scholarly journals Using QALYs versus DALYs to measure cost-effectiveness: How much does it matter?

2020 ◽  
Vol 36 (2) ◽  
pp. 96-103 ◽  
Author(s):  
Xue Feng ◽  
David D. Kim ◽  
Joshua T. Cohen ◽  
Peter J. Neumann ◽  
Daniel A. Ollendorf

ObjectivesQuality-adjusted life-years (QALYs) and disability-adjusted life-years (DALYs) are commonly used in cost-effectiveness analysis (CEA) to measure health benefits. We sought to quantify and explain differences between QALY- and DALY-based cost-effectiveness ratios, and explore whether using one versus the other would materially affect conclusions about an intervention's cost-effectiveness.MethodsWe identified CEAs using both QALYs and DALYs from the Tufts Medical Center CEA Registry and Global Health CEA Registry, with a supplemental search to ensure comprehensive literature coverage. We calculated absolute and relative differences between the QALY- and DALY-based ratios, and compared ratios to common benchmarks (e.g., 1× gross domestic product per capita). We converted reported costs into US dollars.ResultsAmong eleven published CEAs reporting both QALYs and DALYs, seven focused on pharmaceuticals and infectious disease, and five were conducted in high-income countries. Four studies concluded that the intervention was “dominant” (cost-saving). Among the QALY- and DALY-based ratios reported from the remaining seven studies, absolute differences ranged from approximately $2 to $15,000 per unit of benefit, and relative differences from 6–120 percent, but most differences were modest in comparison with the ratio value itself. The values assigned to utility and disability weights explained most observed differences. In comparison with cost-effectiveness thresholds, conclusions were consistent regardless of the ratio type in ten of eleven cases.ConclusionsOur results suggest that although QALY- and DALY-based ratios for the same intervention can differ, differences tend to be modest and do not materially affect comparisons to common cost-effectiveness thresholds.

2009 ◽  
Vol 30 (3) ◽  
pp. 314-319 ◽  
Author(s):  
Lisa M. Meckley ◽  
Dan Greenberg ◽  
Joshua T. Cohen ◽  
Peter J. Neumann

Background. Cost-effectiveness acceptability curves (CEACs) plot the probability that one health intervention is more cost-effective than alternatives, as a function of societal willingness to pay for additional units of health (e.g., life-years or quality-adjusted life-years gained). Objectives. To quantify the adoption of CEACs in published cost-utility analyses (CUAs), and to identify factors associated with CEAC use. Methods. Data from the Tufts Medical Center Cost-Effectiveness Analysis Registry (www.cearegistry.org), a database with detailed information on approximately 1,400 CUAs published in the peer reviewed literature through 2006, was analyzed. The registry includes data on study origin, study methodology, reporting of results, whether CEACs were presented, and a subjective quality score. Univariate and multivariate logistic regression analyses were used to identify factors predicting CEAC use, from their introduction in 1994 through 2006. Results. Approximately 15% of CUAs published since 1994 present a CEAC. The use of CEACs has increased rapidly in recent years, from 2.1% of published CUAs in 2001 to 32.6% in 2006 (P < 0.0001). The most significant predictors of CEAC use were study quality (odds ratio [OR]: 2.26; 95% confidence interval [CI]: 1.80, 2.85), recent publication (OR: 1.99; 95% CI: 1.73, 2.29), and whether studies pertain to the UK (OR: 5.66; 95% CI: 3.67, 8.72) or Sweden (OR: 3.76; 95% CI: 1.67, 8.44). Conclusions. CEAC use is increasing in the published cost-effectiveness literature, especially in UK-based studies.


Author(s):  
Scott Burris ◽  
Micah L. Berman ◽  
Matthew Penn, and ◽  
Tara Ramanathan Holiday

Chapter 5 discusses the use of epidemiology to identify the source of public health problems and inform policymaking. It uses a case study to illustrate how researchers, policymakers, and practitioners detect diseases, identify their sources, determine the extent of an outbreak, and prevent new infections. The chapter also defines key measures in epidemiology that can indicate public health priorities, including morbidity and mortality, years of potential life lost, and measures of lifetime impacts, including disability-adjusted life years and quality-adjusted life years. Finally, the chapter reviews epidemiological study designs, differentiating between experimental and observational studies, to show how to interpret data and identify limitations.


2021 ◽  
Vol 24 (3) ◽  
pp. 353-360
Author(s):  
Maša Davidović ◽  
Nadine Zielonke ◽  
Iris Lansdorp-Vogelaar ◽  
Nereo Segnan ◽  
Harry J. de Koning ◽  
...  

Author(s):  
Charu Prakash

This study examines the parameters crucial to cost-effectiveness of universal hepatitis B immunization in India. An incremental cost-effectiveness analysis was done using a decision tree (Markov model) to follow up a hypothetical cohort of 100,000 newborns for the effects of hepatitis B acquired vertically at birth. The measure of effectiveness was disability-adjusted life-years gained. Uncertainty analysis and Scenario analysis were done using Latin hypercube sampling. Hepatitis B endemicity is the most important factor, followed by the cost of vaccine. Other factors of some influence are vaccination coverage, vaccine efficacy, HBeAg positivity, and vaccine wastage.


2020 ◽  
Vol 5 (7) ◽  
pp. e003259 ◽  
Author(s):  
Sanjay G Reddy

Are the steps that have been taken to arrest the spread of COVID-19 justifiable? Specifically, are they likely to have improved public health understood according to widely used aggregate population health measures, such as Quality Adjusted Life Years (QALYs) and Disability Adjusted Life Years (DALYs) as much or more than alternatives? This is a reasonable question, since such measures have been promoted extensively in global and national health policy by influential actors, and they have become almost synonymous with quantification of public health. If the steps taken against COVID-19 did not meet this test, then either the measures or the policies must be re-evaluated. There are indications that policies against COVID-19 may have been unbalanced and therefore not optimal. A balanced approach to protecting population health should be proportionate in its effects across distinct health concerns at a moment, across populations over time and across populations over space. These criteria provide a guide to designing and implementing policies that diminish harm from COVID-19 while also providing due attention to other threats to aggregate population health. They should shape future policies in response to this pandemic and others.


2021 ◽  
Vol 12 ◽  
Author(s):  
Yaohua Cao ◽  
Lina Zhao ◽  
Tiantian Zhang ◽  
Weiling Cao

Background: To evaluate the cost-effectiveness of adding daratumumab to bortezomib, melphalan, and prednisone for transplant-ineligible newly diagnosed multiple myeloma patients.Methods: A three-state Markov model was developed from the perspective of US payers to simulate the disease development of patient’s life time for daratumumab plus bortezomib, melphalan, and prednisone (D-VMP) and bortezomib, melphalan, and prednisone (VMP) regimens. The primary outputs were total costs, expected life-years (LYs), quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs).Results: The base case results showed that adding daratumumab to VMP provided an additional 3.00 Lys or 2.03 QALYs, at a cost of $262,526 per LY or $388,364 per QALY. Sensitivity analysis indicated that the results were most sensitive to utility of progression disease of D-VMP regimens, but no matter how these parameters changed, ICERs remained higher than $150,000 per QALY.Conclusion: In the case that the upper limit of willingness to pay threshold was $150,000 per QALY from the perspective of US payers, D-VMP was not a cost-effective regimen compared to VMP.


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