Cost and cost-effectiveness studies in heart failure research

Progress in Cardiology

Cost and cost-effectiveness studies in heart failure research William S. Weintraub, MD,a Jason Cole, MD,a and Joseph F. Tooley, PharmDb Atlanta, Ga

Background Heart failure is a major and increasing cause of death and disability and accounts for significant resourse use. In the United States alone, the prevalence is 4.6 million, with an incidence rate of 550,000 new cases a year and approximately 957,000 hospitalizations a year.

Methods and Results Methods of evaluating cost and outcome and of comparing cost with outcome are reviewed. Economic and cost-effectiveness studies in heart failure research, especially those related to clinical trials, are reviewed in the therapeutic areas of digoxin, angiotension-converting enzyme inhibition, beta blockers, disease management, and transplantation. Conclusion In an era in which economic constraints on medical resourse use limit the ability to give all services to all patients, economic studies can help guide more rational decision making. Economic studies in heart failure can be expected to improve and so help society to make better, more informed choices. (Am Heart J 2002;143:565-76.) Overview of heart failure Costs related to heart failure comprise $20.3 billion in direct costs and $2.2 billion in indirect costs, for a total of $22.5 billion. This figure may be an underestimate because a portion of the costs for coronary artery disease are likely to be the result of heart failure. Heart failure itself poses a considerable societal burden.1 In the United States, the approximate prevalence of heart failure is 4.7 million, with an incidence rate of 550,000 new cases a year and approximately 978,000 hospitalizations a year. Furthermore, hospitalizations for heart failure have increased by 159% between 1979 and 1998.2 In 1997, the Health Care Financing Agency paid $3.7 billion to Medicare beneficiaries for heart failure, which is the single most common cause of hospitalizations for patients aged >65 years.3 Heart failure is a disease process and thus differs from and is more complicated than a single form of therapy or diagnostic test (Table I). In consideration of a new therapy for heart failure, there may be no clear starting point or stopping point (other than death). The natural history of heart failure may vary substantially, as may management. The patient’s condition may be stable but then decompensate, resulting in a hospitalization and intensified therapy, presumably with a somewhat worse health state and associated costs. The goal of symptomFrom the aDivision of Cardiology, Emory University School of Medicine, and bGlobal Outcomes Research, Pharmacia. Funded by a grant from Pharmacia. Submitted February 20, 2001; accepted October 10, 2001. Reprint requests: William S. Weintraub, MD, Emory Center for Outcomes Research, 1652 Briarcliff Rd, Ste 1N, Atlanta, GA 30303. E-mail: [email protected] Copyright 2002, Mosby, Inc. All rights reserved. 0002-8703/2002/$35.00 + 0 4/1/120965 doi:10.1067/mhj.2002.120965

atic heart failure therapy is to return the patients to their baseline health state and maintain them there. Finally, after all other therapeutic options have failed, patients may be considered for transplantation to try to reverse or partially reverse heart failure, also with associated costs. Economic considerations should include direct costs and indirect costs, which may be substantial because of lost productivity. Heart failure may also have a considerable impact on how people feel (quality of life) and how they function (health status). A good design for an outcomes study in heart failure should take into account all of these possibilities.

Background on economic analyses In an environment with economic limitations, products or services compete for resources on the basis of effectiveness or utility and cost. A comparison of cost between contending therapies can involve a simulation in which costs and outcome are estimated from nonrandomized comparisons and randomized, controlled trials. Even within randomized trials, an economic analysis can range from a simulation to a detailed component of the trial with extensive primary data collection. For any of these designs, the simplest type of economic study is a comparison of costs or a cost-minimization study. Such a study is useful when it is reasonable to assume that the 2 treatments offer similar outcomes. When effectiveness cannot be assumed to be the same for competing therapies, there are 3 related forms of economic analyses that can be used to study the relationship of cost to outcome: cost-effectiveness, cost-utility, and cost-benefit. Cost-effectiveness analysis assumes that there is 1 overall measure of effectiveness, often survival.4 This method breaks down when there are

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Figure 1

Decision matrix.

