A systematic approach to managing hypertension and the metabolic syndrome in primary care.
Methods: Longitudinal data on blood pressure, low-density lipoprotein cholesterol (LDL-C), hemoglobin A1c (HbA1c), cardiovascular and renal comorbidities, and treatment medications were obtained on all 817 hypertensive patients seen from January 1, 2000 to June 30, 2003.
Results: The hypertensive patients were 72 [+ or -] 11 (SD) years old, and more than 55% of them were high risk based on target organ damage, clinical cardiovascular disease, or diabetes mellitus. Blood pressure was <140/90 mm Hg in 77% of all patients. Among the high-risk patients, mean blood pressure was 126 [+ or -] 14/71 [+ or -] 10 on 2.8 [+ or -] 1.4 antihypertensive medications, with 88% on angiotensin converting enzyme inhibitors or angiotensin receptor blockers, 59% on diuretics, 49% on calcium channel blockers, and 36% on [beta]-blockers. Among dyslipidemic hypertensives, LDL-C was controlled to <130 mg/dL in 84% (510/605) overall and to <100 mg/dL in 70% of the high-risk group (299/427). Among diabetic hypertensives, the mean HbA1c was 6.8%, with 64% (155/242) less than 7%. New patients demonstrated improved blood pressure, LDL-C, and hemoglobin A1c control over time as the management algorithm was applied.
Conclusions: A high prevalence of complicated hypertension was documented. Blood pressure, LDL-C, and HbA1c were controlled to goal in a high proportion of patients. The findings demonstrate that application of an evidence-based management algorithm can facilitate higher rates of cardiovascular risk factor control than are generally reported in primary care practices.
Key Words: cholesterol, diabetes mellitus, evidence-based goals, hypertension, metabolic syndrome
Cardiovascular disease is the leading cause of morbidity and mortality, especially in the Southeast where event rates are shifted 10 to 20 years earlier in life. Within the "Stroke Belt," cardiovascular disease rates are higher in rural than in urban settings. (1) Evidence-based trials, summarized in the recommendations of current consensus documents, indicate that a significant proportion of cardiovascular disease can be prevented or delayed, yet the majority of patients do not have cardiovascular risk factors controlled to goal. (2-5) Another trend complicating efforts to reduce cardiovascular disease is the obesity epidemic, which is fueling an increase in metabolic syndrome risk factors, including hypertension, dyslipidemia, and type 2 diabetes mellitus. (6) Older patients are of particular concern, since the prevalence of metabolic syndrome and cardiovascular disease increase sharply as a function of age. (5,6) Cardiovascular risk factor control is often lowest in those at highest risk, including the elderly, diabetics, and ethnic minorities. (2,3,7) There are medical therapies for each component of the metabolic syndrome that dramatically reduce events and mortality.
Given the preceding information, an evidence-based and scientifically-guided algorithm was developed and implemented by a physician member of the team (WHB). The algorithm was applied in managing hypertensive patients in his rural, Southeast private practice setting. An established system for auditing risk factor treatment and control data in outpatient settings and providing summary reports was used. This system was used to quantify the efficacy of the management algorithm in achieving control of three major modifiable cardiovascular risk factors to levels established by the treatment guidelines. (7-9) The results of the algorithm-driven approach in all hypertensive patients managed in this practice setting from January 1, 2000 to June 30, 2003 are summarized in this report.
Materials and Methods
The protocol was reviewed and approved by the Office of Research Protection at the Medical University of South Carolina as exempt from informed consent requirements in a two-step process. In phase one, demographic and selected clinical information was provided along with a unique number for each patient from the practice site to the data management center at the Medical University of South Carolina. The data provided did not include name, address, social security number, or telephone number. These data were entered into a Microsoft SQL Server 2000 database and queries were written for generating semiautomated descriptive feedback reports on a quarterly basis to the provider. In phase two, data were transferred to an analytical database devoid of the unique identifier to further ensure that no patient could be personally identified.
