Abstract Background Cost-effectiveness analysis can guide policymakers in resource allocation decisions. It assesses whether the health gains offered by an intervention are large enough relative to ...any additional costs to warrant adoption. When there are constraints on the health care system’s budget or ability to increase expenditures, additional costs imposed by interventions have an “opportunity cost” in terms of the health foregone because other interventions cannot be provided. Cost-effectiveness thresholds (CETs) are typically used to assess whether an intervention is worthwhile and should reflect health opportunity cost. Nevertheless, CETs used by some decision makers—such as the World Health Organization that suggested CETs of 1 to 3 times the gross domestic product (GDP) per capita—do not. Objectives To estimate CETs based on opportunity cost for a wide range of countries. Methods We estimated CETs based on recent empirical estimates of opportunity cost (from the English National Health Service), estimates of the relationship between country GDP per capita and the value of a statistical life, and a series of explicit assumptions. Results CETs for Malawi (the country with the lowest income in the world), Cambodia (with borderline low/low-middle income), El Salvador (with borderline low-middle/upper-middle income), and Kazakhstan (with borderline high-middle/high income) were estimated to be $3 to $116 (1%–51% GDP per capita), $44 to $518 (4%–51%), $422 to $1967 (11%–51%), and $4485 to $8018 (32%–59%), respectively. Conclusions To date, opportunity-cost-based CETs for low-/middle-income countries have not been available. Although uncertainty exists in the underlying assumptions, these estimates can provide a useful input to inform resource allocation decisions and suggest that routinely used CETs have been too high.
ObjectivesTo provide national estimates of the number and clinical and economic burden of medication errors in the National Health Service (NHS) in England.MethodsWe used UK-based prevalence of ...medication errors (in prescribing, dispensing, administration and monitoring) in primary care, secondary care and care home settings, and associated healthcare resource use, to estimate annual number and burden of errors to the NHS. Burden (healthcare resource use and deaths) was estimated from harm associated with avoidable adverse drug events (ADEs).ResultsWe estimated that 237 million medication errors occur at some point in the medication process in England annually, 38.4% occurring in primary care; 72% have little/no potential for harm and 66 million are potentially clinically significant. Prescribing in primary care accounts for 34% of all potentially clinically significant errors. Definitely avoidable ADEs are estimated to cost the NHS £98 462 582 per year, consuming 181 626 bed-days, and causing/contributing to 1708 deaths. This comprises primary care ADEs leading to hospital admission (£83.7 million; causing 627 deaths), and secondary care ADEs leading to longer hospital stay (£14.8 million; causing or contributing to 1081 deaths).ConclusionsUbiquitous medicines use in health care leads unsurprisingly to high numbers of medication errors, although most are not clinically important. There is significant uncertainty around estimates due to the assumption that avoidable ADEs correspond to medication errors, data quality, and lack of data around longer-term impacts of errors. Data linkage between errors and patient outcomes is essential to progress understanding in this area.
Abstract Background Policymakers in high-, low-, and middle-income countries alike face challenging choices about resource allocation in health. Economic evaluation can be useful in providing ...decision makers with the best evidence of the anticipated benefits of new investments, as well as their expected opportunity costs—the benefits forgone of the options not chosen. To guide the decisions of health systems effectively, it is important that the methods of economic evaluation are founded on clear principles, are applied systematically, and are appropriate to the decision problems they seek to inform. Methods The Bill and Melinda Gates Foundation, a major funder of economic evaluations of health technologies in low- and middle-income countries (LMICs), commissioned a “reference case” through the International Decision Support Initiative (iDSI) to guide future evaluations, and improve both the consistency and usefulness to decision makers. Results The iDSI Reference Case draws on previous insights from the World Health Organization, the US Panel on Cost-Effectiveness in Health Care, and the UK National Institute for Health and Care Excellence. Comprising 11 key principles, each accompanied by methodological specifications and reporting standards, the iDSI Reference Case also serves as a means of identifying priorities for methods research, and can be used as a framework for capacity building and technical assistance in LMICs. Conclusions The iDSI Reference Case is an aid to thought, not a substitute for it, and should not be followed slavishly without regard to context, culture, or history. This article presents the iDSI Reference Case and discusses the rationale, approach, components, and application in LMICs.
Abstract A model's purpose is to inform medical decisions and health care resource allocation. Modelers employ quantitative methods to structure the clinical, epidemiological, and economic evidence ...base and gain qualitative insight to assist decision makers in making better decisions. From a policy perspective, the value of a model-based analysis lies not simply in its ability to generate a precise point estimate for a specific outcome but also in the systematic examination and responsible reporting of uncertainty surrounding this outcome and the ultimate decision being addressed. Different concepts relating to uncertainty in decision modeling are explored. Stochastic (first-order) uncertainty is distinguished from both parameter (second-order) uncertainty and from heterogeneity, with structural uncertainty relating to the model itself forming another level of uncertainty to consider. The article argues that the estimation of point estimates and uncertainty in parameters is part of a single process and explores the link between parameter uncertainty through to decision uncertainty and the relationship to value of information analysis. The article also makes extensive recommendations around the reporting of uncertainty, in terms of both deterministic sensitivity analysis techniques and probabilistic methods. Expected value of perfect information is argued to be the most appropriate presentational technique, alongside cost-effectiveness acceptability curves, for representing decision uncertainty from probabilistic analysis.
