Journal of the American College of Cardiology
ACCF/AHA 2009 Performance Measures for Primary Prevention of Cardiovascular Disease in AdultsA 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) Developed in Collaboration With the American Academy of Family Physicians; American Association of Cardiovascular and Pulmonary Rehabilitation; and Preventive Cardiovascular Nurses Association Endorsed by the American College of Preventive Medicine, American College of Sports Medicine, and Society for Women's Health Research
Author + information
- Rita F. Redberg, MD, MSc, FACC, FAHA, Chair, WRITING COMMITTEE MEMBER,
- Emelia J. Benjamin, MD, ScM, FACC, FAHA, WRITING COMMITTEE MEMBER,
- Vera Bittner, MD, MSPH, FACC, FACP, FAHA, WRITING COMMITTEE MEMBER*,
- Lynne T. Braun, PhD, CNP, FAHA, FAAN, WRITING COMMITTEE MEMBER†,
- David C. Goff Jr, MD, PhD, FACP, FAHA, WRITING COMMITTEE MEMBER,
- Stephen Havas, MD, MPH, MS, WRITING COMMITTEE MEMBER,
- Darwin R. Labarthe, MD, MPH, PhD, FAHA, WRITING COMMITTEE MEMBER‡,
- Marian C. Limacher, MD, FACC, FACP, FAHA, FSGC, WRITING COMMITTEE MEMBER,
- Donald M. Lloyd-Jones, MD, ScM, FACC, FAHA, WRITING COMMITTEE MEMBER,
- Samia Mora, MD, MHS, FACC, WRITING COMMITTEE MEMBER,
- Thomas A. Pearson, MD, MPH, PhD, FACC, WRITING COMMITTEE MEMBER,
- Martha J. Radford, MD, FACC, FAHA, WRITING COMMITTEE MEMBER§,
- Gerald W. Smetana, MD, FACP, WRITING COMMITTEE MEMBER∥,
- John A. Spertus, MD, MPH, FACC, WRITING COMMITTEE MEMBER and
- Erica W. Swegler, MD, FAAFP, WRITING COMMITTEE MEMBER¶
ACCF/AHA Task Force on Performance Measures
Frederick A. Masoudi, MD, MSPH, FACC, Chair; Robert O. Bonow, MD, MACC, FAHA#; Elizabeth DeLong, PhD; David C. Goff, Jr, MD, PhD, FACP, FAHA; Kathleen Grady, PhD, RN, FAHA, FAAN; Lee A. Green, MD, MPH; Kathy J. Jenkins, MD, MPH, FACC; Ann R. Loth, RN, MS, CNS; Eric D. Peterson, MD, MPH, FACC, FAHA; Martha J. Radford, MD, FACC, FAHA; John S. Rumsfeld, MD, PhD, FACC, FAHA; David M. Shahian, MD, FACC
Table of Contents
Preamble......1365
1. Introduction......1366
1.1 Scope of the Problem......1368
1.2 Structure and Membership of the Writing Committee......1368
1.3 Disclosure of Relationships With Industry......1368
1.4 Review and Endorsement......1368
2. Methodology......1368
2.1 Target Population and Care Period......1368
2.2 Dimensions of Care......1369
2.3 Literature Review......1369
2.4 Definition of Potential Measures......1370
2.5 Selection of Measures for Inclusion in the Performance Measure Set......1370
3. Primary Prevention of CVD Performance Measures......1371
3.1 Definition of Primary Prevention......1371
3.2 Brief Summary of the Measurement Set......1371
3.3 Data Collection......1371
3.4 Exclusion Criteria and Challenges to Implementation......1372
4. Discussion......1372
4.1 Sex......1372
4.2 Frequency of Screening......1372
4.3 Risk Screening......1372
4.4 Lifestyle Counseling......1373
4.5 Weight Management......1373
4.6 Hypertension......1373
4.7 Lipid Screening and Control......1374
4.8 Global Risk Estimation......1374
4.9 Stroke Risk Assessment......1375
4.10 Aspirin Use......1375
4.11 Diabetes Mellitus......1375
4.12 Dietary Supplementation......1375
5. Conclusions......1375
Appendix A. Author Relationships With Industry and Other Entities—ACCF/AHA 2009 Performance Measures for Primary Prevention of Cardiovascular Disease in Adults......1377
Appendix B. Peer Reviewer Relationships With Industry and Other Entities— ACCF/AHA 2009 Performance Measures for Primary Prevention of Cardiovascular Disease in Adults......1378
Appendix C. Sample Performance Measure Survey Form and Exclusion Criteria Definitions......1379
Appendix D. ACCF/AHA 2009 Primary Prevention of Cardiovascular Disease Performance Measurement Set Specifications......1381
Appendix E. Sample Prospective Data Collection Flow Sheet......1398
Appendix F. Coronary Heart Disease Risk Prediction......1400
Appendix G. Measuring Waist Circumference......1402
Appendix H. Body Mass Index Table......1402
References......1403
Preamble
Over the past decade, there has been an increasing awareness that the quality of medical care in the United States is highly variable. In its seminal document dedicated to characterizing deficiencies in delivering effective, timely, safe, equitable, efficient, and patient-centered medical care, the Institute of Medicine described a quality “chasm” (1). Recognition of the magnitude of the gap between the care that is delivered and the care that ought to be provided has stimulated interest in the development of measures of quality of care and the use of such measures for the purposes of quality improvement and accountability.
Consistent with this national focus on healthcare quality, the American College of Cardiology Foundation (ACCF) and the American Heart Association (AHA) have taken a leadership role in developing measures of the quality of care for cardiovascular disease (CVD) in several clinical areas (Table 1).The ACCF/AHA Task Force on Performance Measures was formed in February 2000 and was charged with identifying the clinical topics appropriate for the development of performance measures and assembling writing committees composed of clinical and methodological experts. When appropriate, these committees have included representation from other organizations involved in the care of patients with the condition of focus. The committees are informed about the methodology of performance measure development and are instructed to construct measures for use both prospectively and retrospectively, rely on easily documented clinical criteria, and, where appropriate, incorporate administrative data. The data elements required for the performance measures are linked to existing ACCF/AHA clinical data standards to encourage uniform measurements of cardiovascular care. The writing committees are also instructed to evaluate the extent to which existing nationally recognized performance measures conform to the attributes of performance measures described by the ACCF/AHA and to strive to create measures aligned with acceptable existing measures when this is feasible.