One primary care general internist (WHB) who is also a certified clinical hypertension specialist, (10) working in a group of 5 primary care providers in Beaufort, SC, focused his practice on the medical treatment and prevention of atherosclerotic arterial disease beginning in 1998. Patients already in the practice were not discharged regardless of diagnosis. All new patients had hypertension, type 2 diabetes, hyperlipidemia, or clinical arterial disease including stroke, transient ischemic attack, angina pectoris, myocardial infarction, abdominal aortic aneurysm, or peripheral arterial disease. New patients, for the purposes of this report, were defined as individuals that were first seen more than 6 months after beginning the data audit and feedback, which started in January 1, 2000. The objective was to minimize all risk factors for arterial disease using an evidence-based and scientifically-guided algorithm described below, that is, a best practices approach.
Algorithm for managing cardiovascular risk factors
The algorithm was developed from evidence-based clinical trials, and from other relevant peer-reviewed publications when data from adequately powered, randomized, controlled clinical trials were not yet available (Table 1). (8,9,11-21) The algorithm was scientifically guided by data indicating that endothelial function is critical in blood pressure (BP) regulation, glucose metabolism, atherosclerosis, and associated clinical vascular complications. (22,23) Pharmacological interventions demonstrated to improve endothelial function and maximize risk factor control were preferred. (16,23,24)
Most patients were managed in quarterly office visits of 15 to 25 minutes each. The physician changed therapy at every visit if any risk factor was not at goal, beginning with the medication at the top of the list for each risk factor (Table 1) and proceeding down the list adding medications as required to achieve values established by the guidelines. (21,25-27)
Patients were often given samples of proprietary medications when a new treatment was initiated. Patients were responsible for obtaining and paying for their own medications, since these agents were not provided as part of a research grant of any special funding. There were no special incentives for patients to participate in this study, since the effort was focused on documenting the efforts of standardizing a best practices approach in usual care on cardiovascular risk factor control.
Patient education materials were prepared on diet, exercise, medications, and insulin titration by the physician and given to patients. This outpatient practice does not employ a certified diabetes educator or any other personnel (eg, a dietician) specifically for patient education. However, selected patients received counseling on diabetes at the local community hospital (Beaufort Memorial Hospital, Beaufort, SC) from an educator certified by the American Diabetes Association.
A data reporting card, described previously, (7) was utilized to track patient data. The data included demographics, medications, other risk factors such as tobacco use, menopausal status for women, family history of premature cardiovascular disease, and comorbidities including congestive heart failure, other cardiovascular disease, and renal disease. Values for blood pressure, hemoglobin A1c (HbA1c), and low-density lipoprotein cholesterol (LDL-C) were also recorded. The definition of each risk factor and comorbidity was based on the Sixth Report of the Joint National Committee on Hypertension (JNC VI). (21) The time required to complete the card was approximately one minute for new patients and 15 to 30 seconds for return visits. There were 15 to 20 data points on each card for new patients, and 4 to 6 for returns. The cards were collected and sent to the Hypertension Initiative office at 1 to 2 week intervals for tabulation and analysis. A quarterly performance report summarizing the data was sent to each provider participating in the data audit and feedback program.
Data management and analysis
The patient information cards, without personal identifiers, were double-entered into a Microsoft SQL Server 2000 database program by different individuals to verify accuracy. A third party reviewed the original data card to resolve any discrepancies. If the discrepancy could not be resolved at this step, the practice site was contacted to resolve the question from the original patient record. To facilitate timely and consistent reports, algorithms (queries) were written to assess mean values for systolic and diastolic blood pressure, LDL-C and HbA1c values in JNC VI Risk Groups A (BP only), B (BP and lipids), and C (BP, lipids, HbA1c). The percentage of patients in each risk group and the percentage of patients with risk factors controlled to levels indicated by the guidelines were calculated. Reports included the frequency of medication use by class in each risk group. Data presented are the mean of values for the most recent visit during the past year adapted from Health Plan Employer Data and Information Set (HEDIS) guidelines. (28)
Data cards were obtained on 817 different hypertensive patients during the study period from January 1, 2000, to June 30, 2002. Descriptive characteristics of these hypertensive patients are provided in Table 2. This was mainly an older group of high risk hypertensive patients, ie, Risk Group C as defined by JNC VI; (21) 27% of patients were 65 to 74 years of age, and 34% were 75 to 84. Women comprised 55% of the patients.
