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The American Journal of Managed Care October 2009
Bending the Curve: Effective Steps to Address Long-Term Healthcare Spending Growth
Joseph Antos, PhD; John Bertko; Michael Chernew, PhD; David Cutler, PhD; Dana Goldman, PhD; Mark McClellan, MD, PhD; Elizabeth McGlynn, PhD; Mark Pauly, PhD; Leonard Schaeffer; and Stephen Shortell, PhD
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Impact of Compliance With Proton Pump Inhibitors on NSAID Treatment
Mei Sheng Duh, MPH, ScD; Antoine Gosselin, MA; Roger Luo, PhD; Herve Lohoues, PhD; Barbara E. Lewis, PhD; and Joseph A. Crawley, MS
Delivering Vaccines: A Case Study of the Distribution System of Vaccines for Children
Jason T. Shafrin, PhD; and John M. Fontanesi, PhD
Office Manager and Nurse Perspectives on Facilitators of Adult Immunization
Mary Patricia Nowalk, PhD, RD; Melissa Tabbarah, PhD, MPH; Jonathan A. Hart, MS; Dwight E. Fox, DMD; Mahlon Raymund, PhD; Stephen A. Wilson, MD, MPH; and Richard K. Zimmerman, MD, MPH; for the FM-PittNet Practice Based Research Network
VA Pharmacy Users: How They Differ From Other Veterans
Sherrie L. Aspinall, PharmD, MSc; Jessica S. Banthin, PhD; Chester B. Good, MD, MPH; G. Edward Miller, PhD; and Francesca E. Cunningham, PharmD
Do Patients Continue to See Physicians Who Are Removed From a PPO Network?
Meredith B. Rosenthal, PhD; Zhonghe Li, MS; and Arnold Milstein, MD, MPH
Dental Care Coverage Transitions
Richard J. Manski, DDS, MBA, PhD; John F. Moeller, PhD; Haiyan Chen, MD, PhD; Patricia A. St Clair, ScB; Jody Schimmel, PhD; Larry S. Magder, MPH, PhD; and John V. Pepper, PhD
The Effect of Certificate-of-Need Laws on Hospital Beds and Healthcare Expenditures: An Empirical Analysis
Fred J. Hellinger, PhD
Healthcare Reform With a Safety Net: Lessons From San Francisco
Andrew B. Bindman, MD; Anders Chen, MD; Jean S. Fraser, JD; Hal F. Yee Jr, MD, PhD; and David Ofman, MD, MA
Effects of a Medicaid Prior Authorization Policy for Pregabalin
Jay M. Margolis, PharmD; Stephen S. Johnston, MA; Bong-Chul Chu, PhD; Eberechukwu Onukwugha, PhD; Kyle Hvidsten, MPH; Jose Alvir, DrPH; Joseph G. Rossi, PharmD; and C. Daniel Mullins, PhD
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Preventing Myocardial Infarction and Stroke With a Simplified Bundle of Cardioprotective Medications
R. James Dudl, MD; Margaret C. Wang, PhD, MPH; Michelle Wong, MPH, MPP; and Jim Bellows, PhD

Preventing Myocardial Infarction and Stroke With a Simplified Bundle of Cardioprotective Medications

R. James Dudl, MD; Margaret C. Wang, PhD, MPH; Michelle Wong, MPH, MPP; and Jim Bellows, PhD

Bundled cardioprotective medications with simplified delivery reduced the risk of hospitalization for myocardial infarction or stroke among patients at high risk.

Objective: To assess the effect of promoting a bundle of fixed doses of a generic statin and angiotensin-converting enzyme inhibitor/angiotensin receptor blocker (ACEI/ARB), delivered with minimal outpatient visits, laboratory testing, and dosage titration, to people with diabetes, coronary artery disease (CAD), or both in a large integrated healthcare system.


Study Design: Three-year observational study of 170,024 Kaiser Permanente members with diabetes, CAD, or both.


Methods: Using instrumental variable analysis, we assessed the impact of promoting the cardioprotective bundle on hospitalization rates for stroke and myocardial infarction (MI).


Results: In 2004 and 2005, 47,268 of 170,024 individuals received “low exposure” (medication possession on 1 to 365 days). Their risk of hospitalization for MI or stroke in 2006 was lowered by 15 events per 1000 person-years (95% confidence interval [CI] = 1, 30), preventing events in 726 people. Furthermore, 21,292 of 170,024 individuals received “high exposure” (medication possession on 366 to 730 days). Their risk of hospitalization for MI or stroke was reduced by 26 events per 1000 person-years (95% CI = 17, 34), preventing events in 545 people.


Conclusion: A simplified method for bundling fixed doses of a generic statin and an ACEI/ARB was successfully implemented in a large, diverse population in an integrated healthcare delivery system, reducing the risk of hospitalization for MI and stroke.


