Cost-effectiveness analysis is a tool used to aid decisions about which medical care should be offered. It is a method of comparing the cost and effectiveness of two or more alternatives. Such comparisons are useful when one of the alternatives being considered is standard care, as this allows the decision maker to consider whether an innovation is better than the status quo.
The goal of cost-effectiveness analysis to determine if the value of an intervention justifies its cost. Cost-effectiveness involves more than determining cost, it also involves assignment of a value to the outcome.
To facilitate the comparison of different interventions, a standard method of cost-effectiveness analysis was developed by a task force of experts organized by the U.S. Public Health Service (PHS) (Gold, Siegel, Russell, & Weinstein, 1996).
The PHS Task Force made the following recommendations:
- Costs should be estimated from society's perspective. The effects of an intervention on all costs should be considered, not only the direct cost of the intervention, but its effect on healthcare expenditures, and costs incurred by patients.
- Costs and benefits should be discounted at a 3% annual rate, to reflect the lower economic value of an expense that is delayed and the higher value of a benefit that is realized sooner.
- When the effect of the intervention on costs and benefits is not fully realized during the study period, modeling should be used to estimate the costs and benefits over the patient's lifetime.
- The task force also described methods of estimating the statistical significance of cost-effectiveness findings. Note that when cost-effectiveness is a primary study hypothesis, variance in costs and outcomes, and their covariance will affect the sample size.
Cost-effectiveness analysis is not uniformly applied in the healthcare system. Decision makers often adopt new treatments without knowing if they are cost-effective. Even when cost-effectiveness has been studied, decision makers may not be able to interpret the data, or they may not agree with the results. Despite this limitation, cost-effectiveness is increasingly used to inform healthcare decision makers.
A second PHS task force revised these recommendations in 2016. A description of the major changes made by the second task force is found in the HERC Bulletin article "Major Changes to CEA Guidelines".
Cost-Effectiveness Studies of Two Interventions
When the choice is between an innovation and standard care, the analyst first applies the principle of strong dominance. Either the innovation or standard care may be preferred using this principal. Strong dominance favors a strategy that is both more effective and less costly. Strong dominance occurs only when the innovation is very good (it works better and saves cost) or very bad (its works worse and costs more).
When the more effective innovation is more costly, strong dominance provides no guidance. The decision maker must decide if the greater effectiveness justifies the cost of achieving it.
It is for this reason that the PHS Task Force recommended that cost-effectiveness studies use the Quality-Adjusted Life Year (QALY) as the outcome measure The QALY reflects both the quantity and the quality of life (Torrance & Feeny, 1989) . It is the most widespread method of measuring the value of providing a healthcare intervention.
Quality of life adjustments are based on patient or societal ratings of the quality of life associated with different health states. The ratings, also known as "preferences" or "utilities," are on a scale of zero (representing death) to one (representing perfect health). There are several methods for obtaining these ratings. The Time-Trade-Off method asks the individual doing the rating how much healthy life they are willing to give up to be cured of the condition. The Standard Gamble method asks them how much of a risk of death they are willing to incur in order to be cured of the condition. The Health Utilities Index (HUI) and EuroQoL are instruments used to gather information on quality of life. Methods for assessing economic quality of life are found in the HERC guidebook, Preference Measurement in Economic Analysis.
When the more effective innovation is also the more costly, the decision maker must decide if the greater effectiveness justifies the cost of achieving it. This is done by calculating an incremental cost-effectiveness ratio. This is difference in costs divided by the difference in outcomes. The ratio is the most useful when outcomes are expressed in Quality Adjusted Life Years (QALYs).
The cost-effectiveness ratio represents a measure of how efficiently the proposed intervention can produce an additional QALY. By using this standard method, the cost-effectiveness of alternative innovations may be compared, helping healthcare payers decide what changes they should adopt. The goal of the decision maker is to adopt all interventions that represent efficient ways of producing QALYs, and to disapprove of interventions with ratios that are too high.