The management algorithm for hypertension, hypercholesterolemia, and diabetes is shown in Table 1. The vast majority of patients were appropriate for medical therapy with this treatment paradigm. The distribution of patients in this private practice setting using the JNC VI risk stratification scheme is depicted in Figure 1. Using the JNC VI risk stratification paradigm, 2.2% of hypertensives were at low risk, ie, premenopausal women with hypertension without other cardiovascular risk factors, target organ damage or clinical cardiovascular disease; 41.1% were at intermediate risk, defined as all men, all postmenopausal women, and premenopausal women with hyperlipidemia, cigarette smoking, or a family history of premature cardiovascular disease; and 56.7% were at high risk, defined by the presence of target organ damage, clinical cardiovascular disease or diabetes mellitus. (21, 29)
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The percentage of patients in each risk group that achieved risk factor control by various cut points is shown in Table 3. The majority of patients achieved a blood pressure level of <140/90 mm Hg. Although the study was done before the release of JNC VII, a substantial proportion of high-risk individuals targeted for a blood pressure goal less than 130/80, ie, diabetics and patients with renal disease, achieved that target. (30) The majority of intermediate and high-risk patients with hypercholesterolemia achieved their target LDL-C values. The majority of diabetic hypertensives achieved target HbA1c values as shown, and a substantial minority (43%) attained target values for blood pressure, LDL-C, and HbA1c.
The change of blood pressure, LDL-cholesterol, and HbA1c for patients that were first identified more than 6 months after the start of this program and followed over the course of their next 3 visits are depicted in Figures 2 and 3. As shown, systolic BP declined an average of 5.3/2.4 mm Hg from 131.7/74.7 to 126.4/72.3, LDL-C declined an average of 13 points from 109 to 96 mg/dL, and HbA1c was reduced from an average of 7.1% to a mean of 6.4%.
The major classes of antihypertensive medications used to treat elevated blood pressure are shown for each Risk Group in Table 4. The mean number of antihypertensive medications per patient in the low, intermediate and high-risk groups is also provided and confirms the importance of combination regimens for achieving blood pressure control, particularly among patients at highest risk. (25) The data on medications used to treat hypertension suggest the management algorithm proposed for blood pressure control in Table 1 was, in fact, applied in the majority of patients, especially those at highest risk based on the presence of target organ damage, clinical cardiovascular disease, and diabetes. Patients with compelling indications for angiotensin-converting enzyme inhibitors and/or angiotensin receptor blockers were receiving one of these agents in the majority of cases.
The study results suggest that systematic application of an evidence-based and scientifically-guided management algorithm for patients with hypertension and other cardiovascular risk factors can be successfully implemented in private practice. This private practice-based group of patients was at very high risk for cardiovascular disease based upon their relatively advanced age (Table 2), and the high proportion of patients with comorbid diabetes, clinical cardiovascular disease, and major target damage, ie, JNC VI Risk Group C (Table 4). (21) In a previous nationally representative sample of hypertensive patients from an earlier National Health and Nutrition Examination Survey (NHANES I), only 19% of hypertensive patients met criteria for Risk Group C. (29) Despite the high prevalence of complicating factors associated with lower rates of cardiovascular risk factor control, (2,3) the majority of patients reached their therapeutic goal for control of blood pressure, LDL-C, and glycosylated hemoglobin (Table 3). (21,25-27)
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While the mean changes in individual risk factors were comparatively modest, the cumulative effect on cardiovascular risk is important. The Framingham Study has demonstrated that relatively small changes in a cluster of individual risk factors translates into much larger changes in absolute event risk. (31) A substantial minority of patients that do not meet evidence-based (guided) goals for blood pressure control are, in fact, close to control. (32) Thus, small reductions in blood pressure can lead to a large increment in hypertension control rates. Moreover, controlling blood pressure to goal, especially systolic blood pressure, emerges as a very effective tool for reducing cardiovascular risk. (33) Of note is the fact that mean risk factor values of those patients initially seen in the practice after the first 6 months of the program were close to the control goals for each of <130 mm Hg for BP, <100 mg/dL for LDL-C, and <7% for HbA1c. The modest improvement in risk factor levels led to mean values for each that met the target control goal (Figs. 2 and 3). Moreover, those who were initially farthest from the treatment goal for each of the major cardiovascular risk factors showed the greatest improvement.