(Am J Manag Care. 2009;15(10):e88-e94)

Statins and angiotensin-converting enzyme inhibitors individually reduce cardiovascular events, but their combined effectiveness in large populations is undocumented.


  • We promoted the use of a cardioprotective bundle delivered via a simplified regimen—fixed doses of generic medications and minimal outpatient visits, laboratory testing, and dosage titration—to a high-risk population.
  • Exposure to the bundle over 2 years reduced the risk of hospitalization for myocardial infarction or stroke in the following year.
  • Our approach can be applied in many settings to reduce cardiovascular events in populations at risk.
Seminal clinical trials established that statins and angiotensin-converting enzyme inhibitors (ACEIs) individually reduce the rate of fatal and nonfatal cardiovascular events among people with diabetes and/or cardiovascular disease. In patients with diabetes, coronary artery disease (CAD), or other occlusive arterial disease, simvastatin 40 mg/day reduces by about one-quarter the risk of myocardial infarction (MI), stroke, revascularization procedures, and coronary deaths.1,2 Among individuals with known vascular disease or diabetes and another risk factor, ACEIs reduce the rate of MIs by 18% and the

rate of stroke by 23%.3,4

More recently, researchers have investigated the impact of combination pharmacotherapy. In a very small study, the vascular and metabolic effects of combined therapy with simvastatin and ramipril in patients with type 2 diabetes were more beneficial than those of either drug alone.5 In patients with diabetes, evidence-based pharmacotherapy combined with dietary and exercise interventions reduced the risk of cardiovascular events by approximately 50%.6 In a pilot study of patients undergoing peripheral vascular interventions, evidence-based use of statins, ACEIs, beta-blockers, and antiplatelet therapy reduced death, MI, and stroke at 6 months; in a later study of patients with acute coronary syndrome, this evidence-based drug therapy was associated with a greatly reduced risk of death at 6 months.7,8 In adults without known cardiovascular disease, a “polypill” containing low doses of thiazide, atenolol, ramipril, simvastatin, and aspirin reduced blood pressure, low-density lipoprotein cholesterol (LDL-C), and urinary 11-dehydrothromboxane B2 levels.9

Individual drug trials and subsequent studies raised 2 questions. First, could a simple process be developed to deliver combination pharmacotherapy to large numbers of people with diabetes or CAD in realistic settings across an entire delivery system? Second, how would implementing such a process affect hospitalizations for cardiovascular events?

In 2002, Kaiser Permanente used the Archimedes Model to project the effects of combined pharmacotherapy and to develop a simple, inexpensive method for delivering it.10-12 The Archimedes Model realistically simulates the pathophysiology, treatments, and outcomes of disease and its complications at the level of individuals and aggregates the results to project population-level effects that correlate well with clinical trial results.13 Using evidence from available clinical trials, the model forecasted that a “bundle” of a statin and an ACEI would, beginning in the first year, reduce by 71% the risk of MI and stroke in a high-risk population of individuals with diabetes. Subsequent trials and meta-analyses enriched our understanding of the benefits of these medications, but were not available at the time of modeling.14,15

The modeling also determined that using generic formulations and offering a fixed dose to every person, regardless of baseline blood pressure or LDL-C level, would achieve these results with the most efficient use of clinical resources. The model also predicted that population-level clinical benefits could be achieved without patient-by-patient titration to physiologic target, which has since been confirmed elsewhere.16

As a result, Kaiser Permanente’s clinical leaders launched an initiative to make bundled cardioprotective therapy rapidly and widely available to all Kaiser Permanente members with diabetes over the age of 55 years and all members with CAD. Individuals were offered a medication bundle consisting of a statin (typically lovastatin 40 mg/day) and an ACEI (typically lisinopril 20 mg/day). Physicians were advised to use a single initiation visit to rule out contraindications, eliminate patients at high risk for complications (eg, those with serum creatinine >1.5 mg/dL, underlying liver disease, or prior rhabdomyolysis or angioedema), and adjust downward the lisinopril dosage in hypotension-prone patients. Physicians exercised clinical judgment about whether it was appropriate to titrate the dosage for safety purposes or to meet a target. An angiotensin II receptor blocker was substituted for the ACEI when clinically indicated; for convenience, we refer to both here as ACEIs. Laboratory tests consisting of total cholesterol and LDL-C, triglycerides, high-density lipoprotein cholesterol, serum creatinine, potassium, and alanine aminotransferase were advised before starting therapy and at 3 weeks to 3 months. The medication bundle also included low-dose aspirin, but aspirin was not part of our study because we could not consistently measure its use.

A variety of programwide strategies supported rapid implementation. Each Kaiser Permanente region determined how best to meet the guidelines of the initiative under local conditions, but key elements across all regions included extensive use of clinical champions, patient education, outreach strategies, and point-of-service reminders. In addition, electronic clinical decision support tools at the point of care identified members in the target population who were not yet receiving statins and ACEIs. As the initiative rolled out across the regions, a national network of clinical champions teleconferenced quarterly to share regional performance reports on bundle use and learnings about how to facilitate rapid implementation.

