or health insurers. With good data collection in place, creative strategies to improve quality could be used and assessed, including randomized trials. For example, many practices may already have the information available for determination of global risk for each patient. Would an EHR system that automatically calculated and documented global risk lead to improved quality of risk-factor control? Recently National Ambulatory Medical Care Survey data showed that 50% of ambulatory visits did not collect the height and weight data needed to screen for obesity. In addition, among patients with BMI ≥30, 70% were not diagnosed and 63% received no dietary, exercise, or weight-loss counseling. Could using and reporting the weight assessment/weight management performance measures lead to improvement in these dismal statistics? Might widespread improvements in adherence to 13 performance measures lead to decreased CVD? It is not possible to answer these questions until there is widespread adoption of these measures.
Acknowledging the challenges of integrating the 13 proposed performance measures, there are huge implications from inaction. The financial cost from CVD to society was estimated in 2009 to be $475.3 billion. U.S. healthcare costs rose to an estimated 17.6% of GDP in 2009 with CVD representing a large portion of those expenditures. Perhaps more important than the cost implications is the opportunity cost experienced by the continued reduction of many Americans’ quality of life due to CVD. It is clear that to effectively implement these 13 recommendations the practice environment needs to be substantially re-engineered. This important document cannot be allowed to simply "sit on a shelf" as an academic exercise. All of us working in CVD should be called into action to better implement preventive practices into routine clinical care and to work to develop more creative strategies for the implementation of primary preventive strategies into our communities by modifying "accepted" societal norms. More prevention research is needed to develop better methods to implement the principles behind these 13 measures. Most importantly, efforts are needed to reach the large numbers of individuals presently not impacted by current prevention activities. Healthcare reform, in whichever form it ultimately takes, needs to support primary care/prevention. Truly there is much work yet to be done.
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- -- The opinions expressed in this commentary are not necessarily those of the editors or of the American Heart Association --