Table I. What is different about economics of heart failure? Disease process rather than procedure No clear starting point No clear stopping point Disease course may vary widely Management may vary widely Boundaries of inclusion may be difficult Indirect costs may be substantial Health status may be affected significantly

multiple measures of effectiveness. For instance, 1 form of therapy may increase the risk of death but offer improved symptomatic status. This may, in principle, be addressed through cost-utility analysis in which all measures of effectiveness are incorporated into 1 measure, utility.4 A third and somewhat less popular form of analysis is cost-benefit analysis in which measures of both cost and effectiveness are reduced to a single measure, generally in a currency.4 We can begin to understand the approach of costeffectiveness analysis with consideration of competing therapies, A and B, for treatment of the same condition (Figure 1). In panel 1, therapy A is less effective but

more expensive than therapy B. In this setting, B is said to dominate A. Similarly in panel 4, A is more effective and less expensive than B. In this setting, A would dominate B. Commonly, however, the more effective therapy or test is also more expensive. Thus, in panel 2, A is more effective but also more expensive. Similarly, in panel 3, B is more effective but also more expensive. When a therapy is both more effective and more expensive than the competing therapy, cost-effectiveness analysis can help decision makers choose whether to allocate resources to the more effective service. The perspective in these analyses can have an important impact on their structure and outcome. For instance, an analysis from a hospital’s perspective might not include the long-term consequences of a particular clinical strategy, whereas this issue may be most important to the patient and the payor. The perspective of all of the various stakeholders may be viewed in aggregate as “society.” To be most useful in serving societal goals, cost and cost-effectiveness analyses should be performed from a societal perspective, in which an attempt to measure all of the costs and measures of outcome associated with a particular treatment is made. These costs should include those incurred by

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the patient, the costs of medical resources that could have been used for other patients, and any loss of income that the patient sustained because of poor health and the loss of income for those who may have provided informal care to the patient. Outcome should include events, quality of life, and survival. By looking at the sum of all of these costs in relation to outcome, a policy maker could decide, for example, whether the public good benefited more by allocating limited health care resources to preventive services or a new therapy for heart failure.

Determining costs

Weintraub, Cole, and Tooley 567

Table II. Nomenclature for costs Cost perspective Provider (ie, hospital or professional) Payer (ie, insurance carrier) Patient Cost category Direct costs Indirect costs Accounting method Top-down Bottom-up Costs per service Average cost Marginal (incremental) cost

Nomenclature for costs Economists are more concerned with how society chooses to allocate limited resources rather than what something costs per se.5 Cost may be used to sum resource use of several types, permitting an economic comparison of services with a common scale. Accounting methods are used to develop costs from resource use; a summary of accounting names is shown in Table II. Costs must be considered from one of several possible perspectives.6 For hospitals, costs are their expenses related to providing a service. For payers, the cost is what the providers charge, plus their administrative expenses. In principle, cost studies often seek to determine societal costs, which can be used in cost-effectiveness analyses to gain the widest perspective. However, societal costs are never directly measurable, and thus combinations of cost proxies from 1 or several stakeholders, where measurable, are often used as estimates. Costs are classified as direct or indirect.7 Varying definitions of indirect costs may lead to uncertainty in categorizing a particular cost. Theoretically, direct costs are those incurred by a stakeholder for a therapy or test, and indirect related costs are those incurred by other societal groups. More commonly, direct costs relate to the provision of medical care, and indirect costs are other societal costs. Medical costs can also be divided into 3 components: in-hospital direct costs, follow-up direct costs, and indirect costs. Inpatient costs are comprised of hospital costs (eg, room, laboratory testing, pharmacy) and physician professional billings. Follow-up direct costs include physician office visits, outpatient testing, medications, home health providers, and additional hospitalizations. Indirect costs reflect lost patient or business opportunity and may be referred to as productivity costs.8 A final way of thinking about costs is that direct costs are realistically linked to a particular service and indirect costs are not. This type of indirect cost is also called overhead.9 The appropriate length of time over which to measure costs is dependent on the procedures being studied and outcomes being measured. The cost of a hospitalization for heart failure could be considered the ini-

tial hospitalization alone. Alternatively, the cost for a hospitalization for heart failure could be considered to include the “induced” cost related to that hospitalization during a period of follow-up examination.10 Often in the United States, hospital provider costs are used as a proxy for societal costs. What a hospital charges for a service is not its cost.11 Measuring hospital cost is difficult and has been approached with what is called either top-down or bottom-up accounting.12 Top-down costing involves dividing all the money spent on a hospitalization or procedures by the number of episodes of care of the particular type performed. A payer perspective would be the amount paid the provider for the service. In contrast, a bottom-up approach involves individually costing all resources used for a service (ie, supplies, equipment depreciation and facilities, salaries, etc). All methods involve a set of assumptions and limitations. In consideration of the cost of a specific procedure with top-down costing, it must be assumed that costs in the department in which the procedure is provided can be separated from costs in other departments. There may also be variability within a department. Bottom-up methods also are limited by the ability to account for all resources consumed and to appropriately apply costs. Another issue involved in measuring hospital costs is average versus marginal or incremental cost.13 Average cost is calculated by dividing all costs for a therapy or test by the number of that particular type. In contrast, the marginal cost is the cost of the next similar procedure. Average costs include all resources used, including overhead, whose costs would not be decreased if not used. Marginal costing accepts fixed costs as a given and focuses only on variable costs or those additional resources consumed by each additional patient. Variable costs are analytically separated from fixed costs by establishing the perspective and time frame as fixed. For instance, facilities’ costs are commonly considered fixed, but how should marginal personnel costs be assigned? If an older test, such as Swan Ganz catheters, decreases as echocardiography becomes more common, how is the

