Cost-Effectiveness Analysis

Beth Woods B, Paul Revill, Mark Sculpher, Karl Claxton 
Value in Health. 2016;19(8):929-935.

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.

OBJECTIVE
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.

Clementine Nordon, Helene Karcher, Rolf H. H. Groenwold, Mikkel Z. Ankarfeldt, Franz Pichler, Helene Chevrou-Severac, Michel Rossignol, Adeline Abbe, Lucien Abenhaim. 
Value in Health. 2016;19(1):75-81.

BACKGROUND
The concept of the "efficacy-effectiveness gap" (EEG) has started to challenge confidence in decisions made for drugs when based on randomized controlled trials alone. Launched by the Innovative Medicines Initiative, the GetReal project aims to improve understanding of how to reconcile evidence to support efficacy and effectiveness and at proposing operational solutions.

OBJECTIVE
The objectives of the present narrative review were 1) to understand the historical background in which the concept of the EEG has emerged and 2) to describe the conceptualization of EEG.

METHODS
A focused literature review was conducted across the gray literature and articles published in English reporting insights on the EEG concept. The identification of different "paradigms" was performed by simple inductive analysis of the documents' content.

RESULTS
The literature on the EEG falls into three major paradigms, in which EEG is related to 1) real-life characteristics of the health care system; 2) the method used to measure the drug's effect; and 3) a complex interaction between the drug's biological effect and contextual factors.

CONCLUSIONS
The third paradigm provides an opportunity to look beyond any dichotomy between "standardized" versus "real-life" characteristics of the health care system and study designs. Namely, future research will determine whether the identification of these contextual factors can help to best design randomized controlled trials that provide better estimates of drugs' effectiveness.

Richard Cookson, Andrew J. Mirelman, Susan Griffin, Miqdad Asaria, Bryony Dawkins, Ole Frithjof Norheim, Stéphane Verguet, Anthony J. Culyer
Value in Health. 2017;20(2):206-212.

ABSTRACT
This articles serves as a guide to using cost-effectiveness analysis (CEA) to address health equity concerns. We first introduce the “equity impact plane,” a tool for considering trade-offs between improving total health—the objective underpinning conventional CEA—and equity objectives, such as reducing social inequality in health or prioritizing the severely ill. Improving total health may clash with reducing social inequality in health, for example, when effective delivery of services to disadvantaged communities requires additional costs. Who gains and who loses from a cost-increasing health program depends on differences among people in terms of health risks, uptake, quality, adherence, capacity to benefit, and—crucially—who bears the opportunity costs of diverting scarce resources from other uses. We describe two main ways of using CEA to address health equity concerns: 1) equity impact analysis, which quantifies the distribution of costs and effects by equity-relevant variables, such as socioeconomic status, location, ethnicity, sex, and severity of illness; and 2) equity trade-off analysis, which quantifies trade-offs between improving total health and other equity objectives. One way to analyze equity trade-offs is to count the cost of fairer but less cost-effective options in terms of health forgone. Another method is to explore how much concern for equity is required to choose fairer but less cost-effective options using equity weights or parameters. We hope this article will help the health technology assessment community navigate the practical options now available for conducting equity-informative CEA that gives policymakers a better understanding of equity impacts and trade-offs.

Alexis P. Chidi, Cindy L. Bryce, Michael J. Fine, Douglas P. Landsittel, Larissa Myaskovsky, Shari S. Rogal, Galen E. Switzer, Allan Tsung, Kenneth J. Smith 
Value in Health. 2016;19(4):326-334.

BACKGROUND
Interferon-free hepatitis C treatment regimens are effective but very costly. The cost-effectiveness, budget, and public health impacts of current Medicaid treatment policies restricting treatment to patients with advanced disease remain unknown.

OBJECTIVES
To evaluate the cost-effectiveness of current Medicaid policies restricting hepatitis C treatment to patients with advanced disease compared with a strategy providing unrestricted access to hepatitis C treatment, assess the budget and public health impact of each strategy, and estimate the feasibility and long-term effects of increased access to treatment for patients with hepatitis C.