The PHS Task Force did not recommend a standard of what constitutes a cost-effective intervention, that is, how low the cost-effectiveness ratio must be for an intervention to be adopted. When outcomes are measured in QALY's, the ratio may be compared to the ratios of other innovations (if standard methods have been employed). Knowledge of the incremental cost-effectiveness of interventions that have been approved can be helpful. It has been observed that the U.S. healthcare system adopts treatments that cost less than $50,000 per quality-adjusted life year (Owens, 1998). The criteria for judging cost-effectiveness are different in different healthcare systems and in different countries.
Comparison of Multiple Interventions
In some studies that compare multiple mutually exclusive interventions, an additional dominance principle is applied (Kamlet, 1992). As in the case when comparing two interventions, the analyst first applies the principle of strong dominance. Any of the competing interventions is ruled out if these is another intervention that is both more effective and less costly.
The analyst may then apply the principle of extended dominance (sometimes called "weak dominance"). The list of interventions, trimmed of strongly dominated alternatives, is ordered by effectiveness. Each intervention is compared to the next most effective alternative by calculating the incremental cost-effectiveness ratio. Extended dominance rules out any intervention that has an incremental cost-effectiveness ratio that is greater than that of a more effective intervention. The decision maker prefers the more effective intervention with a lower incremental cost-effectiveness ratio. By approving the more effective interventions, QALY's can be purchased more efficiently. This is made clear by the following example.
Example of Method for Multiple Interventions
Here is a hypothetical example of a comparison of multiple mutually exclusive interventions. The table gives cost in dollars and outcomes in QALY's for standard care and 5 innovations. In the first table, we can rule out intervention A. It is strongly dominated by intervention B, which costs less and yields better outcomes.
Next we apply the principle of extended-dominance. Interventions are listed in the order of effectiveness. The incremental cost-effectiveness ratio of each intervention is found by comparing it to the next most effective intervention.
|Intervention||Cost||Effectiveness||Incremental Cost-Effectiveness Ratio|
We can use extended dominance to rule out intervention C. It has an incremental cost-effectiveness ratio of $15,000 per QALY. In order to adopt C, the decision maker must have decided to adopt interventions with a cost-effectiveness ratio of $15,000 per QALY. If this is the case, then the decision maker would prefer intervention D. A greater number of QALY's may be obtained at a lower cost per QALY.
The final table indicates the interventions and their cost-effectiveness ratios after the dominance principles have been applied. It is now up to the decision maker to choose among the interventions by deciding how much a QALY is worth. If a QALY is not worth even $5,000 to the decision maker, then none of the innovations generate sufficient value to be adopted; if a QALY is worth more than $20,000 to the decision maker, then intervention E would be adopted.
Dominance principles can be also applied by ranking interventions in the order of their cost. The same finding will result. Dominance principles can be applied when outcomes are measured in units other than QALY's. This requires the assumption that measures reflect the most important effect of the treatment on health. For example, if a drug prevents death, and the side effects are known to be minor, outcomes could be measures in terms of life years of survival.
QALY's are the preferred measure of the outcomes, because they have the potential to allow the analysis to trade off mortality with quality of life, including treatment benefits and the side effects.
Guidelines for cost-effectiveness analysis specify that health services be assigned the opportunity cost based on a long-term, societal perspective. Cost-effectiveness analysts usually use reimbursements (the amount that the sponsor paid the provider) as a proxy for this opportunity cost. When the billed charge for a hospital stay is available, the cost-adjusted charge may be a better source, as it reflects variation in resource use that do not affect reimbursement. The cost adjusted charge is the amount billed for the hospital stay multiplied by the hospital wide ratio of cost-to-charges.
Using reimbursements as a proxy for costs is not possible for pharmaceuticals or newly developed interventions. There is no published schedule of reimbursements for individual drugs, and the analyst must use a drug price data base, such as Federal Supply Schedule or a private data source, and adjust to the price to reflect the best estimate of the cost to the sponsor, net of reimbursements.