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decrease in intensive care unit nurse activity and increase in echocardiography technician activity reflected? Because of these difficulties, most cost and cost-effectiveness studies use average costs.

Cost measurement There is a detailed approach to top-down costing on the basis of the Universal Billing 92 summary of hospital charges, which is commonly used in the United States.14 The Universal Billing 92 summary is a uniform billing statement used by all third party carriers. The relationship between costs and charges, in the form of global specific cost to charge ratios, must be developed with American Hospital Association guidelines and then filed annually with the Centers for Medicare and Medicaid Services (formerly the Health Care Financing Administration) in a Hospital Cost Report, which is in the public domain. An alternative approach is to use bottom-up cost accounting and assign cost weights to each type of resource used.15 The sum of resources times their cost weights yields total cost. However, the methods are sufficiently laborious that they are rarely used. Another approach is to use a payer perspective.16 In the United States, Medicare diagnosis-related group (DRG) reimbursement rates can be used to define cost. Similar methods are available in other countries. The use of DRGs to assign cost does not account for variation in cost within that DRG and may not even reflect average resource use. To assess professional costs, it is not sufficient to consider only the primary physicians’ fees alone because other professionals provide services.17,18 The goal must be to capture all of the professional services for an episode of care. In the United States, there has been an effort to rationalize physician payments by developing a set of scales for services.19 This system, the resourcebased relative value scale, was developed over time to try to assess the relative time, physical, and cognitive efforts associated with physician services.19 Each service is assigned a number called the relative value unit (RVU). If the profile of physician services for a procedure or hospitalization is known, then RVU for each service may be used to develop a proxy for the physician costs. The total RVU may be converted to a dollar figure with a conversion factor from Medicare or private insurance carriers. The determination of the costs of outpatient services presents different challenges in the determination of patient services utilization, including direct and indirect medical costs. Direct costs include physician office visits, medications, procedures and testing, rehabilitation, nursing home stays, and home health services, and patient out-of-pocket expenses, including travel. Services can be assigned a cost with the Medicare fee schedule as discussed previously. Medication costs can be estimated

from compiled prices by sampling pharmacies or with published wholesale pharmaceutical prices. Indirect productivity costs include missed time from work by the patient or family members. In any case, it is not possible to directly measure all of the indirect costs. For instance, if an executive in a company has a myocardial infarction (MI) and is out of work for 6 weeks, there may or may not be loss of pay, but the effect on the business cannot readily be determined. Indirect costs, if measured at all, are often confined to family loss of income, and the numbers must be examined with both interest and skepticism.

Inflation and discounting Costs in the future should be deflated with multiplication with a constant to convert from any 1 year to another, on the basis of the medical inflation rate.20 Future costs should also be discounted to reflect the opportunity costs of current dollars, or future costs should be expressed at their present value.21 For instance, if a policy maker were given the alternative of spending $1000 now or $1000 in 5 years to treat a given condition and obtain the same outcome, the decision would always be the latter. Costs are generally discounted at a rate of 3% to 5% per year.21

Comparing costs to outcome Determination of patient utility and quality-adjusted life years In the treatment of heart failure, it is unusual for 1 measurement of outcome to be of sufficient clinical importance that all other outcome measures may be ignored in clinical decision making. Although death overwhelms other outcome measures in importance, these patients also have considerable disability. Thus, a therapy may be justified on the basis of symptomatic improvement alone, even if not life saving. In principle, this task may be accomplished through the determination of patient utility. The utility of a therapy or test is the sum of benefits, both positive and negative, that accrues to a patient over time as the result of the procedure.22 We may consider the assessment of utility beginning with a decision tree (Figure 2), which takes a patient at a specific point and then considers, in principle, all possible events up to some point in the future. In this model, nodes with squares represent choices and nodes with circles represent chance events. In the simplified model shown, a single choice is made and, for each choice, there are two possible outcomes. Each outcome is called a health state. Each health state has a utility and a probability of occurrence. The utility of choice A in Figure 2 is the sum of the utility of health state 1 times its probability plus the utility of health state 2 times its probability. Unlike this simplified model, for any 1 treatment, there may be mul-