ACCF/AHA Performance Measurement Sets
The initial measure sets published by the ACCF/AHA focused primarily on processes of medical care or actions taken by healthcare providers, such as the prescription of a medication for a condition. These process measures are founded on the strongest recommendations contained in the ACCF/AHA clinical practice guidelines, delineating actions taken by clinicians in the care of patients, such as the prescription of a particular drug for a specific condition. Specifically, the writing committees consider as candidates for measures those processes of care that are recommended by the guidelines either as Class I, which identifies procedures/treatments that should be administered, or Class III, which identifies procedures/treatments that should not be administered (Table 2).Class II recommendations are not considered as candidates for performance measures. The methodology guiding the translation of guideline recommendations into process measures has been explicitly delineated by the ACCF/AHA, providing guidance to the writing committees (8).
Applying Classification of Recommendations and Level of Evidence
Although they possess several strengths, processes of care are limited as the sole measures of quality. Thus, current ACCF/AHA Performance Measures Writing Committees are instructed to consider structures of care, outcomes, and efficiency as complements to process measures. In developing such measures, the committees are guided by methodology established by the ACC/AHA (9). Although implementation of measures of outcomes and efficiency is currently not as well established as that of process measures, it is expected that such measures will become more pervasive over time.
Although the focus of the performance measures writing committees is on measures intended for quality improvement efforts, other organizations may use these measures for external review or public reporting of provider performance. Therefore, it is within the scope of the writing committee's task to comment, when appropriate, on the strengths and limitations of such external reporting for a particular CVD state or patient population. Thus, the metrics contained within this document are categorized as either performance measuresor test measures. Performance measures are those metrics that the committee designates as appropriate for use for both quality improvement and external reporting. In contrast, test measures are those that have been deemed appropriate for the purposes of quality improvement but not for external reporting until further validation and testing are performed.
All measures have limitations and pose challenges to implementation that could result in unintended consequences when used for accountability. The implementation of measures for purposes other than quality improvement requires field testing to address issues related but not limited to sample size, frequency of use of an intervention, comparability, and audit requirements. The manner in which these issues is addressed is dependent on several factors, including the method of data collection, performance attribution, baseline performance rates, incentives, and public reporting methods. The ACCF/AHA encourages those interested in implementing these measures for purposes beyond quality improvement to work with the ACCF/AHA to consider these complex issues in pilot implementation projects, to assess limitations and confounding factors, and to guide refinements of the measures to enhance their utility for these additional purposes.
By facilitating measurements of cardiovascular healthcare quality, ACCF/AHA performance measurement sets may serve as vehicles to accelerate appropriate translation of scientific evidence into clinical practice. These documents are intended to provide practitioners and institutions that deliver care with tools to measure the quality of their care and identify opportunities for improvement. It is our hope that application of these performance measures will provide a mechanism through which the quality of medical care can be measured and improved.
Frederick A. Masoudi, MD, MSPH, FACC
Chair, ACCF/AHA Task Force on Performance Measures
1 Introduction
The ACCF/AHA Primary Prevention of Cardiovascular Disease Performance Measures Writing Committee (the Writing Committee) was charged to develop performance measures for the prevention of CVD. These performance measures do not specifically address prevention of stroke, although because risk factors for heart disease and stroke overlap, their use should contribute to the prevention of stroke as well. These measures are intended for adults (18 years of age and older) evaluated in the outpatient setting. The Writing Committee designed most of the measures, including all of the lifestyle measures, to begin at age 18 because we recognize that risk for atherosclerosis accumulates over a lifetime and, although it is never too late to make changes to prevent heart disease, the greatest benefit accrues with early lifestyle changes. The relation between cardiovascular risk factors and the extent and severity of coronary atherosclerosis in the teenage years and earlier is well established on the basis of autopsy studies (10,11). Evidence from long-term follow-up studies demonstrates that a favorable risk factor profile during the working years is associated with a longer, healthier life and reduced medical care expenses after age 65 (12–17). These observations indicate the value of prevention of risk factors in the first place, beginning in childhood and youth, as called for by the AHA's “Guidelines for Primary Prevention of Atherosclerotic Cardiovascular Disease Beginning in Childhood” (18). Although the greatest long-term benefit occurs with changes early in life, changes in adults are also encouraged because they have been demonstrated to reduce risk and prevent heart disease in both middle-aged and older adults. The Writing Committee also acknowledges that the field of primary prevention is rapidly evolving because of the contributions of observational research, registries, and clinical trials. Hence, modifications to these performance measures for primary prevention will be necessary as the field advances.
The Writing Committee designed the performance measures to be applicable to the broadest possible population. A healthy lifestyle is believed to be beneficial across the entire spectrum of age, race, and sex. With respect to age, however, we recognize that there comes a time when the benefits of screening and treatment to avert future events may be of limited value because life expectancy is limited. Moreover, a number of the investigations establishing the benefits of primary prevention have not included elderly patients. In an effort to balance the competing interests of applying primary prevention as broadly as possible and being consistent with other organizations' age criteria, the Writing Committee recommends the use of the proposed measures for patients older than 18 years of age both for accountability and for public reporting. Certain measures have an upper age limit of 80 years because of a paucity of evidence to support the measure in an older age group. In addition, there may be measurement circumstances in which a narrower target age range is appropriate, and those who implement measures may choose to specify an age range that is less broad.
Certain measures, such as blood pressure control, may not be achievable in all patients. Good blood pressure control is a challenge for providers in selected patient subsets, including those with multiple comorbidities and some older patients with isolated systolic hypertension. In addition, patient adherence to medical regimens varies for many reasons. The Writing Committee recognizes that providers may care for patients with complex medical and socioeconomic conditions for whom attainment of target levels for risk factors is difficult. Thus, target levels for attainment of performance measure goals will vary by patient population and by practice setting; for internal quality improvement initiatives, they are set by the providers.
1.1 Scope of the Problem
For more than a century, CVD has been the number 1 killer in the United States for all but 1 year (1918, in which there was an influenza pandemic). CVD is the underlying cause of 36.3% of all deaths, or 1 of every 2.8 deaths, in the United States, according to data from 2004. In 2008, an estimated 770 000 Americans suffered a first coronary attack (this includes myocardial infarction and unstable angina). Another 175 000 had a silent, or unrecognized, myocardial infarction. The total cost of CVD and stroke in the United States for 2007 is estimated at $448.5 billion (19).
Given the magnitude of the problem and the financial burden of CVD, improvements in the quality of primary prevention of cardiovascular disease will lead to substantial improvement in healthcare outcomes. Despite advances and wide publication and dissemination of prevention guidelines in the cardiovascular literature, the inconsistent application of best practices does a disservice to patients and leaves many opportunities for improvement in care and systems. Accountability at the practice level is 1 step toward more consistent application of best practice guidelines and improved clinical outcomes. The size of the performance measure set may place a burden on the practitioner but reflects the complexity of CVD prevention due to its multifactorial pathogenesis. Many practitioners are assuming this burden to ensure the quality of their practice (20,21). In addition, external groups are engaged in quality performance measurement and reporting. Where logical, the Writing Committee has attempted to distinguish between measures that are appropriate for accountability or public reporting and those that should be used only for internal quality improvement.