Newly developed interventions are not found on reimbursement schedules, and the analyst must directly estimate their cost.
To find the cost of an intervention the analyst should include the cost of all activities needed to replicate the intervention in a typical healthcare setting. Costs incurred only to study the intervention should be excluded. When an activity involves both delivery of the intervention and research on its effect, the cost of any activity needed to deliver the intervention is included.
For example, consider the cost of a follow-up telephone call. The study participant is asked to return to a clinic to receive more intervention and to fill out a research assessment. The call is a cost of intervention. In order to replicate the intervention in the real world, the follow-up call will still be needed so that the patient will return to clinic to receive more intervention. A strict accounting of intervention cost would exclude any extra cost that was exclusively attributable to research-for example, any extra minutes spent describing the research assessment. This extra cost would not be needed to replicate the intervention in the real world. Another example is a laboratory test conducted to identify patients who are eligible for the intervention being studied. The test is a cost of the intervention because it would be needed to replicate the intervention elsewhere with same level of effectiveness.
Staff cost should be fully burdened with the cost of benefits, employer contributions to taxes, and non-productive time such as vacation and sick leave. This can be done in the calculation of the hourly cost of staff time. Total staff cost is divided by the number of applied (productive) hours, the time spent on activities that involve patient care. Hours on overhead activities such as vacations, sick leave, and professional training are excluded from the count of applied hours. For more details on measuring the cost of staff time, view Measuring Staff Activities.
When the cost is found in this manner, it represents the hourly cost of a worker engaged in productive activities. This method distributes the cost of vacation and sick leave across the productive hours of the employee. The analyst should consider if some of the cost of administrative duties, phone calls, and other activities should also accrue to the intervention; if so, they may be excluded from applied hours, and the cost distributed using this same method.
There may be costs arising from subcontracts with outside firms. Contract costs should be included if they relate to the intervention. Beyond the stated value of a contract, there will also be indirect costs relating to the bidding process and contractor oversight. These indirect costs should also be included. Clinical studies may involve a more intensive level of patient assessment than would occur under usual circumstances. For example, physicians may order more tests in a clinical study in order to detail patient outcomes as fully as possible in the final report. By contrast, in general practice there is typically pressure to minimize costs by performing only those tests that are medically indicated. A knowledgeable clinician can determine whether the intervention is being carried out differently from how it would occur in typical practice settings. If so, a discussion of cost-effectiveness could present additional figures for the cost of the intervention under typical circumstances.
Economic analyses often use data from two or more calendar years. Price inflation causes the value of a dollar to fall over time, and so the same dollar amount in two different years will usually represent different amounts of purchasing power. To counteract this problem, analysts typically adjust dollar figures to account for inflation. Figures that have not been adjusted for inflation are said to be in 'nominal dollars,' while those that have been adjusted are in 'real dollars.' This FAQ response describes how to adjust for inflation so that dollar values are expressed in terms of a single year's currency.
Inflation adjustments are made using price indices. Each index consists of numbers representing the price level in each year relative to a base year. Some indices have values that correspond to shorter periods as well, such as months or quarters. What distinguishes the indices is how the price levels are established.
To correct for inflation the analyst selects a base year. The goal is to adjust all dollar figures so that they are expressed in terms of dollars in that year. Often the base year is chosen to be the current year or the final year of study data. For example, suppose that you adjust for inflation using the Consumer Price Index for all urban consumers. To express a 2000 cost in 2005 dollars, simply multiply the cost by the 2005 index and divide by the 2000 index. The relevant index values are 113.4 for 2005 and 100.0 for 2000. If the cost were $20 in 2000, this would be the calculation:
$20.00 x (113.4/100.0) = $20.00 x 1.1342 = $22.68
Converting costs to 'real dollars' allows us to compare costs incurred in different years. For example, which is more expensive in 2005 dollars: A, which costs $20 in 1995, or item B, which costs $23 in 2000? Using the CPI for all urban consumers, item B is more expensive in real terms: it costs $26.09 in 2005 dollars, whereas item A costs only $25.63 in 2005 dollars.