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Figure 2

Idealized decision tree for decision on diagnostic strategy or therapeutic choice. P, Probability of health state “x”; U, utility of health state “x.”

tiple possible health states; it is generally difficult to determine the probability and utility health states. Utility changes over time correspond to changes in health state. The utility of 2 alternative treatments for heart failure is compared in Figure 3. After initiating therapy A, the patient may feel well and utility rises. A recurrent symptomatic period between year 1 and 2 causes utility to fall. With successful treatment, utility rises again. For therapy B, there is no episode of recurrent symptoms and utility gradually rises. Ultimately, the patients get to the same point, but the patient who has the episode of recurrent heart failure has a period of decreased utility. Utility measurement includes patient preference. One patient may dislike the disability of heart enough to be willing to undergo more aggressive therapy to maintain function. Another patient may dislike the difficulties involved with more aggressive care enough to be willing to put up with more functional limitation. Utility may be measured indirectly with either a validated survey, such as the Health Utilities Index23 or the EuroQol,24 or with directly assessing patient preference. The patient preference methods, Standard Gamble and Time Trade-off,4 ask patients to directly evaluate their current state of health and then evaluate what they would give up or risk to achieve perfect health. The patient preference methods are probably

superior to surveys because the evaluation of patients’ views of their own states of health are measured directly, but they are more difficult to administer. In the Time Trade-Off approach, patients weigh the fraction of expected survival they are willing to give up to live in perfect health. With the Standard Gamble, patients weigh what risk of death they are willing to take to live in perfect health. The Standard Gamble is probably superior because it includes the element of risk.4 Utility alone does not provide a final summary measure of outcome because it does not include life expectancy. A summary measure can be created by combining utility and survival to obtain quality-adjusted life years (QALYs).25 Survival, as with cost presented previously, is generally discounted, which means that patients value a year of survival at the present time more than a year of survival in the future. The “true” discount rate for survival is unknown. Values in the literature for the discount rate have varied from 2% to 10%, with 3% being the most popular, and it should be discounted at the same rate as cost.21 Thus, with a discount rate of 3%, next year’s survival is 3% less important than this year’s survival. QALY is the best summary measure of outcome in a cost-utility analysis because it incorporates patient value, risk aversion, expected survival, and a discount rate.

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Figure 3

Theoretic time course of utility for 2 different therapies for heart failure. With therapy A, there is a dip in utility followed by recovery, and for therapy B, utility gradually rises.

Cost-effectiveness and cost-utility analysis Cost-effectiveness is defined as the change in cost per unit increase in effectiveness. If the summary effectiveness measure is in QALYs, then the marginal or incremental cost effectiveness of therapy or test A compared with therapy or test B is defined as: COSTA – COSTB/ QALYA – QALYB. The cost-effectiveness ratio combines the 3 important outcome measures of utility, survival, and cost. Cost-effectiveness analysis involves multiple assumptions in measuring both cost and outcome, which introduces uncertainty or error. Uncertainty in clinical microeconomics is generally approached through sensitivity analysis. With sensitivity analysis, measurements in which there is uncertainty are varied between appropriate ranges and the analysis is repeated. However, the appropriate ranges for the variables for sensitivity analysis may not be clear. Sensitivity analysis offers a sense of the stability of the cost-effectiveness ratio; in some studies the variation in the ratio with sensitivity analysis may be small, and in others it may be sufficiently large that the original point estimate may have little meaning. Therapies that appear cost-effective with only the central point estimate may not seem as cost-effective when the underlying assumptions are varied, or a ratio that was marginally cost-effective may seem quite cost-effec-

tive when the assumptions are varied; this may be especially true concerning the cost of a new therapy that may decline over time.

Cost-effectiveness of therapy for heart failure There have been studies of the cost-effectiveness of heart failure therapy concerning the use of digoxin, angiotensin-converting enzyme (ACE) inhibition, beta blockade, disease management, and transplantation. These are summarized in Table III and are presented subsequently.