METHODS
Using a Markov model, we compared two strategies for 45- to 55-year-old Medicaid beneficiaries: 1) Current Practice—only advanced disease is treated before Medicare eligibility and 2) Full Access—both early-stage and advanced disease are treated before Medicare eligibility. Patients could develop progressive fibrosis, cirrhosis, or hepatocellular carcinoma, undergo transplantation, or die each year. Morbidity was reduced after successful treatment. We calculated the incremental cost-effectiveness ratio and compared the costs and public health effects of each strategy from the perspective of Medicare alone as well as the Centers for Medicare & Medicaid Services perspective. We varied model inputs in one-way and probabilistic sensitivity analyses.

RESULTS
Full Access was less costly and more effective than Current Practice for all cohorts and perspectives, with differences in cost ranging from 5,369 to 11,960 and in effectiveness from 0.82 to 3.01 quality-adjusted life-years. In a probabilistic sensitivity analysis, Full Access was cost saving in 93% of model iterations. Compared with Current Practice, Full Access averted 5,994 hepatocellular carcinoma cases and 121 liver transplants per 100,000 patients.

CONCLUSIONS
Current Medicaid policies restricting hepatitis C treatment to patients with advanced disease are more costly and less effective than unrestricted, full-access strategies. Collaboration between state and federal payers may be needed to realize the full public health impact of recent innovations in hepatitis C treatment.

Julia R. Trosman, Christine B. Weldon, Michael P. Douglas, Patricia A. Deverka, John B. Watkins, Kathryn A. Phillips
Value in Health. 2017;20(1):40-46.

BACKGROUND
New payment and care organization approaches, such as those of accountable care organizations (ACOs), are reshaping accountability and shifting risk, as well as decision making, from payers to providers, within the Triple Aim context of health reform. The Triple Aim calls for improving experience of care, improving health of populations, and reducing health care costs.

OBJECTIVE
To understand how the transition to the ACO model impacts decision making on adoption and use of innovative technologies in the era of accelerating scientific advancement of personalized medicine and other innovations.

METHODS
We interviewed representatives from 10 private payers and 6 provider institutions involved in implementing the ACO model (i.e., ACOs) to understand changes, challenges, and facilitators of decision making on medical innovations, including personalized medicine. We used the framework approach of qualitative research for study design and thematic analysis.

RESULTS
We found that representatives from the participating payer companies and ACOs perceive similar challenges to ACOs’ decision making in terms of achieving a balance between the components of the Triple Aim—improving care experience, improving population health, and reducing costs. The challenges include the prevalence of cost over care quality considerations in ACOs’ decisions and ACOs’ insufficient analytical and technology assessment capacity to evaluate complex innovations such as personalized medicine. Decision-making facilitators included increased competition across ACOs and patients’ interest in personalized medicine.

CONCLUSIONS
As new payment models evolve, payers, ACOs, and other stakeholders should address challenges and leverage opportunities to arm ACOs with robust, consistent, rigorous, and transparent approaches to decision making on medical innovations.

Pieter T. de Boer, Pascal Crepey, Richard Pitman, Bérengère Macabeo, Ayman Chit, Maarten J. Postma
Value in Health. 2016;19(8):964-975.

BACKGROUND
Designed to overcome influenza B mismatch, new quadrivalent influenza vaccines (QIVs) contain one additional B strain compared with trivalent influenza vaccines (TIVs).

OBJECTIVE
To examine the expected public health impact, budget impact, and incremental cost-effectiveness of QIV versus TIV in the United States.

METHODS
A dynamic transmission model was used to predict the annual incidence of influenza over the 20-year-period of 2014 to 2034 under either a TIV program or a QIV program. A decision tree model was interfaced with the transmission model to estimate the public health impact and the cost-effectiveness of replacing TIV with QIV from a societal perspective. Our models were informed by published data from the United States on influenza complication probabilities and relevant costs. The incremental vaccine price of QIV as compared with that of TIV was set at US $5.40 per dose.

RESULTS
Over the next 20 years, replacing TIV with QIV may reduce the number of influenza B cases by 27.2% (16.0 million cases), resulting in the prevention of 137,600 hospitalizations and 16,100 deaths and a gain of 212,000 quality-adjusted life-years (QALYs). The net societal budget impact would be US $5.8 billion and the incremental cost-effectiveness ratio US $27,411/QALY gained. In the probabilistic sensitivity analysis, 100% and 96.5% of the simulations fell below US $100,000/QALY and US $50,000/QALY, respectively.

CONCLUSIONS
Introducing QIV into the US immunization program may prevent a substantial number of hospitalizations and deaths. QIV is also expected to be a cost-effective alternative option to TIV.