Bundle use grew rapidly. Between 2002 and 2005, the percentage of eligible members in the regions we studied who consistently used the medication bundle increased from 33% to 52% of the target population. We report here the clinical impact of the initiative.


Setting, Subjects, and Data Sources

Kaiser Permanente is the largest not-for-profit integrated health delivery system in the United States, serving 8.7 million members in 8 regions spanning 9 states and the District of Columbia. Kaiser Permanente provides and coordinates the entire scope of members’ care, including preventive care, well-baby and prenatal care, immunizations, emergency care, hospital and medical services, and ancillary services such as pharmacy, laboratory, and radiology.

We studied the bundle’s impact in Kaiser Permanente’s 2 largest regions: Northern and Southern California. Our study population consisted of 170,024 members who were (1) diagnosed with CAD and/or over the age of 55 years and diagnosed with diabetes, (2) not already taking both bundle medications as of 2003, and (3) continuously enrolled between January 1, 2001, and December 31, 2006. Members were included in the study if they received either statins or ACEIs in 2003 but were excluded if they received both. The study population was part of the much larger, programwide Kaiser Permanente population receiving the medication bundle.

We obtained baseline characteristics for the study population dating from 2001. Widespread use of the medication bundle rose most rapidly during 2003. We measured bundle use in 2004 and 2005 and adverse events in 2006. Data on diagnoses, medication use, and event rates before and after the initiative were derived from inpatient and outpatient encounter records and pharmacy and laboratory databases. Data on hospitalization rates for MI and stroke were extracted from hospital discharge and billing claims databases. The appropriate institutional review boards approved the evaluation protocol.


To measure exposure to the medication bundle, we first examined statins and ACEIs independently. We calculated exposure as the total number of days for which each drug was dispensed between January 1, 2004, and December 31, 2005 (“dispensed days”). We assumed that exposure to the medication bundle (“bundle days”) was equal to the lower of the dispensed days for individual medications.

We classified members with zero bundle days dispensed during 2004 and 2005 as “no exposure,” those with 1 to 365 bundle days dispensed as “low exposure,” and members with 366 to 730 bundle days dispensed as “high exposure.” The main outcome measure was hospitalization due to MI or stroke between January 1 and December 31, 2006.

Statistical Analysis

As is commonly the case when estimating clinical effects from observational studies, patient selection represented a significant source of potential bias.17 Patients at highest risk may be more apt to take prescribed medications, and clinicians may be more likely to prescribe cardioprotective medications for patients at highest risk, although some evidence suggests a paradoxical risk-treatment relationship.18 The possibility of  selection bias is most acute when the analysis cannot incorporate some risk factors, as was the case in our study because we could not consistently obtain data on factors such as body

mass index or smoking status.

Instrumental variable analysis can effectively address patient-level selection biases caused by unmeasured confounding variables.19-21 It does so by introducing into the analytic model 1 or more variables, the “instruments,” that are correlated with the treatment but not causally related to outcomes except through the treatment (Figure). Instrumental variable analysis yields unbiased estimates of individual-level treatment effectiveness if the underlying assumption about absent causal relationships between instruments and outcome is valid.

We used facility-level use rates as instruments, making use of variations across facilities in promoting bundle use. Facility-level use rates make good instrumental variables for this purpose because they are strongly associated with individual bundle exposure; by definition, patients at high-use facilities are more likely to have statins and ACEIs dispensed. We reasoned that facility-level use rates would be related to the outcomes only through individual exposure. The reasoning underlying our use of instrumental variable analysis is that patients can be viewed as randomly assigned to high- or low-use facilities. The resulting estimate of treatment effectiveness is based on patients who would have been treated at high-use facilities but not treated at low-use facilities.

Instrumental Variable. A total of 58 facilities, with 74 to 11,600 members of the study population per facility, were included; for each, we calculated the percentage of members of the target population who had any exposure to the bundle. Facility-level use rates ranged from 32.2% in the lowest-using quintile of facilities to 49.1% in the highest-using quintile. Unadjusted annual rates of hospitalization for MI or stroke in 2006 ranged from 22.8 per 1000 members in the lowest-using quintile of facilities to 17.7 per 1000 in the highest-using quintile.

Covariates. We adjusted for covariates for which we were able to obtain reliable and consistent observational data: age, sex, comorbidities (diabetes, heart failure, depression, CAD), and geographic region. We also adjusted for glycemic control in 2003; the number of previous hospitalizations due to MI, stroke, and all other causes in 2001-2004; and the number of previous coronary artery bypass graft and percutaneous transluminal coronary angioplasty procedures in 2001-2004. We also adjusted for history of hyperlipidemia through 2003, using a proxy variable based on documented LDL-C control and use of lipid-lowering medications during 2001-2003.

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