Digoxin Despite more than 200 years of experience, the role of digoxin in the treatment of heart failure remains uncertain. In the absence of adequate clinical data, the cost-effectiveness data will be similarly limited. Nonetheless, Ward et al26 developed a decision-analytic model concerning digoxin withdrawal in patients with stable heart failure. The clinical sequelae of digoxin withdrawal came from the Prospective Randomized Study of Ventricular Failure and Efficacy of Digoxin and Randomized Assessment of Digoxin and Inhibitors of Angiotensin Converting Enzyme trials.27,28 Costs were

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estimated from hospital and Medicare data. Outcomes included treatment failures, digoxin toxicity, and health care costs. Continuation of digoxin therapy in patients with heart failure nationally would avoid 185,000 office visits, 27,000 emergency visits, and 137,000 hospital admissions for heart failure but would result in 12,500 cases of digoxin toxicity. The net annual savings would be $406 million (90% CI of $106 to $822 million). Sensitivity analysis results showed that digoxin is cost saving if the incidence rate of digoxin toxicity is ≤33%. Thus, digoxin therapy was found to dominate withdrawal of digoxin in stable heart failure. In a large randomized trial study, the effect of digoxin on mortality and hospitalization rates in patients with heart failure and left ventricular ejection fractions of ≤0.45 were randomly assigned to digoxin (3397 patients) or placebo (3403 patients) in addition to diuretics and ACE inhibitors.29 Although there was no effect on mortality rate, there was a 6% reduction in hospitalizations overall with digoxin and fewer hospitalizations for worsening heart failure (26.8% versus 34.7%; relative risk, 0.72; 95% CI, 0.66 to 0.79; P <.001). Although no formal cost-effectiveness analysis is available, Mark30 estimated that the digoxin therapy is at least cost neutral and probably cost saving.

Angiotensin-converting enzyme inhibition In a metaanalysis of 32 trials totaling 7105 patients, the mortality rate in patients randomized to ACE inhibitor was 15.8% compared with 21.9% for placebo (odds ratio, 0.77; 95% CI, 0.67 to 0.88).31 None of these trials included prospective economic evaluations. However, there have been several decision analytic analyses on the basis of these trials. Several large randomized trials have shown a reduction in acute MI for patients with left ventricular dysfunction after an acute MI who undergo treatment with an ACE inhibitor.32 Tsevat and colleagues33 examined the cost-effectiveness of this intervention with resource utilization, survival, and health-related quality of life information from the Survival and Ventricular Enlargement (SAVE) trial, a randomized trial of captopril for survivors of an anterior MI with an ejection fraction of ≤40%. The investigators conservatively estimated that the benefit of captopril did not persist beyond 4 years. The trial found that captopril improved survival rate at 3.5 years by about 20%. Costs were calculated in 1991 dollars. The cost-effectiveness ranged from $60,800 per QALY for 50-year-old patients to $3600 for 80-year-old patients. Hummel et al34 performed a similar analysis in the United Kingdom on the basis of data from SAVE, noting that over 4 years therapy costs were approximately £10,000 per life saved in 1994 to 1995 values. McMurray and colleagues35 also found that ACE inhibitors are an economically attractive intervention after MI. Glick et al36 developed a decision analytic model on

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the basis of the Studies of Left Ventricular Dysfunction (SOLVD) trial.37 SOLVD was an 83-center trial in which 2569 patients with symptomatic heart failure and ejection fractions ≤35% received either the ACE inhibitor enalapril or placebo. At 41.4 months follow-up period, enalapril decreased mortality and hospitalization rates by 16% and 26%, respectively. Costs were estimated on the basis of Health Care Financing Administration reimbursement rates in 1992 dollars. For patients with heart failure, enalapril dominates placebo in the short term and is highly economically attractive in the long term. Enalapril saved approximately $717 per patient during the period of the SOLVD treatment trial. When trial data were projected over a patient’s lifetime, therapy with enalapril produced a cost utility ratio of $115 per QALY. As noted by Boyko, Glick, and Schulman,38 there is variation in the cost of ACE inhibitors, and as these agents have become less expensive their costeffectiveness ratio may become even more attractive. Somewhat more general in the treatment of heart failure, is the Paul et al39 decision-analytic model on the basis of the SOLVD and Veterans Affairs Cooperative Heart Failure I and II trials. These trials considered the strategies of (1) standard therapy (digoxin and diuretics) with no vasodilator agents, (2) hydralazine hydrochloride–isosorbide dinitrate combination, and (3) ACE inhibition with enalapril. With data from 3 major randomized controlled trials to estimate treatment efficacy, mortality rates, and hospitalization rates, the cost was $5600 per year of life gained with hydralazine–isosorbide dinitrate compared with standard therapy. Compared with the hydralazine-isosorbide combination therapy, the incremental cost-effectiveness ratio for enalapril therapy was $9700 per year of life saved. The cost-effectiveness of ACE inhibition also has been studied in Europe with decision analytic techniques. In mild heart failure, Kleber40 found ACE inhibition to be cost-effective but not cost saving. However, in The Netherlands, van Hout et al41 found ACE inhibition to dominate not using ACE inhibition. Similarly, in a study from the United Kingdom on the basis of SOLVD trial, Hart, Rhodes, and McMurray42 found that ACE therapy could potentially dominate not using ACE-inhibition therapy. Butler and Fletcher43 performed a similar costeffectiveness study with a decision-analytic model on the basis of SOLVD trial in Australia. They also found that use of ACE-inhibition therapy would be cost saving and, therefore, dominant. Erhardt et al44 conducted an economic study in Sweden considering ACE inhibition with data from the Acute Infarction Ramipril Efficacy (AIRE) study. In AIRE, 2006 patients with heart failure after MI were randomized to ramipril versus placebo. With ramipril, there was 17% mortality rate over 15 months compared with 23% with placebo. Ramipril also resulted in a significant decrease in hospitalizations. Costs were on the basis of Swedish reimburse-