1.2 Structure and Membership of the Writing Committee
The members of the Writing Committee included senior clinicians (physicians and an advanced practice nurse) and specialists in internal and family medicine, cardiology, preventive medicine, and epidemiology. The Writing Committee also included representatives from the American Academy of Family Physicians; American Association of Cardiovascular and Pulmonary Rehabilitation; American College of Physicians; Preventive Cardiovascular Nurses Association; and Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Division for Heart Disease and Stroke Prevention.
1.3 Disclosure of Relationships With Industry
The work of the Writing Committee was supported exclusively by the ACCF and AHA. Committee members volunteered their time, and there was no commercial support for the development of these performance measures. Meetings of the Writing Committee were confidential and attended only by Writing Committee members and staff. Writing Committee members were required to disclose in writing all financial relationships with industry relevant to this topic according to standard ACCF and AHA reporting policies, and they verbally acknowledged these relationships to the other members (Appendix A).
1.4 Review and Endorsement
Between January 22 and February 22, 2008, the performance measures document underwent a 30-day public comment period, during which ACCF and AHA members and other health professionals had an opportunity to review and comment on the text in advance of its final approval and publication. The official peer and content review of the document was conducted simultaneously with the 30-day public comment period, with 2 peer reviewers nominated by the ACCF and 2 nominated by the AHA. We sought additional comments from clinical content experts and performance measurement experts. See Appendix Bfor relationships with industry and other entities of the peer reviewers.
The ACCF/AHA 2009 Clinical Performance Measures for Primary Prevention of Cardiovascular Disease in Adults was adopted by the respective boards of directors of the ACCF and AHA in June 2009. These measures will be reviewed for currency once annually and updated as needed. They should be considered valid until either updated or rescinded by the ACCF/AHA Task Force on Performance Measures.
2 Methodology
The development of performance systems involves identification of a set of measures that target a specific patient population observed over a particular time period. To achieve this goal, the ACCF/AHA Task Force on Performance Measures has outlined 5 mandatory sequential steps. Sections 2.1 through 2.5outline how the Writing Committee addressed these elements.
2.1 Target Population and Care Period
The target population consists of patients 18 years of age or older. We developed exclusion criteria and upper age limits for certain measures to further specify the target population. These performance measures are intended for primary prevention in the adult population and do not address prevention specific to children and adolescents. More information on primary prevention for children and adolescents can be found in the AHA “Guidelines for Primary Prevention of Atherosclerotic Cardiovascular Disease Beginning in Childhood” (18).
The Writing Committee recognizes that there are many opportunities and healthcare settings for primary prevention of CVD. Thus, these performance measures are aimed at any physician or healthcare professional who sees adult patients (age 18 years and older) at risk for CVD. For this document, the outpatient care period is defined as the period of care provided in an outpatient setting. An ongoing relationship with the healthcare professional is critical to both the initiation and eventual success of preventive measures. In addition, any single visit may not provide the opportunity to address the full range of preventive care required, and in general, the Writing Committee recommends that evidence of at least 2 encounters over a period of 1 year be established before the physician is expected to have responsibility for primary CVD prevention. However, certain measures, such as smoking cessation, are so important for prevention that the Writing Committee believed they should occur even in 1 acute visit over a 2-year period.
2.2 Dimensions of Care
Given the multiple potential domains of treatment that can be measured, the Writing Committee identified the relevant dimensions of care that should be evaluated. We placed each potential performance measure into the relevant dimension-of-care categories. Performance measures selected for inclusion in the final set and their dimensions of care are summarized in Table 3.
ACCF/AHA Primary Prevention of Cardiovascular Disease Performance Measurement Set: Dimension of Care Measures Matrix
Although the Writing Committee considered a number of additional measures that focus on equally important aspects of care, length and complexity considerations did not allow their inclusion in the present set. Final selection of performance measures was based on 1) the evidence base for a given measure, 2) ease/complexity of measurement, and 3) coverage in other measurement sets. The Writing Committee focused on outcome measures rather than process measures whenever possible. The Writing Committee recognized that for some patients, there are many obstacles to attaining the desired outcome. For example, it is difficult for some patients to attain blood pressures less than 140/90 mm Hg because of medication noncompliance, costs, side effects, or other reasons. To avoid penalizing clinicians who care for such patients, the Writing Committee designed performance measures that give credit for good faith attempts to attain the treatment goal (e.g., documentation of the use of at least 2 antihypertensive medications in patients with blood pressures greater than 140/90 mm Hg), as well for attainment of the desired outcome. Such a strategy fulfills the goals of performance measurement by balancing attainment of targets for blood pressure or lipids with recognition of obstacles despite attention to goals. For internal quality improvement purposes, the Writing Committee believed that the standards could be more rigorous. The final set includes both process measures (risk assessment and risk factor counseling) and intermediate outcome measures (blood pressure, cholesterol values).
2.3 Literature Review
The Writing Committee used the 2002 AHA “Guidelines for Primary Prevention of Cardiovascular Disease and Stroke” as the primary source for deriving these measures (22). In addition, the Writing Committee reviewed other more recent guidelines to consider the most current available evidence. These included the US Preventive Services Task Force's “Guide to Clinical Preventive Services” (23), the European guidelines on CVD prevention in clinical practice (24), the AHA's “Evidence-Based Guidelines for Cardiovascular Disease Prevention in Women: 2007 Update” (25), the Joint British Societies' “Guidelines on Prevention of Cardiovascular Disease in Clinical Practice” (26), the Third Report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) (27), and the seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (28).
2.4 Definition of Potential Measures
Explicit criteria exist for the development of performance measures that accurately reflect quality of care, including defining the numerators and denominators of potential measures and evaluating their applicability, interpretability, and feasibility. To select measures for inclusion in the performance measurement set, the Writing Committee prioritized the recommendations from the 2002 AHA guidelines for primary prevention of CVD and stroke (22).