Previous studies indicate that medical treatment outperforms mechanical interventions such as arterial bypass and angioplasty in stable patients with atherosclerotic disease. (34,35) These reports led to the present focus on the medical treatment of arterial disease in an attempt to bring together the medical evidence in a best-practices approach. The basis of the plan was to use treatments for any given risk factor based on evidence of event reduction, favorable effects on other cardiovascular risk factors, beneficial effects on endothelial function, and consensus guidelines. (8-27) For example, in previous studies, angiotensin-converting enzyme inhibitors, (36,37) losartan, (38) metformin, (39) and pravastatin (19) decreased the risk of cardiovascular complications and the rate of diabetes mellitus compared with placebo or other active interventions.
Treating type 2 diabetes with two insulin injections daily often results in a weight gain of approximately 10 pounds in the first year, which negatively affects all components of the metabolic syndrome. Metformin therapy for diabetes produces weight loss and favorably affects endothelial function, lipids, and BP. (20,40,41) Blood pressure control in the highest risk patients (Group C) was accomplished with an average of fewer than 3 antihypertensive medications in contrast to the average of 3 or more in previous clinical trials. (25) This suggests that the multiple beneficial effects of the agents selected for the management algorithm contributed to the efficient control of several risk factors including hypertension.
While an integrated pharmacologic approach is required to achieve control of all risk factors, tracking of results is equally indispensable. Effective audit and feedback assists the primary care practitioner in detecting where the therapeutic approach falls short of the intended target, and guides revision in the approach, thereby improving practice performance. In other words, ongoing feedback is a key component of an effective, continuous quality improvement process.
It is tempting to speculate briefly about the potential beneficial impact if the approach described in this report were broadly applied in primary care settings. The available evidence suggests that reductions in event rates of 50% or greater could be obtained. (14,37,41-46) As a next step in exploring the potential benefit, we plan to quantify event rates in these patients to a demographically and disease-matched group of patients managed by usual medical care.
In summary, an evidence-based and scientifically-guided treatment algorithm was developed for patients with hypertension, with the majority having either type 2 diabetes, dyslipidemia, clinical cardiovascular disease, or target organ damage. The algorithm was applicable to patients in a primary care setting and resulted in risk factor control to consensus guideline goals in the majority for each of the major modifiable cardiovascular risk factors. An audit and feedback tool was used to document the utility of the algorithm and guiding refinements in its application. Since those at highest risk typically derive the greatest benefit from risk factor treatment and control, broader application of this management algorithm and feedback program has the potential to reduce cardiovascular events in the population.