Cost-effectiveness analysis involves the comparison of the incremental cost-effectiveness ratio of a new technology, which is more costly than existing alternatives, with the cost-effectiveness ...threshold. This indicates whether or not the health expected to be gained from its use exceeds the health expected to be lost elsewhere as other health-care activities are displaced. The threshold therefore represents the additional cost that has to be imposed on the system to forgo 1 quality-adjusted life-year (QALY) of health through displacement. There are no empirical estimates of the cost-effectiveness threshold used by the National Institute for Health and Care Excellence.
(1) To provide a conceptual framework to define the cost-effectiveness threshold and to provide the basis for its empirical estimation. (2) Using programme budgeting data for the English NHS, to estimate the relationship between changes in overall NHS expenditure and changes in mortality. (3) To extend this mortality measure of the health effects of a change in expenditure to life-years and to QALYs by estimating the quality-of-life (QoL) associated with effects on years of life and the additional direct impact on QoL itself. (4) To present the best estimate of the cost-effectiveness threshold for policy purposes.
Earlier econometric analysis estimated the relationship between differences in primary care trust (PCT) spending, across programme budget categories (PBCs), and associated disease-specific mortality. This research is extended in several ways including estimating the impact of marginal increases or decreases in overall NHS expenditure on spending in each of the 23 PBCs. Further stages of work link the econometrics to broader health effects in terms of QALYs.
The most relevant 'central' threshold is estimated to be £12,936 per QALY (2008 expenditure, 2008-10 mortality). Uncertainty analysis indicates that the probability that the threshold is < £20,000 per QALY is 0.89 and the probability that it is < £30,000 per QALY is 0.97. Additional 'structural' uncertainty suggests, on balance, that the central or best estimate is, if anything, likely to be an overestimate. The health effects of changes in expenditure are greater when PCTs are under more financial pressure and are more likely to be disinvesting than investing. This indicates that the central estimate of the threshold is likely to be an overestimate for all technologies which impose net costs on the NHS and the appropriate threshold to apply should be lower for technologies which have a greater impact on NHS costs.
The central estimate is based on identifying a preferred analysis at each stage based on the analysis that made the best use of available information, whether or not the assumptions required appeared more reasonable than the other alternatives available, and which provided a more complete picture of the likely health effects of a change in expenditure. However, the limitation of currently available data means that there is substantial uncertainty associated with the estimate of the overall threshold.
The methods go some way to providing an empirical estimate of the scale of opportunity costs the NHS faces when considering whether or not the health benefits associated with new technologies are greater than the health that is likely to be lost elsewhere in the NHS. Priorities for future research include estimating the threshold for subsequent waves of expenditure and outcome data, for example by utilising expenditure and outcomes available at the level of Clinical Commissioning Groups as well as additional data collected on QoL and updated estimates of incidence (by age and gender) and duration of disease. Nonetheless, the study also starts to make the other NHS patients, who ultimately bear the opportunity costs of such decisions, less abstract and more 'known' in social decisions.
The National Institute for Health Research-Medical Research Council Methodology Research Programme.
The WHO HIV Treatment Guidelines suggest routine viral-load monitoring can be used to differentiate antiretroviral therapy (ART) delivery and reduce the frequency of clinic visits for patients stable ...on ART. This recommendation was informed by economic analysis that showed the approach is very likely to be cost-effective, even in the most resource constrained of settings. The health benefits were shown to be modest but the costs of introducing and scaling up viral load monitoring can be offset by anticipated reductions in the costs of clinic visits, due to these being less frequent for many patients.
The cost-effectiveness of introducing viral-load informed differentiated care depends upon whether cost reductions are possible if the number of clinic visits is reduced and/or how freed clinic capacity is used for alternative priorities. Where freed resources, either physical or financial, generate large health gains (e.g. if committed to patients failing ART or to other high value health care interventions), the benefits of differentiated care are expected to be high; if however these freed physical resources are already under-utilized or financial resources are used less efficiently and would not be put to as beneficial an alternative use, the policy may not be cost-effective. The implication is that the use of conventional unit costs to value resources may not well reflect the latter's value in contributing to health improvement. Analyses intended to inform resource allocated decisions in a number of settings may therefore have to be interpreted with due consideration to local context. In this paper we present methods of how economic analyses can reflect the real value of health care resources rather than simply applying their unit costs. The analyses informing the WHO Guidelines are re-estimated by implementing scenarios using this framework, informing how differentiated care can be prioritized to generate greatest gains in population health.