The AHA primary prevention guidelines (22) were drafted before the AHA's adoption of a formal rating system regarding the strength of the recommendation and the level of evidence. That system, adopted by the AHA and the ACCF, enables guideline writing groups to specify the degree to which the benefit of the care is likely to outweigh any potential risk, as well as the level of evidence supporting that conclusion. In general, ACCF/AHA Class I (benefit >>> risk) and Class III (risk greater than or equal to benefit) indications for therapy identify potential dimensions of care and processes for performance measurement; however, not all performance measures must be based on grade A level of evidence (general consistency of direction and magnitude of effect from multiple [3 to 5] randomized trials or meta-analyses with population risk strata evaluated). In particular, when considering interventions to remove harmful exposures (e.g., smoking cessation counseling), or to restore norms that existed during earlier phases of human evolution (e.g., increased consumption of fruits, vegetables, and whole grains and decreased consumption of animal products), the need to obtain evidence from clinical trials is less obligatory than for recommendations to add a pharmaceutical agent to a patient's regimen. The Writing Committee recognizes that randomized, controlled trials of lifestyle interventions are more difficult to perform than pharmaceutical trials; however, lifestyle behavior change remains the cornerstone of a successful prevention strategy. The recommended performance measures in this document are based on processes of care that are expected to lead to benefit that far outweighs any potential risk based on evidence sufficiently strong to support broad population-wide applicability. For some measures, we needed to make recommendations despite the absence of evidence from randomized, controlled trials that used clinical events and deaths as outcomes.
The Writing Committee recognizes that performance measures imply performance standards, and there are those who may find these implicit standards lower than their own practice standards, particularly with respect to assessment frequency and target intermediate outcomes, such as cholesterol and blood pressure. Physicians using these measures to assess their practice quality are invited to choose more aggressive measure specifications. The measures outlined herein are geared towards the minimum level of acceptable performance rather than optimal care, particularly when used to compare providers or for public reporting.
2.5 Selection of Measures for Inclusion in the Performance Measure Set
From analysis of these recommendations, the Writing Committee identified potential measures relevant to the primary prevention of CVD and then independently evaluated their potential for use as performance measures using 8 exclusion criteria adapted from the “ACCF/AHA Attributes of Performance Measures” (Table 4)and the Sample Performance Measure Survey Form and Exclusion Criteria Definitions (Appendix C). As part of this process, the Writing Committee also evaluated the optimal use of each measure for accountability/public reporting (A/PR) versus internal quality improvement (IQI) only. Member ratings of all the potential measures were collated and discussed by the full Writing Committee to reach consensus about which measures should advance for inclusion in the final measure set and whether any should be designated as IQI measures. Nineteen potential measures were advanced initially for full specification to assess their suitability as performance measures. These were eventually reduced to 13 final measures through an iterative process of repeated surveys within the Writing Committee, additional literature review, and detailed group discussions. The 13 performance measures generally support practices expected to reduce long-term risk of cardiovascular events. However, most patient encounters offer opportunities to maintain low risk among persons not yet exhibiting increased risk. Reinforcement of favorable health behavior patterns is desirable as part of every patient encounter, including those that do not require specific risk-reducing interventions.
Summary of ACCF/AHA Attributes of Performance Measures
The Writing Committee has designated 2 measures (Global Risk Estimation and Aspirin Use) as appropriate for IQI only. In addition, for some measures, separate numerators and/or denominators that may be used in IQI programs have been specified in addition to numerators/denominators that are appropriate for use in A/PR programs. In making these designations, the Writing Committee weighed a number of factors, including the strength of evidence for the intervention in the primary prevention population; the availability (or lack) of evidence in specific subgroups, such as women or elderly patients; the potential for unintended consequences if used for A/PR (e.g., incentives to avoid treating sicker or harder to control patients or to overtreat) and the lack of tested risk models to adjust for variations across provider patient populations (especially for measures of intermediate outcomes, e.g., Blood Pressure Control and Blood Lipid Therapy and Control), which could lead to misleading results if used for A/PR. Although these IQI measures represent valuable tools to aid clinicians in improving quality of care and enhancing outcomes for patients, they are not ready for use in A/PR programs until there is further testing and validation.
3 Primary Prevention of CVD Performance Measures
3.1 Definition of Primary Prevention
For purposes of this document, primary preventionis defined as prevention of the first occurrence of CVD. These measures are therefore appropriate for all patients without clinical CVD, including those with diabetes mellitus. This measure set is intended to include asymptomatic individuals with disease identified only by imaging studies. It does not apply to patients who would be included in the existing ACCF/AHA/Physician Consortium coronary artery disease performance measures (3).
3.2 Brief Summary of the Measurement Set
Table 5summarizes the ACCF/AHA Primary Prevention of Cardiovascular Disease Performance Measurement Set—those measures with the highest level of evidence and support among the Writing Committee members. Appendix Dprovides the detailed specifications for each performance measure, including the numerator, denominator, period of assessment, method of reporting, sources of data, rationale, clinical recommendations, and challenges to implementation.
ACCF/AHA Primary Prevention of Cardiovascular Disease Performance Measurement Set
3.3 Data Collection
These performance measures for primary prevention of CVD are ideally intended for prospective use to enhance the quality improvement process but may also be applied retrospectively. We recommend use of a data collection instrument to aid compliance and measurement (Appendix E). Individual institutions may modify the sample instrument or develop a different tool based on local practice and standards.
The burden of collection of accurate data may be greater for certain performance measures because of the inconsistent and potentially incomplete recording of lifestyle screening and counseling. This reporting could be facilitated by inclusion of specific entry fields for history, physical examination, and nonpharmacological interventions (such as counseling, diet, or physical activity prescriptions) in electronic health records. Otherwise, electronic health records or retrospective medical record reviews will miss much of the lifestyle counseling that occurs during routine clinical practice. These would then require prospective data collection as a relatively burdensome means to collect the lifestyle variables. In addition, the Writing Committee recognized that there are different levels of counseling but chose to allow any mention of counseling for lifestyle changes to satisfy these performance measures, to be consistent with the philosophy that these performance measures represent a minimum expectation for good quality care. Other performance measures related to end points that are usually recorded in an electronic health record include physical measurements (body weight, blood pressure), laboratory values (blood lipids), and prescription pharmaceuticals; these would confer relatively low burdens of data collection. Calculation and recording of global risk scores may be enhanced by an electronic health record, which can be designed to automatically calculate the Framingham Risk Score or other global risk scores with availability of the required risk factor data.
3.4 Exclusion Criteria and Challenges to Implementation
The Writing Committee added exclusion criteria, recognizing that there are justifiable reasons for not meeting the performance measures. These reasons, which may be due to patient, medical, or system factors, should be recorded on the data collection form. Documentation of such factors should be encouraged to provide data for future research and facilitate in-depth quality improvement in situations in which there are apparent outliers with respect to the number of patients with medical or patient-centered reasons for exclusion.
