scholarly journals The who-choice cost-effectiveness Threshold: a Country-level analysis of changes over time

2015 ◽  
Vol 18 (3) ◽  
pp. A88 ◽  
Author(s):  
M. Griffiths ◽  
M. Maruszczak ◽  
J. Kusel
2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
K Mullavelil ◽  
V George ◽  
A Thannikkal ◽  
R Aravindakshan ◽  
D John ◽  
...  

Abstract Background Only little attention has been paid to treatment strategies of chronic disease conditions that require long term treatment and repeated hospitalizations Purpose Our aim was to review cost-effectiveness of guideline directed medical therapy of heart failure in India and identify drugs that can be made available free of cost or at subsidized rates to the patient population. Methods Data extracted from ten landmark trials in heart failure was used to compute Number Needed to Treat (NNT) and Cost Needed to Treat (CNT) of drugs used in heart failure, to prevent cardiovascular mortality and heart failure re-hospitalization using HDS Plotter- Incremental Cost Effectiveness Calculator. Since various brands (i.e. trade names) with wide cost range are available in Indian market, the average retail price in Indian Rupees for year 2019 was considered and converted to US dollars and used for the analysis.NNT and CNT of each drug was computed and the cost-effectiveness was analyzed. WHO recommendation of three times per capita GDP was used as the cost effectiveness threshold. Results Medications that were labeled as class I for the treatment of heart failure, were included in our analysis. Ivabradine, Valsartan and Angiotensin Receptor Neprilysin inhibitor (ARNi) did not meet the cost effectiveness criteria for preventing cardio-vascular mortality. For prevention of heart failure re-hospitalization, all drugs except ARNi, met the cost effectiveness threshold. Conclusion Any future research would need to consider compliance factor along with Willingness to Pay (WTP) to understand the real acceptance of these drugs on the ground in India. Log prices (in US$) of various HF drugs Funding Acknowledgement Type of funding source: None


2015 ◽  
Vol 19 (14) ◽  
pp. 1-504 ◽  
Author(s):  
Karl Claxton ◽  
Steve Martin ◽  
Marta Soares ◽  
Nigel Rice ◽  
Eldon Spackman ◽  
...  

BackgroundCost-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.Objectives(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.MethodsEarlier 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.ResultsThe 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.LimitationsThe 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.ConclusionsThe 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.FundingThe National Institute for Health Research-Medical Research Council Methodology Research Programme.


2018 ◽  
Vol 21 ◽  
pp. S113
Author(s):  
P. van Baal ◽  
M. Perry-Duxbury ◽  
P. Bakx ◽  
M. Versteegh ◽  
E. van Doorslaer ◽  
...  

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