The findings have important implications for how economic analyses should be undertaken and reported in HIV and other disease areas. Results provide guidance on conditions under which viral load informed differentiated care will more likely prove to be cost effective when implemented.
IMPORTANCE: Since publication of the report by the Panel on Cost-Effectiveness in Health and Medicine in 1996, researchers have advanced the methods of cost-effectiveness analysis, and policy makers ...have experimented with its application. The need to deliver health care efficiently and the importance of using analytic techniques to understand the clinical and economic consequences of strategies to improve health have increased in recent years. OBJECTIVE: To review the state of the field and provide recommendations to improve the quality of cost-effectiveness analyses. The intended audiences include researchers, government policy makers, public health officials, health care administrators, payers, businesses, clinicians, patients, and consumers. DESIGN: In 2012, the Second Panel on Cost-Effectiveness in Health and Medicine was formed and included 2 co-chairs, 13 members, and 3 additional members of a leadership group. These members were selected on the basis of their experience in the field to provide broad expertise in the design, conduct, and use of cost-effectiveness analyses. Over the next 3.5 years, the panel developed recommendations by consensus. These recommendations were then reviewed by invited external reviewers and through a public posting process. FINDINGS: The concept of a “reference case” and a set of standard methodological practices that all cost-effectiveness analyses should follow to improve quality and comparability are recommended. All cost-effectiveness analyses should report 2 reference case analyses: one based on a health care sector perspective and another based on a societal perspective. The use of an “impact inventory,” which is a structured table that contains consequences (both inside and outside the formal health care sector), intended to clarify the scope and boundaries of the 2 reference case analyses is also recommended. This special communication reviews these recommendations and others concerning the estimation of the consequences of interventions, the valuation of health outcomes, and the reporting of cost-effectiveness analyses. CONCLUSIONS AND RELEVANCE: The Second Panel reviewed the current status of the field of cost-effectiveness analysis and developed a new set of recommendations. Major changes include the recommendation to perform analyses from 2 reference case perspectives and to provide an impact inventory to clarify included consequences.
The current recommendation of using transrectal ultrasound-guided biopsy (TRUSB) to diagnose prostate cancer misses clinically significant (CS) cancers. More sensitive biopsies (eg, template prostate ...mapping biopsy TPMB) are too resource intensive for routine use, and there is little evidence on multiparametric magnetic resonance imaging (MPMRI).
To identify the most effective and cost-effective way of using these tests to detect CS prostate cancer.
Cost-effectiveness modelling of health outcomes and costs of men referred to secondary care with a suspicion of prostate cancer prior to any biopsy in the UK National Health Service using information from the diagnostic Prostate MR Imaging Study (PROMIS).
Combinations of MPMRI, TRUSB, and TPMB, using different definitions and diagnostic cut-offs for CS cancer.
Strategies that detect the most CS cancers given testing costs, and incremental cost-effectiveness ratios (ICERs) in quality-adjusted life years (QALYs) given long-term costs.
The use of MPMRI first and then up to two MRI-targeted TRUSBs detects more CS cancers per pound spent than a strategy using TRUSB first (sensitivity = 0.95 95% confidence interval {CI} 0.92–0.98 vs 0.91 95% CI 0.86–0.94) and is cost effective (ICER = £7,076 €8350/QALY gained). The limitations stem from the evidence base in the accuracy of MRI-targeted biopsy and the long-term outcomes of men with CS prostate cancer.
An MPMRI-first strategy is effective and cost effective for the diagnosis of CS prostate cancer. These findings are sensitive to the test costs, sensitivity of MRI-targeted TRUSB, and long-term outcomes of men with cancer, which warrant more empirical research. This analysis can inform the development of clinical guidelines.
We found that, under certain assumptions, the use of multiparametric magnetic resonance imaging first and then up to two transrectal ultrasound-guided biopsy is better than the current clinical standard and is good value for money.
The use of multiparametric magnetic resonance imaging before transrectal ultrasound-guided biopsy can detect more clinically significant prostate cancer and be cost effective compared with the use of imaging post-biopsy.
The United States is one of the few high-income countries not to apply economic evaluation routinely to health care decision making on a national level, yet it excels at spending least efficiently on ...health care. In the interest of continuing to develop new solutions to curb spending on health care and reduce waste in the United States, perhaps now is an important moment to reconsider the benefits of economic evaluation and the barriers that must be overcome to have it emerge as a solution for health care institutions and the patients they serve. This article offers several distinct considerations to make economic evaluation methods (such as cost-effectiveness analysis) an effective component of value-based decision making in the United States. These considerations include overcoming the barriers presented by opportunity costs, spending on health care services versus biomedical technologies, phasing out low-value care, using value of information to prioritize resources, and determining what to do with the quality-adjusted life-year. These issues need to be addressed to achieve a collective purpose for economic evaluation at state and national levels.
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