Challenges to implementation of the measures are discussed where applicable. In general, the initial challenge facing any measurement effort is inadequate documentation. Discussion of these challenges is not an argument against any individual measure. Rather, these discussions are cautionary notes that draw attention to areas in which additional research may enhance the value of the measures.
4 Discussion
4.1 Sex
The Writing Committee recommends identical screening and advice for men and women for most cardiovascular risk factors, including lifestyle, diet, physical activity, smoking, and blood pressure. Sex-specific age of onset of cardiac risk follows from the varying epidemiology of heart disease in men and women (22,25,27). For men 35 years of age and older and for women 45 years of age and older, global risk assessment takes into account the sex-specific levels of risk so that interventions are not sex-specific but rather tailored to risk. We have recommended sex-specific assessment of adiposity to target patients with waist circumference of 35 inches or more for women and 40 inches or more for men for additional intervention. For assessment of lipid therapy and control, the risk from a family history of CVD is relegated to male first-degree relatives younger than 55 years of age and female first-degree relatives younger than 65 years of age, whereas the risk associated with low levels of high-density lipoprotein cholesterol is defined as less than 40 mg/dL in men and less than 50 mg/dL in women. We recommend global risk screening for all men 35 years of age or older and for all women 45 years of age or older. Finally, we recommend administration of aspirin as preventive therapy for men with a 10-year coronary heart disease (CHD) risk of 10% or more and for women with 10-year CHD risk of 20% or more, given different thresholds of risk and benefit (25,27).
4.2 Frequency of Screening
In general, a comprehensive assessment of risk factors should be performed at least every 5 years starting at 18 years of age, and a global risk score should be calculated at least every 5 years starting at the age of 35 years for men and 45 years for women. Those with increased cardiovascular risk, for example, those with diabetes, cigarette smokers, or those with obesity, should have their risk factors and cardiovascular risk assessed more frequently.
4.3 Risk Screening
Numerous observational studies have documented the powerful associations of healthy lifestyle choices, such as healthier diet, greater physical activity, avoidance of smoking, and maintaining a lean body mass, with marked reductions in CVD events (15,29,30). Although limited data indicate that assessment (alone) of diet and physical activity improves outcomes, and there are concerns regarding the reliability of patient self-report, assessment and documentation of these factors are important means to help the patient and provider understand the patient's risk for CVD, to begin a dialogue regarding healthy lifestyle choices, and to provide specific counseling regarding risk factor reduction to lower overall risk. Although the addition of longitudinal, multicomponent behavioral interventions increases the effectiveness of clinical recommendations alone regarding healthy diet and physical activity, advice alone has been shown to reduce risk factor levels and overall CHD risk (31,32).
There is no consensus on what constitutes adequate documentation of diet, physical activity, and alcohol use. The Writing Committee believes that physicians and other practitioners should strive to capture the healthy and unhealthy aspects of the patient's habits to provide counseling and observe change over time. Although the Writing Committee did not think that any specific tools should be required for assessment of diet and physical activity, the Committee noted the existence of numerous validated measures that could assist patients and providers in assessing the quality and quantity of diet and physical activity. The numerous dietary instruments range from the extensive Diet History Questionnaire (available at http://riskfactor.cancer.gov/DHQ/) to a simple nutrition history form that a patient can fill out (33) or a simple question regarding how many servings of fruits and vegetables a patient eats on average every day. Likewise, there are a variety of validated instruments to help measure physical activity frequency and intensity, such as the International Physical Activity Questionnaire (available at http://www.ipaq.ki.se/ipaq.htm). Some of these instruments are extensive and are designed for research purposes, but portions of them may be useful to clinicians, and many can be self-administered and are available in a wide variety of languages.
There was not a clear consensus among the Writing Committee members regarding assessment and counseling on alcohol in CVD risk. Likewise, although premature CVD in a patient's first-degree relative is clearly a risk factor for CVD (34,35), there were concerns regarding the ability of providers to adequately assess and document a family history of CVD given reliance on patient self-report and varying definitions of a positive family history. Therefore, alcohol use and family history were included for use in internal quality improvement only, not for accountability or public reporting. Nonetheless, providers are strongly encouraged to ascertain relevant family history and history of alcohol use as reliably as possible, including verifying diagnoses of premature CVD with review of medical records of first-degree relatives if the patient can obtain them. One widely available tool that can assist patients and providers in ascertaining and updating family history information is the US Surgeon General's Family History Initiative (available at http://www.hhs.gov/familyhistory/). The “My Family Health Portrait” tool on this Web site is intended to make the process of gathering and storing family history information easier and more efficient for both patients and healthcare professionals.
4.4 Lifestyle Counseling
Consuming a heart-healthy diet (lower in animal products and rich in fruits and vegetables, whole grains, low-fat or nonfat dairy products, fish, legumes, poultry, and lean meats; calorie controlled; and moderate in sodium intake), as well as engaging in regular physical activity, lowers an individual's risk for CVD. Therefore, the Writing Committee strongly believes that diet and physical activity counseling is the foundation of primary prevention. Such counseling has the potential to either reduce or prevent the development of risk factors, for example, hypertension, hyperlipidemia, obesity, and diabetes. The Writing Committee recognizes that clinical trial evidence related to morbidity and mortality outcomes for lifestyle counseling provided in medical practice settings is not as robust as the evidence for other medical therapies; however, strong evidence supports the importance of diet and activity in the risk of CVD, and accumulated evidence supports the impact of practice-based counseling on behaviors (36). The Writing Committee believes that a performance measure for lifestyle counseling should be adopted despite the lack of definitive evidence for morbidity and mortality benefits, because such trials are unlikely to be conducted, and efforts to restore biological and evolutionary norms are less likely to introduce harm than are pharmacological interventions. Given that the adoption of lifestyle changes can prevent and treat CVD risk factors, the need for other medical therapies may be reduced or averted entirely. The Writing Committee agreed that unless diet counseling and physical activity counseling are put forward as performance measures, there is no incentive for clinicians to provide such interventions to patients. Yet, the literature provides evidence that patients respond favorably when counseling is provided. In a recent study (37), physicians who gave brief advice on physical activity and educational materials showed that patients increased physical activity by 18 minutes per week more than control patients at 6 months, and a 4% higher proportion of patients achieved the minimum recommended physical activity level. Furthermore, subgroup analyses showed that individuals 50 years of age and older and those who were given an individual physical activity prescription had even greater success, for example, doubling their minutes per week of moderate or vigorous physical activity.
A problem identified by the Writing Committee is that the clinician's cognitive interactions with patients, for example, counseling, are undervalued and therefore are not reimbursed by third-party payers. However, the creation of an incentive by naming these interactions as performance measures will help identify barriers to effective counseling and improve the value placed on these interventions by the reimbursement system.