One can convert costs to any year for which a price index exists. The base year does not affect which good is more expensive. If A is more costly than B in one base year, it will be more costly in terms of any other base year.
At HERC we often use the U.S. Consumer Price Index for all urban consumers. Values for this index tell what a market basket of consumer goods that cost $100 in 1983 would cost in the year in question. It quantifies the erosion of purchasing power by inflation. If most of the costs you are considering derive from staff, as is often the case for health care, then the general CPI is appropriate. The chain-weighted CPI is likely to be more accurate than the standard CPI, but it has only been figured since 2000.
We do not recommend using the Consumer Price Index for medical care. It analyzes changes in the cost of providing a day of stay and an outpatient visit. In recent years fewer but more expensive days of stay and visits are needed to treat an illness. This change is captured by the index without considering the change in productivity, overstating the increase in cost. Other faults of the medical care CPI are its reliance on list prices and the weighting of component medical care goods and services based on consumers out-of-pocket costs rather than overall health care expenditures. Berndt et al. (2000) provide a more through discussion of shortcomings in the medical care CPI and propose a fundamental reform of it.
The US Department of Labor Bureau of Labor Statistics and US Department of Commerce Bureau of Economic Analysis posts tables of index values for three common inflation indices used for health care research: the Consumer Price Index (CPI) for all urban consumers; the chain-weighted CPI for all urban consumers; and the Gross Domestic Product (GDP) implicit price deflator.
The Chain-Weighted All-Item CPI differs from the standard All-Item CPI in that the weights assigned to goods in the index change over time. The percentage figures reveal that the chain-weighted index yields slightly lower inflation rates than the standard CPI in the period 2000-2009. The GDP Implicit Deflator, also a common inflation measure, yields an inflation rate similar to those of the two CPI indices but not consistently higher or lower than either of them.
What About Discounting?
If you are comparing two interventions, each involving a series of expenditures over time, you need to consider the time value of money (the fact that a dollar spent today is a bigger expense than a dollar spent a year from now). This requires application of a discount rate. The Public Health Service Panel on Cost-Effectiveness in Medicine recommends a discount rate of 3% (Lipscomb et al., 1996). To find the incremental cost-effectiveness ratio, the discount rate should be applied to both real costs and to outcomes measured as quality-adjusted life years.
Discounting should not be confused with adjusting for inflation. Both are needed. The inflation adjustment reflects the change in purchasing power of currency. Discounting reflects the loss in value when there is a delay in obtaining an item of value. We discount expenses and health outcomes if there is a delay in realizing them.
Discounting reflects the loss in economic value that occurs when there is a delay in realizing a benefit or incurring a cost. Cost-effectiveness analysis incorporates the economic fact that costs and benefits that are deferred have lower value than those that are realized immediately.
Discounting should not be confused with adjustment for inflation. All costs should be expressed in real terms (adjusted for inflation) before discounting is done.
Both cost and outcomes should be discounted. Failure to discount outcomes as well as costs can result in a paradox described by Keeler and Cretin (1983). If costs are discounted, and outcomes are not, the cost-effectiveness of an intervention can always be improved by delaying its implementation indefinitely.
Costs and outcomes enter into the cost-effectiveness analysis expressed in their present discounted value. Most analysts discount on an annual basis. Expenses incurred in the first year are not discounted. If a discount rate of 3% is chosen, then expenses incurred in the second year are discounted by 3%, that is, they are divided 1.03. Third year expenses are divided by (1.03)2. Each successive year is discounted by an additional 3%.
The present value (PV) of costs incurred by a subject from the first year of the study (t=1) until the study ends (t=n) is thus:
Present Value of Cost
Note that Ct represents the cost incurred in year t, and that i is the discount rate, e.g., .03. The present value of outcomes is calculated in the same manner.
What is the Appropriate Rate of Discounting?