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Table III. Summary of heart failure economic studies Study

Intervention

Study size

Population

Costs

Ward et al26

Digoxin withdrawal

Total 266 patients

Patients with NYHA classification II/III CHF on digoxin

Assumed, on basis of average cost at Henry Ford Hospital

Tsevat et al33

Captopril

2231 patients

Patients s/p MI with EF <40%

Calculated from SAVE trial at Brigham and Women’s Hospital

Hummel et al34

Captopril

2231 patients

Patients s/p MI with EF <40%

Assumed, from NHS Trusts in England and “published drug costs”

Glick et al37

Enalapril

2569 patients

Patients with EF <35%

Assumed, from HCFA RBRVS and federal supply drug costs

Paul et al39

Hydralazine, isosorbide dinitrate

3 trials: 642, 804, and 2569 patients

Patients with CHF

Assumed, on basis of internal costs at Massachusetts General Hospital

Erhardt et al44

Ramipril

2006 patients

Patients with CHF at any time s/p MI

McMurray et al35

Ramipril, captopril

2 trials of >2000 patients each

Patients with CHF s/p MI

Assumed, on basis of Swedish pharmacy drug costs and Swedish hospital costs Assumed, on basis of United Kingdom national database costs; ACE-inhibitors each assumed to have same cost

Delea et al46

Carvedilol

1094 patients

Patients with NYHA classification II-IV CHF with EF <35%

Assumed, from Medicare parts A and B payment rates

Disease management strategy

282 patients

Patients with classification III-IV CHF

Prospectively determined during study

Patients for cardiac transplant

Estimated, with wide range of variation

Rich et al49

Evans54

Cardiac transplantation

NYHA, New York Heart Association; CHF, congestive heart failure; s/p, status post; EF, ejection fraction; NHS, National Health Service; HCFA, Health Care Financing Administration; RBRVS, resource-based relative value scale; PROVED, Prospective Randomized Study of Ventricular Failure and Efficacy of Digoxin; RADIANCE, Randomized Assessment of Digoxin and Inhibitors of Angiotensin Converting Enzyme.

ments rates. The marginal cost-effectiveness was measured over 3 treatment periods: 1, 2, and 3.8 years. The cost-effectiveness varied from $1837 to $4290 for the 3 treatment periods. McMurray and colleagues35 also found that ACE inhibitors are an economically attractive intervention after MI. A decision-analytic model on the basis of AIRE and SAVE was developed. Costs were based on resource use in the United Kingdom. Cost per year of life gained over 10 years for patients at high risk (AIRE strategy) was £1752/life year gained and for patients at intermediate risk (SAVE strategy) was £2962/life year gained. An alternative is initial short-term treatment of all patients, with cost per life year gained of £2017 for

patients at high risk and £3110 for patients at intermediate risk.

Beta blockade There have been 4 randomized trials of carvedilol in 1094 patients with New York Heart Association classification II to IV symptoms and left ventricular ejection fraction ≤0.35.45 The series of trials was terminated early, on the basis of a finding of a 65% mortality rate reduction in patients receiving carvedilol (95%CI, 39% to 82%). Delea et al46 constructed a decision-analytic model, estimating life expectancy and health care costs for patients with heart failure receiving carvedilol plus conventional therapy (digoxin, diuretics, and ACE

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Costs discounted

Cost-effectiveness

Sensitivity analysis

Comments

No

Net annual savings, $406 million

Digoxin cost saving if digoxin toxicity <33%

On basis of PROVED27 and RADIANCE28 trials

5%/year

$60,800 per QALY at age 50 years; $3600 per QALY at age 80 years £10,000 per life-year saved during 4 years