The Writing Committee acknowledges the challenges associated with mandating diet and physical activity counseling. First, counseling takes time during an already brief clinician office visit. We encourage clinicians to provide a direct message to patients and to use available resources to help deliver lifestyle information, for example, by giving them printed educational materials, referring patients to www.mypyramid.gov, and handing patients an activity prescription (goal equals 30 minutes of brisk walking 5 days per week). Second, as performance measures, diet and physical activity counseling must be documented. We encourage practices to integrate counseling interventions into electronic medical records or paper form so that such documentation can be expedited. One obvious concern is that compliance with a counseling measure does not provide an understanding of the intensity or quality of the counseling.
4.5 Weight Management
Body mass index and waist circumference are the designated measures for assessment of obesity and abdominal obesity, respectively. Body mass index has been linked with many health outcomes and is the measure most commonly reported in treatment trials. However, studies have also demonstrated the independent contribution of abdominal obesity to cardiovascular risk, particularly in blacks (38–40). Therefore, the Writing Committee encourages the assessment of both of these simple measurements, but only 1 is necessary to meet the performance standard. At present, there is no evidence that defining and managing patients on the basis of the concept of metabolic syndrome results in reduced morbidity and mortality; hence, we focused on the individual risk factors and not on the concept of the metabolic syndrome.
4.6 Hypertension
Hypertension is a major risk factor for the development of CVD. The evidence linking untreated hypertension to increased cardiovascular morbidity is undisputed. However, literature surveys continue to report suboptimal population-based management of hypertension. For example, in the 1999–2002 National Health and Nutrition Examination Survey of non-Hispanic whites, 62.9% of patients with hypertension were aware of their diagnosis, 48.6% were receiving treatment, and only 29.8% had their hypertension controlled (41). The Writing Committee elected to develop separate performance measures that evaluate measurement and control.
Published guidelines differ regarding the age at which blood pressure assessment should commence. We elected to use the recommendations of the seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (28), which recommends screening beginning at 18 years of age. We chose 140/90 mm Hg as the threshold for satisfactory blood pressure control because it is the target blood pressure suggested by the seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure for the general hypertensive population. We recognize that target blood pressure should be lower for special high-risk populations (such as patients with diabetes or chronic kidney disease). Our selected target represents the minimum degree of control, or floor, that is acceptable as a performance measure. We do not mean to imply that lower targets are not desirable for special populations.
Controversy remains as to the optimal role of specific classes of antihypertensive medication in the treatment of hypertension. For example, the seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure and the European Society of Hypertension differ with regard to preferred agents for initial monotherapy. This area of inquiry continues to evolve. Recognizing that individual physicians may reasonably choose 1 initial strategy over another and still comply with published guidelines, we have chosen not to mandate the use of particular antihypertensive drug classes to satisfy the blood pressure control performance measure. Rather, we require that blood pressure be below the target or that at least 2 medications have been prescribed. This allows for different pharmacological strategies and also recognizes that blood pressure for a subset of patients will remain uncontrolled despite treatment that includes at least 2 medications. We included the latter criterion because we did not wish to penalize physicians whose practices may include more challenging patients or more patients with refractory hypertension due to case-mix issues. If blood pressure is not controlled despite antihypertensive medication, clinicians should assess possible reasons for poor control (e.g., patient adherence to recommended treatments) before changing the choice or dose of medication. Both of our blood pressure measures will require electronic or paper medical record reviews. With the exception of patients with hypertension who have filled prescriptions for at least 2 antihypertensive medications, claims data will not adequately capture the information necessary to evaluate these performance measures.
4.7 Lipid Screening and Control
The Writing Committee had an extensive discussion about the appropriate age at which lipid screening should be initiated. The Adult Treatment Panel III guidelines recommend lipid screening from age 20 years onward. The US Preventive Services Task Force recommends lipid screening at age 35 years for all men and at age 45 years for women who are at increased risk for CHD and does not make a recommendation for or against screening in younger individuals who are not at increased risk for CHD. Some Writing Committee members advocated the younger age cutoff, noting that atherosclerosis originates in youth and progresses in young adults; however, many Writing Committee members advocated older age thresholds for lipid screening because of the lack of an evidence base of randomized, controlled trials in younger cohorts documenting that lipid screening at younger ages results in reduction of cardiovascular events in the long term. The Writing Committee adopted the older age thresholds as the minimum standard for accountability/public reporting, whereas the internal quality improvement standard calls for screening at younger ages.
Decisions about lipid-lowering therapy should be based on an individual's risk for CVD rather than solely on sex or age (27,42). The Writing Committee acknowledges that evidence is limited for women and the elderly (43,44). Such risk assessment requires comprehensive ascertainment and documentation of lipid and nonlipid risk factors. Data on individual risk factors are best synthesized by validated risk scores, and global risk estimation is thus recommended by current lipid-lowering guidelines and included in the present document as an internal quality improvement measure (see Section 4.9). Given the lack of consensus regarding which global risk assessment instrument most correctly captures risk and which time frame for risk estimation is most appropriate, and because there are no studies to date that directly demonstrate superior patient outcomes with formal risk scoring as opposed to comprehensive risk factor assessment alone, the Writing Committee has chosen not to designate global risk estimation as a performance measure. Ascertainment of the data elements for global risk estimation, however, meets performance measure criteria.
Considerations similar to those discussed in detail in the section on hypertension treatment and control apply to the treatment and control of dyslipidemia. Statins are the mainstay of pharmacological lipid-lowering therapy, but the Writing Committee has chosen not to prescribe certain lipid-lowering regimens in favor of others given the variability of lipoprotein phenotypes and the heterogeneity of patients' tolerance to various medication classes and agents within classes.
4.8 Global Risk Estimation
The current framework for assessment of risk for CHD and the selection of potential patients for drug therapy includes assessment of absolute risk for CHD in the next 10 years based on multivariable equations that include a number of established risk factors. These risk equations have face validity and provide excellent discrimination of high-risk (20% or greater), intermediate-risk (10% to 20%), and low-risk (less than 10%) individuals. Their calibration may vary depending on differences in event rates and prevalence of risk factors between the population from which the equations were derived and the population in which they are being utilized. Limited data indicate that the use of these risk equations improves outcomes (45,46); this area of research requires further study. Furthermore, most risk equations focus on 10-year risk, whereas it is increasingly recognized that risk for CHD occurs over one's lifespan, and low 10-year predicted risk in a young person may not indicate low lifetime risk (14). Indeed, 10-year risk estimates are universally low, even in the face of significant risk factor burden (47–49), in younger men (younger than 35 years of age) and women (younger than 45 years of age). Therefore, several panels (25,27) have recommended consideration of long-term or lifetime risk estimates for younger individuals to help emphasize the importance of early positive lifestyle changes. Lifetime risks may be estimated for individuals 50 years of age or younger with a published simple risk factor stratification scheme (14).