A discount rate of 3% was recommended by the Public Health Service Panel on Cost-Effectiveness in Medicine (Lipscomb, et al, 1996). The Panel recommended that an alternative analysis be done with a 5% discount rate, so that results are comparable to those studies that use this higher rate.
Simplification for Costs and Benefits Realized at a Constant Rate.
When either cost or outcomes are realized at a constant rate, a formula may be used to find their discounted present value.* It can be used for models that assume that annual healthcare cost are incurred at a constant rate. It can also be used to find discounted life-years of remaining survival. The formula incorporates a discount factor (r):
which includes the discount rate (i). Other variables in the formula are the annual rate at which costs are incurred (a) and the number of years over which they will be incurred (n).
Present Value of Cost
The formula can also be applied to outcomes. If it is assumed the quality of life of the remaining years of survival is constant, then (a) represents the quality of life adjustment. If the outcomes are measured in life years, this factor takes a value of one, and drops out of the equation.
* This is the formula for a finite geometric series. A finite geometric series consists of a series of terms. The ratio of each term to its predecessor is a fixed constant (r):
The value of a geometric series (Sn) may be determined by subtracting r(Sn) from both sides of the equation, and applying simple algebra to yield:
If you are comparing two interventions, each involving a series of expenditures over time, you need to consider the time value of money (the fact that a dollar spent today is a bigger expense than a dollar spent a year from now). Benefits and cost should be discounted at the same rate. The Public Health Service Panel on Cost-Effectiveness in Medicine recommends a discount rate of 3%. View the section, "Discounting Healthcare Costs".
Benefits must be discounted for the same reason as costs are discounted. A benefit realized today has greater value than a benefit realized a year from today. Failure to discount benefits, or to discount costs and benefits at a lower rate, results in the Keeler-Cretin paradox.
Here is a simplified version of the Keeler-Cretin argument. Consider an intervention that costs $100,000 and saves 10 lives. If you chose to wait, and fund the intervention 10 years from now, the cost would be discounted, that is, the net present value would be less than $100,000, but it would still save 10 lives. The "waiting" strategy would be more cost-effective. If you waited 20 years, the intervention would even be less costly, and would still save 10 lives. You would always prefer to defer to the future, and you'd never do the intervention. The paradox is described more fully in the Gold, 1996.
There are controversial questions in discounting health consequences (e.g., QALYs). Research analysts interested in this topic should consult the articles listed in the References section.
To compare the value of one treatment with another, you need an outcome measure that works across different health states. This rules out disease-specific quality of life measures as they only reflect a specific disease or illness.
In addition, the outcome measure must also work as a measure of preference. Preference measures not only measure health status, but they also measure how the individual values the current health state. The valuation of the current health state usually covers the spectrum from full health to death.
To date, the quality adjusted life year (QALY) model is the preferred metric for estimating the health effects (Gold et al., 1996). QALYs are estimated by multiplying each life year gained with an intervention by a quality-weighting factor that reflects the individual's quality of life in the health state for that year. Utilities, measured on a scale from zero (death or the worst health imaginable) to one (perfect health), can be used as quality-weighting factors. See Gold et al., 1996 for details.
There are different ways to find quality weights. The easiest is to use published reports and league tables. Besides Medline, a great resource for this is the Tufts Cost-Effectiveness Analysis Registry.
If existing utility weights do not meet your needs, you may need to collect weights. In doing so, sampling issues should be considered carefully (see Gold et al., 1996). The estimation of the quality weights for a given period (i) and treatment (k) requires the successful completion of two tasks:
- Measuring the impact of an intervention on the distribution of health states. This task requires that the health states influenced by the treatment are completely characterized.
- Assessing the preferences (utilities) for these alternative health states.
This two-step estimation process can be done with different methods.