Generally not sensitive to variable estimates over a wide range

On basis of SAVE trial

Results most sensitive to discounting of costs versus discounting both costs and life-years Results most sensitive to estimate of hospitalization rates with enalapril therapy Generally not sensitive to wide range of variable assumptions

SAVE trial was basis: results from United States applied to Britain

No (but discounting included in sensitivity analysis) 5%/year

6%/year

5%/year 3%/year

3%/year

No

No data

Therapy saved $717/ patient during course of therapy; $115 per QALY during patient lifetime Cost was $5600/year of life gained for hydralazine/ isosorbide dinitrate and $9700/year of life gained for enalapril Cost-effectiveness varied $1837 to $4290 during 1, 2, and 3.8 years Costs per year of life gained during 10 yrs: £1752 for ramipril strategy and £2962 for captopril strategy Costs per year of life gained: $29,477 assuming limited benefits and $12,799 assuming extended benefits Intervention saved $460/year Transplantation costs $44,300 per year of life saved

inhibitors) or conventional therapy alone. Benefit estimates assumed either limited benefits persisting for 6 months, the average duration of follow-up in the clinical trials, or extended benefits, persisting for 6 months and then declining gradually over 3 years. For conventional therapy alone, estimated life expectancy was 6.67 years, and for carvedilol, it was 6.98 and 7.62 years, assuming limited and extended benefits, respectively. Expected lifetime costs of heart failure–related care were estimated at $28,756 for conventional therapy and $36,420 and $38,867 for carvedilol, assuming limited and extended benefits, respectively. Cost per life-year saved for carvedilol was $29,477 and $12,799 with limited and extended benefits assumptions,

Generally not sensitive to changes in most parameters studied Results most sensitive to drug costs

Most sensitive to mortality rates for patients with CHF on carvedilol

On basis of results from SOLVD36 trial Analysis of SOLVD, Veterans Affairs Cooperative Heart Failure (VheFt I), and VheFt II trials On basis of AIRE trial Comparison of high-risk strategy of AIRE trial with ramipril versus intermediate-risk strategy of SAVE trial with captopril On basis of US Carvedilol Heart Failure Treatment Program

Not performed

Prospective trial

Not performed

Limited and dated study

respectively. Thus, the cost-effectiveness of carvedilol remains reasonable but is not as attractive as that of ACE inhibition. Schadlich, Pashen, and Brecht47 evaluated the costeffectiveness of bisoprolol in Germany, and Malek et al48 in the United Kingdom on the basis of the Cardiac Insufficiency Bisoprolol Study. A total of 641 patients with classification III (95%) and classification IV (5%) heart failure, treated with diuretics and vasodilators, were randomized to placebo versus bisoprolol, 1.25 to 5 mg. Although there was no difference in mortality rate, bisoprolol improved functional status as measured with New York Heart Association classification. In addition, fewer of the patients for bisoprolol needed hospi-

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talization for heart failure (61 patients for bisoprolol versus 90 for placebo; P <.01). With all cardiovascular events, there were 107 in the patients for bisoprolol and 154 in the placebo group (P <.001). In the economic analysis by Schadlich, Pashen, and Brecht,47 resources used for outpatient care, medication use, and hospitalizations were converted to cost on the basis of published German estimates. The authors noted cost savings with bisoprolol, suggesting strong dominance of beta-blocker therapy. Similarly, Makek et al48 estimated costs on the basis of hospital reimbursement rates in the United Kingdom. The investigators found that use of bisoprolol was at least cost neutral.

Disease management strategies Heart failure is particularly well suited to developing strategies, such as the development of heart failure clinics, to improve management. However, evaluating treatment strategies is difficult because (1) it is difficult to construct randomized trials logistically, (2) there may be contamination in which the management strategy is used to some extent in the control arm, (3) there may be differences between programs that are inherent in different medical centers that make collaboration for multisite efforts difficult, and (4) different health care systems may vary substantially. These variations may also limit generalizability. The difficulties in mounting trials to evaluate outcome of management strategies is a similar limitation for randomized trials. Nonetheless, several small efforts have been attempted. Rich et al49 conducted a randomized trial with a nurse-directed, multidisciplinary intervention on readmission rates within 90 days of hospital discharge, quality of life, and costs for elderly patients admitted to the hospital with heart failure. The intervention was comprised of educating the patient and family, diet, early discharge planning, medications review, and intensive follow-up. Survival for 90 days without readmission was achieved in 91 of the 142 patients in the treatment group versus 75 of the 140 patients with conventional care (P = .09). There were 53 readmissions in the treatment group versus 94 in the control group (risk ratio, 0.56; P = .02). The number of readmissions for heart failure was reduced by 56.2% in the treatment group (54 versus 24 in the control group; P = .04). In the control group, 23 patients (16.4%) had more than 1 readmission versus 9 (6.3%) in the treatment group (risk ratio, 0.39; P = .01). In a subgroup of 126 patients, quality-of-life scores at 90 days improved more from baseline in the treatment group (P = .001). Because of the reduction in hospital admissions, the total cost of care was $460 less per patient in 1994 dollars in the treatment group, confirming strong dominance for the management strategy. West et al50 and Kornowski et al51 both studied a disease management strategy on the basis of outpatient