A number of 10-year risk scores are currently available. Of these, the 1998 Framingham Risk Score (50) has been assessed and validated in the broadest range of populations and has the most years of follow-up. A modification of this risk score was adopted by the third Adult Treatment Panel of the National Cholesterol Education Program for risk assessment for the end point of nonfatal myocardial infarction or coronary death. A newer version of Framingham 10-year risk scores was published recently (51) with the added utility of prediction of 10-year global CVD risk and specific CVD end points (CHD, stroke, heart failure, and peripheral arterial disease). Although the Writing Committee recommends that documentation of the Framingham 10-year risk estimate be the preferred method of assessing compliance with this measure (Appendix F), the use of another risk score is also acceptable if it is relevant to the patient/population. The Adult Treatment Panel III global risk estimates are for hard CHD (fatal CHD or nonfatal myocardial infarction, but excluding angina pectoris), whereas the 1998 Framingham scores that are provided in Appendix Fare for total CHD (including angina pectoris), although hard CHD risks can also be derived. The European SCORE (Systematic Coronary Risk Evaluation) (52) estimates fatal CVD risk, whereas the Reynolds Risk Score (53) estimates women's risk for CVD including stroke and revascularization.
4.9 Stroke Risk Assessment
Global risk assessment tools such as the Framingham Stroke Profile for first stroke are also available. Although they have not been validated as widely as the Framingham CHD risk assessment tool, external validity has been demonstrated in European cohorts (54–59). On the other hand, the global risk assessment for CHD is widely used and has been adopted in the Adult Treatment Panel III guideline. Although the calculations differ, patients at higher CHD risk will also be at higher risk for stroke. At this time, we recommend use of a global risk assessment tool for CHD or CVD. Consideration may also be given to use of the recent Framingham global CVD risk scores and the stroke-specific score (51,54,60,61).
4.10 Aspirin Use
Although the benefits of aspirin therapy to prevent myocardial infarction, stroke, and vascular disease death in men and women with established CVD are well known, the use of aspirin in primary prevention is less clear. Among men and women without CVD, there has been little or no benefit for aspirin in reducing CVD death or all-cause death (62). In a recent meta-analysis of primary prevention studies, there was a significant 12% relative risk reduction in CVD events with aspirin, which was similar across CHD risk categories (62). Another meta-analysis of individuals without established disease reported a sex-specific reduction in cardiovascular events (63). Aspirin reduced the risk of myocardial infarction in men and the risk of stroke in women; however, aspirin significantly increased the risk of bleeding in both men and women (64). Aspirin did not reduce the risk of cardiovascular disease in Japanese patients with diabetes in the primary prevention setting unless they were 65 years of age or older (65). The use of aspirin for prevention of CVD in patients with diabetes mellitus or peripheral arterial disease remains unclear (63,65). Thus, in patients without cardiovascular disease, the benefit-risk ratio for aspirin should be carefully weighed since these patients are at lower baseline CVD than patients with known atherosclerotic disease and aspirin increases the risk of bleeding (gastrointestinal bleeding and hemorrhagic stroke). The updated US Preventive Services Task Force statement provides an algorithm that clinicians may sue to assess the potential benefits and risks of aspirin therapy (23).
The Writing Committee discussed using an age cut point however, because the clinical trial data that examined the use of aspirin for primary prevention according to age cut points were based on subgroup analysis, with fewer events occurring in younger individuals, rather than an effect modification by age, the committee preferred to tailor the use of aspirin according to level of CHD risk, consistent with current guideline recommendations. Recent data suggests that those at highest risk (e.g., CHD risk of 20% or greater) may benefit most in terms of absolute risk reduction with aspirin as their absolute risk is high, although they are also at higher risk of bleeding (62).
Available evidence, primarily from secondary prevention studies, shows that low-dose aspirin (75 to 81 mg/d) is adequate to fully inhibit platelet aggregation, although doses of 81 to 325 mg/d are typically prescribed (66). Higher doses of aspirin are associated with an increased risk of bleeding. Guidelines differ in aspirin dose recommendations for primary prevention (81 to 325 mg/d); however, all 3 guidelines (22,23,25) agree that aspirin is recommended for patients at high risk for CHD. Healthcare providers should consider documenting adverse effects, for example, bleeding complications, with respect to aspirin dose.
4.11 Diabetes Mellitus
There is increased risk of developing CHD and stroke in both type 1 and type 2 diabetes mellitus. However, opinions are divided as to whether they should be considered as CHD risk equivalents. We believed the available evidence favored classifying diabetes as a risk factor rather than as a CHD equivalent (67,68).
The literature on the effects of blood glucose control on risk of developing CHD is mixed. There is strong evidence that tight control of glucose in type 1 diabetes mellitus reduces the risk of developing nonfatal myocardial infarction, stroke, and CVD by up to 57% (69). The evidence for the effectiveness of tight glucose control with regard to primary CVD prevention is negative for type 2 diabetes mellitus and may even be associated with increased risk (70–73). We therefore elected not to develop performance measures for diabetes, particularly in light of the fact that the National Diabetes Quality Improvement Alliance has already developed such measures (74). There is very compelling evidence in studies of patients with type 2 diabetes mellitus that tight control of blood pressure and of blood cholesterol significantly reduces the risk of developing CHD.
4.12 Dietary Supplementation
Because of the lack of an established evidence base supporting a primary prevention benefit for antioxidant vitamins, folic acid, coenzyme Q, fish oil capsules, and so on, these were not included in these performance measures.
5 Conclusions
We believe that these measures will provide a useful tool for the shared goal of improving care in the critical arena of primary prevention of CVD. Cardiac risk factor reduction has the added benefit of promoting overall good health, in addition to cardiovascular health. Current federal mandates have made prevention a priority area in health care, recognizing the pivotal role of prevention in good health. We hope that these ACCF/AHA metrics and discussion will help the nation achieve our goal of improving health and health care for all Americans.