Indirect utility assessment
Direct utility assessment
- Rating Scales
- Standard gamble (SG)
- Time tradeoff (TTO)
A key distinction between the methods is the how they handle risk. The Standard Gamble makes the respondent consider the risk of death. The Time Tradeoff method asks the person to consider a tradeoff with years of life. Some say that the TTO is cognitively easier to understand than SG, although the jury is still out on this. Usually the SG and TTO methods require interview administration, although a lot work is being done to use computer and Internet administration. Given the logisitical complexities, many people turn to the rating scales. The rating scales, however, do not require people to consider risk. There is a controversy over the importance of including risk (See Gold et al, 1996, p 118).
It is also important to note that these methods usually yield different utility weights. This has led some people to use multiple methods.
The "Veterans RAND 36-Item Health Survey" (VR-36 and formerly the Veterans SF-36) was developed from the original RAND version of the 36-Item Health Survey version 1.0 (also known as MOS SF-36) at the RAND Corporation as part of the Medical Outcomes Study.1 The VR-12 ("Veterans RAND 12-Item Health Survey," formerly the Veterans SF-12) was derived from the VR-36.1 While the names of these assessment tools have changed, the content of the instruments has not.
There is no cost to use the VR-36 and VR-12. However, so that the developers can monitor the use of these instruments, researchers must obtain permission by requesting to use the instrument in a letter on institutional letterhead to Dr. Lewis Kazis. The letter should state that the requestor agrees to the terms and conditions given by the RAND Corporation and indicate that the user plans to give appropriate acknowledgements for the VR-12 and/or VR-36.2 An abstract of the project should be included with the request.
Is any one assessment tool better than the others?
VR-36/VR-12 vs. SF-36/SF-12
The VR instruments use five-point response choices for seven items in the VR-36 and four items in the VR-12. Response choices that were originally dichotomous (a two-point yes/no choice) are now five-point response choices: "no, none of the time", "yes, a little of the time", "yes, some of the time", "yes, most of the time" and "yes, all of the time".3 These answers then contribute to the scales for role limitations due to physical and emotional problems. Expanding these scales in the VR instruments has resulted in a reduction of floor and ceiling effects, with important gains in the scales’ distributional properties and increases in reliability and validity.3 The VR-36 and VR-12 also include two additional items to assess physical and emotional health change, in contrast to the single general change item in the SF-36.3
VR12/SF-12 vs. VR36/SF-36
The SF-12 is a shorter alternative to the SF-36 but it reproduces the eight-scale profile with fewer levels than the SF-36 and produces less precise scores.4 Because confidence intervals for group averages in health scores are largely determined by sample size, these differences are not as important for large group studies. The SF-12 improves efficiency and lowers cost for both profiles and summary scales, and is most appropriate for use in large samples of general and specific populations as well as large longitudinal studies of health outcomes. Selim and colleagues have also developed the VR-6D algorithm which computes health state utilities for the VR-12. Utilities or preference-based scores reflect values on health states and are essential for cost-effectiveness analysis.
For a list of studies in which the VR-36 and VR-12 was used for measuring health-related quality of life, please refer to Iqbal 2009.
There are some limitations in using the assessment tools. Researchers interested in this topic should consult Kazis 2004a, Kazis 2004b, Keller 1999, Rose 2008, Selim 2006, and Wilson 2000.
The Quality Enhancement Research Initiative (QUERI) has integrated economic analyses into implementation research aimed to improve the quality of VA care. A QUERI economic analysis measures costs and often outcomes of health care interventions, and places this information in context.
HERC has developed guidelines for economic analyses within QUERI projects.
Types of analysis
There are several common forms of QUERI cost analysis:
- Cost-identification determines the cost of an intervention
- Cost-effectiveness analysis (CEA) calculates the dollars that must be spent to gain an additional quality-adjusted life year (QALY) or other natural outcome from the intervention
- Budget impact analysis (BIA), also called a business case analysis, reports the short-term costs to VA of adopting a proposed intervention
- Implementation - estimation of the costs of implementation intervention strategy used to enhance the uptake of an effective program or practice
Intervention costs are estimated in many ways. For studies that change the organization or delivery of care, micro-cost methods are usually employed to estimate the cost of providing the intervention. The analysis should determine what types of care will be affected by the intervention and how this will affect cost.