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care, rather than patient discharge. In a study in Israel, Kornowski et al51 analyzed outcome of 42 patients aged 78 ± 8 years with New York Heart Association heart failure classification III or IV who were examined at home weekly by local internists and a trained paramedical team. The year before, entry to the home-care program was compared with the 1st year of home surveillance. Functional status (ability to perform daily activities on a 1 to 4 scale) improved from 1.4 ± 0.9 to 2.3 ± 0.7 (P <.001). The total hospitalization rate fell from 3.2 ± 1.5 to 1.2 ± 1.6 hospitalizations per year, and length of stay from 26 ± 14 to 6 ± 7 days per year (P <.001 for both). Cardiovascular admissions fell from 2.9 ± 1.5 to 0.8 ± 1.1, and hospitalizations per year and days stay fell from 23 ± 13 to 4 ± 4 days per year (P <.001). This study showed improved outcome but at an uncertain trade-off in resource use between increased home visits and decreased hospitalizations for the intervention. West et al50 used a strategy of physician-led but nurse-managed, home-based heart failure management, not involving home visits. Nurses directed the implementation of guidelines for pharmacologic and dietary therapy by frequent telephone contact of 51 patients with heart failure for 138 ± 44 days. Compared with the period before enrollment, sodium intake fell by 38% (P = .0001), vasodilator doses increased (P = .01), and functional status and exercise capacity improved significantly (P = .01). Compared with the 6 months before enrollment, general medical and cardiology visits declined by 23% and 31%, respectively, (both P <.03) and emergency room visits for heart failure and for all causes declined 67% and 53%, respectively (both P <.001). Compared with 1 year before enrollment, hospitalization rates for heart failure and for all causes declined 87% and 74%, respectively (P = .001). Thus, this strategy improved clinical outcome for heart failure while reducing resource utilization, again suggesting strong dominance. Rich52 and Philbin53 have both reviewed disease management programs. Between 1983 and 1998, 16 studies (10 observational and 6 randomized trials) of multidisciplinary heart failure disease management programs were published in the English language literature. All studies reported reduced hospitalization, and several studies reported improved quality of life, functional capacity, patient satisfaction, and compliance. All studies that included a cost analysis found the disease management programs to be cost-effective. Rich52 suggested that current data are limited by generalizability to the more heterogeneous population of patients with heart failure and the feasibility of translating specific disease management programs into diverse practice environments and individualizing the programs for each patient. Although the impact of heart failure disease management programs on survival is also

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unknown, these programs appear to be cost-effective at reducing morbidity and improving quality of life in selected patients with heart failure.

Heart transplantation Heart transplantation remains sufficiently infrequent, with just 2290 in the United States in 1997, such that its overall impact on costs from a public health standpoint is small. The American Heart Association estimates the average cost of transplants at $253,200, with an annual follow-up cost of $21,200.2 Cardiac transplantation has not been subjected to rigorous cost-effectiveness analysis and certainly not a randomized trial, perhaps because of inadequate natural history data with which to compare patients for transplant. Although cardiac transplantation is certainly expensive, these patients would generally have a life expectancy of a few weeks to months in the absence of the transplant. In a somewhat preliminary, and now dated, study, Evans54 showed that overall cost-effectiveness of heart transplant was estimated at $44,300/year of life saved.

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9. 10. 11. 12.

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Current and future trends and policy implications Cost-effectiveness analysis in clinical medicine offers a powerful approach that may be used to help guide clinical decision-making and policy. To date, most costeffectiveness analyses in heart failure, either within or outside of clinical trials, have been simulations. As the methods and science of cost-effectiveness analyses improve, these analyses should increasingly be integrated into clinical practice.1 With the current changes in health care, accountability and cost are increasingly important, and we can expect to see more studies with these methods and greater incorporation of cost-effectiveness analysis into the medical care delivery system.

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