Staff
American College of Cardiology Foundation
John C. Lewin, MD, Chief Executive Officer
Charlene May, Senior Director, Science and Clinical Policy
Melanie Shahriary, RN, BSN, Associate Director, Performance Measures and Data Standards
Kay Conley, RN, MSN, BC, Senior Specialist, Performance Measures
Erin A. Barrett, Senior Specialist, Science and Clinical Policy
American Heart Association
Nancy Brown, Chief Executive Officer
Rose Marie Robertson, MD, FAHA, FACC, FESC, Chief Science Officer
Gayle R. Whitman, PhD, RN, FAHA, FAAN, Senior Vice President, Office of Science Operations
Kathryn A. Taubert, PhD, FAHA, Senior Scientist
Appendix A
| Name | Research Grant | Speakers' Bureau/Honoraria/ Expert Witness | Stock Ownership/ Equity Interests | Consultant/ Advisory Board/ Steering Committee | Institutional, Organizational or Other Financial Benefit |
|---|---|---|---|---|---|
| Dr Rita F. Redberg | None | None | None | None | None |
| Dr Emelia J. Benjamin | None | None | None | None | None |
| Dr Vera Bittner | • Atherogenics* | None | None | • CV Therapeutics | None |
| • CV Therapeutics* | • Novartis | ||||
| • Merck* | • Pfizer | ||||
| • NIH/Abbott joint effort* | • Reliant Pharmaceuticals | ||||
| • Pfizer* | |||||
| • Roche* | |||||
| Dr Lynne T. Braun | None | • AstraZeneca | None | None | None |
| • diaDexus | |||||
| Dr David C. Goff, Jr | • Merck* | • Scientific Evidence, Inc* | None | None | • Pfizer |
| • St Jude Medical | |||||
| Dr Stephen Havas | None | None | None | None | None |
| Dr Darwin R. Labarthe | None | None | None | None | None |
| Dr Marian C. Limacher | • Orexigen Therapeutics* | None | None | None | None |
| Dr Donald M. Lloyd-Jones | None | • Abbott | None | None | None |
| • Merck | |||||
| • Pfizer | |||||
| Dr Samia Mora | • AstraZeneca* | • Pfizer | None | None | None |
| • Merck* | |||||
| Dr Thomas A. Pearson | • Sanofi-aventis | • Bayer* | None | None | None |
| • Johnson & Johnson/Merck | |||||
| • Kos Pharmaceuticals | |||||
| • Merck/Schering-Plough | |||||
| • Pfizer | |||||
| • Sanofi-aventis | |||||
| Dr Martha J. Radford | None | None | None | None | None |
| Dr Gerald W. Smetana | None | None | • SafeMed | • Harvard Medical International/Novartis | None |
| • Pharma Schweiz CME course director | |||||
| Dr John A. Spertus | • Amgen* | None | • CV Outcomes, Inc | None | None |
| • BMS/Sanofi- aventis Partnership* | • Health Outcomes Sciences, LLC | ||||
| • KCCQ (copyright)* | |||||
| • Lilly* | • Outcomes Instruments, LLC* | ||||
| • PAQ (copyright)* | |||||
| • PRISM Technology | |||||
| • SAQ (copyright)* | |||||
| Dr Erica W. Swegler | None | • Abbott | None | None | None |
CME indicates continuing medical education; KCCQ, Kansas City Cardiomyopathy Questionnaire; NIH, National Institutes of Health; PAQ, personal assessment questionnaire; and SAQ, Seattle Angina Questionnaire.
This table represents the relationships of committee members with industry and other entities that were reported by the authors as relevant to this topic during the document development process. It does not necessarily reflect relationships with industry at the time of publication. A person is deemed to have a significant interest in a business if the interest represents ownership of 5% or more of the voting stock or share of the business entity, or ownership of $10 000 or more of the fair market value of the business entity; or if funds received by the person from the business entity exceed 5% of the person's gross income for the previous year. A relationship is considered to be modest if it is less than significant under the preceding definition. Relationships in this table are modest unless otherwise noted.
↵* Significant (greater than $10 000) relationship.
Author Relationships With Industry and Other Entities—ACCF/AHA 2009 Performance Measures for Primary Prevention of Cardiovascular Disease in Adults
Appendix C
Appendix D
Appendix E
Appendix F
CHD score sheet for men using total cholesterol or LDL-C categories. Uses age, total cholesterol (or LDL-C), HDL-C, blood pressure, diabetes, and smoking. Estimates risk for CHD over a period of 10 years based on Framingham experience in men 30 to 74 years of age at baseline. Average risk estimates are based on typical Framingham subjects, and estimates of idealized risk are based on optimal blood pressure, total cholesterol 160 to 199 mg/dL (or LDL-C 100 to 129 mg/dL), HDL-C of 45 mg/dL in men, no diabetes, and no smoking. Use of the LDL-C categories is appropriate when fasting LDL-C measurements are available. Risk estimates were derived from the experience of the Framingham Heart Study, a predominantly white population in Massachusetts.
CHD indicates cardiovascular heart diease; chol, cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; and Pts, patients.
Adapted from Wilson et al (50), with permission from Lippincott Williams & Wilkins. Copyright 1998, American Heart Association.
*Hard CHD events exclude angina pectoris.
**Low risk was calculated for a person the same age, optimal blood pressure, LDL-C 100–129 mg/dL or cholesterol 160–199 mg/dL. HDL-C 45 mg/dL for men or 55 mg/dL for women, nonsmoker, no diabetes.
Appendix G
Appendix H
Footnotes
↵* American Association of Cardiovascular and Pulmonary Rehabilitation Representative.
↵† Preventive Cardiovascular Nurses Association Representative.
↵‡ Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion Division for Heart Disease and Stroke Prevention. The findings and conclusions in this report are those of the author(s) and do not necessarily represent the official positions of the Centers for Disease Control and Prevention.
↵§ ACCF/AHA Task Force on Performance Measures Liaison.
↵∥ American College of Physicians Representative.
↵¶ American Academy of Family Physicians Representative.
↵# Former Task Force Chair during this writing effort.
This document was approved by the American College of Cardiology Foundation Board of Trustees in June 2009 and by the American Heart Association Science Advisory and Coordinating Committee in June 2009.
The American College of Cardiology Foundation requests that this document be cited as follows: Redberg RF, Benjamin EJ, Bittner V, Braun LT, Goff DC Jr., Havas S, Labarthe DR, Limacher MC, Lloyd-Jones DM, Mora S, Pearson TA, Radford MJ, Smetana GW, Spertus JA, Swegler EW. 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). J Am Coll Cardiol 2009;54:1364–405.
This article has been copublished in the September 29, 2009, issue of Circulation.
Copies: This document is available on the World Wide Web sites of the American College of Cardiology (www.acc.org) and the American Heart Association (my.americanheart.org). For copies of this document, please contact Elsevier Inc. Reprint Department, fax 212-633-3820, e-mail reprints{at}elsevier.com.
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