Cost-effectiveness analysis (CEA)
Standard CEA estimates costs from society’s perspective. Thus, it considers not only the direct cost of an intervention and its effect on subsequent health care utilization, but also costs incurred by other health care systems, and by patients and their families. Standard CEA employs a lifetime perspective. Long-term costs and benefits are included but are discounted to reflect the decline in economic value that results from delay. CEA should include sensitivity analyses, which evaluate the uncertainty on study findings
Budget impact analysis (BIA)
A BIA considers costs from the perspective of the payer, comparing the costs of two or more interventions, over the short-term (e.g. 1-5 years). In such cases discounting of future costs and benefits is unnecessary and only variable costs are taken into account. If a long-run horizon is chosen then discounting could apply and fixed costs would be taken into account. The best guide is to use the time horizon of greatest value to the managers who will use the results. The International Society for Pharmacoeconomics and Outcomes Research (ISPOR) has issued guidance on BIA that should be considered.
BIAs often consider the cost of the intervention, cost of implementation and down steam health care costs that changed as a result of the intervention.
In all of the above analyses, inclusion or exclusion of the costs of implementation should be described in the analysis plan. These costs must be specifically differentiated from other costs to understand the economic implications for implementation strategies.
The report of an economic evaluation must document data sources, methods, and assumptions.
Cyber-seminars by VA researchers on topics related to economic analysis within QUERI may be found on the HSR&D Cyber Seminar web site.
See the guidelines for references to many journal articles and book chapters on cost-effectiveness analysis and budget impact analysis.
The Institute of Medicine estimated that $210 billion worth of unnecessary services were provided in the U.S. health care system in 2009 (United States Institute of Medicine, 2012).
The most recent effort to address this problem is being coordinated by the American Board of Internal Medicine Foundation and Consumer Reports. The "Choosing Wisely" initiative enlisted 9 medical specialty societies, each of which identified five examples of care that is of uncertain value (Cassel &. Guest, 2012). Another 28 societies are now developing their own lists as part of this initiative.
Previous efforts have also identified ineffective and inefficient services. The Institute of Medicine listed infective treatments widely used in the U.S. health care system in 2008 (United States Institute of Medicine, 2008). The Rand Corporation developed its own list of inappropriate services, including hospitalization, surgery, and pharmaceutical treatments (Schuster, McGlynn, & Brook, 2005). Researchers from the New England Healthcare Institute (NEHI) identified 460 studies published in the peer reviewed literature between 1998 and March of 2006 that identified waste or inefficiency (New England Healthcare Institute, 2008). A review of the Tufts Cost-Effectiveness Registry identified low-value services that might be excluded from a value-based insurance coverage (Neumann, Auerbach, Cohen, & Greenberg, 2010). A national panel of health care organizations established national priorities for the U.S. health care system, including a specific list of inappropriate services (National Priorities Partnership, 2008). An American College of Physicians workgroup identified 37 examples of clinical situations in which diagnostic and screening tests do not yield very high-value (Qaseem et al., 2012).
These analyses have documented the presence of inefficiency in the U.S. health care system, but they have some limitations. They represent lists of individual studies, not the synthesis of literature on a topic. As a result, there may be countervailing evidence that a listed service is effective or cost-effective. Not all of these efforts describe the strength of the evidence. It is thus not possible to tell which findings are based on the strongest evidence. There is also a need to rank these services by total cost to set a priority for action.
Efforts to address the problem of existing care that is not cost-effective have been called "disinvestment programs." Elshaug proposed a program for the Australian health plan and included criteria for identifying and prioritizing candidate interventions (Elshaug et al., 2009). Similar proposals have made for NICE to identify candidate therapies for disinvestment by the British National Health Service (Pearson & Littlejohns, 2007). NICE has developed a list of inappropriate therapies.
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