Some cause happiness wherever they go; others, whenever they go. --Oscar Wilde Table 1. Protocol for management of patients with hypertension and other facets of the metabolic syndrome (a,b) Risk Type 2 factor Hypertension Hyperlipidemia diabetes Medication (1) ACEI or ARB Statin Metformin (2) HCTZ Niacin or fibrate HS humulin (3) Amlodipine (4) [beta]-blocker/reserpine (a) ACEI, angiotensin-converting enzyme inhibitor: ARB, angiotensin receptor blockers; HCTZ, hydrochlorothiazide. (b) In the absence of specific contraindications, treatment began with the first agent listed for each risk factor with addition of subsequent agents as required to obtain control to target level. Table 2. Descriptive characteristics of the 817 hypertensive patients (a, b) Characteristic Result Men/Women/Unknown (%) 43.2%/54.6%/2.2% White/Black/Other (b) (%) 83.7%/13.5%/2.8% Age, years 72 [+ or -] 11 Most recent BP, mmHg 127 [+ or -] 14/73 [+ or -] 10 % with hypercholesterolemia 78.3% Most recent LDL-C, mg/dL 98 [+ or -] 32 % with diabetes 33.3% Most recent HbA1c, % 6.8 [+ or -] 1.4 % with cardiovascular disease 36.5% % with heart failure 8.6% N, % with renal disease 2.0% (a) BP, blood pressure; LDL-C, low-density lipoprotein cholesterol; HbA1c, hemoglobin A1c. (b) Numeric values = mean [+ or -] SD (c) Hispanic, other, and missing are merged in the Other category. Table 3. Control rates for hypertension, hypercholesterolemia, and diabetes mellitus BP, mmHg (Mean) N Mean BP All patients 815 127 [+ or -] 14/73 [+ or -] 10 Diabetes mellitus 272 127 [+ or -] 15/72 [+ or -] 10 Renal disease 16 130 [+ or -] 21/71 [+ or -] 13 LDL-cholesterol, mg/dL N Mean LDL "Intermediate" risk 246 107 [+ or -] 30 "High" risk 427 90 [+ or -] 31 HbA1c, % N Mean HbA1c All diabetics 242 6.8 [+ or -] 1.4 BP, mmHg (Mean) <150/95 <140/90 <130/80 All patients 93% 77% 41% Diabetes mellitus 93% 79% 44% Renal disease 81% 69% 50% LDL-cholesterol, mg/dL <160 <130 <100 "Intermediate" risk 97% 79% 41% "High" risk 97% 90% 70% HbA1c, % <8% <7% <6.5% All diabetics 84% 64% 47% Table 4. Antihypertensive medications used in each of the JNC Risk Groups (a) A (low) B (medium) Risk Group No. 18 336 Medication ACE inhibitor 39% 46% A[T.sub.1] antagonist (ARB) 11% 17% [beta]-receptor blocker 6% 23% Calcium antagonist (d) 22% 26% Calcium antagonist (nd) 0% 7% Diuretic 50% 41% BP medications, N/patient 1.3 [+ or -] 0.5 2.1 [+ or -] 1.1 C (high) Diabetes (b) Risk Group No. 463 272 Medication ACE inhibitor 69% 70% A[T.sub.1] antagonist (ARB) 19% 18% [beta]-receptor blocker 36% 32% Calcium antagonist (d) 35% 35% Calcium antagonist (nd) 14% 14% Diuretic 59% 64% BP medications, N/patient 2.8 [+ or -] 1.4 2.7 [+ or -] 1.3 (a) d, dihidropyridine; nd, nondihidropyridine. (b) Diabetic hypertensives represent a subset of the larger group of high risk (Group C) patients.
The authors thank Kim Edwards and Donna Jordan for administrative assistance and Adrian Nida for support in database management.
Accepted March 11, 2004.
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RELATED ARTICLE: Key Points
* The prevalence of the metabolic syndrome, which includes abdominal obesity, hypertension, diabetes mellitus, and dyslipidemia, is 10-fold higher in obese than lean individuals.
* The metabolic syndrome is associated with an approximate tripling of coronary heart disease risk.
* Treatment and control of multiple risk factors significantly reduced coronary heart disease, but multiple cardiovascular risk factors are often not controlled, despite the availability of effective therapy.
* Application of a standardized, evidence-based management algorithm can lead to much higher than usual control rates for multiple cardiovascular risk factors.
William H. Bestermann, MD, Daniel T. Lackland, DRPH, Jessica E. Riehle, and Brent M. Egan, MD
From the Low Country Medical Group, Beaufort, SC, and the Departments of Biometry and Epidemiology, Medicine, and Pharmacology, Medical University of South Carolina, Charleston, SC.
This data audit and reporting program was supported in part by the South Carolina Department of Health and Environmental Control, the Agency for Healthcare Research and Quality P01 HS1087. National Institute of Health HL04290, the Duke Foundation, and an unrestricted grant from Astra-Zeneca Pharmaceuticals, Inc.
Reprint requests to William H. Bestermann, MD, 260 Distant Island Drive, Beaufort, SC 29902. Email: firstname.lastname@example.org