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Paper 3
Published in Aalia Khan, Ramsey Jabbour, Almas Rehman, nMRCGP Applied Knowledge Test Study Guide, 2021
Aalia Khan, Ramsey Jabbour, Almas Rehman
Economic analysis is used to define choices in resource allocation. It takes into account direct, indirect and intangible costs. Cost/benefit analysis measures the outcome in monetary units and cost utility analysis measures outcomes in quality adjusted life years (QALYs).
Undertaking economic evaluations
Published in David Kernick, Getting Health Economics into Practice, 2018
When different interventions are being considered (for example resource allocations between mental health or cardiovascular disease) and there is no common clinical outcome measure, or when decision makers wish to encompass quality of life, a cost utility analysis will be the method of choice. Due to methodological problems of converting all outputs into monetary values, cost benefit exercises have not been widely used.
What is wrong with medicine?
Published in Jim Connelly, Chris Worth, Making Sense of Public Health Medicine, 2018
Health economists describe a number of techniques that, it is claimed, are useful in providing a framework to enable doctors or others to choose the most efficient use of resources among alternatives. These techniques include cost-benefit analysis (CBA), cost-effectiveness analysis (CEA) and cost-utility analysis (CUA). Let us take cost-effectiveness analysis (CEA) and look at its details. CEA is generally believed to be the least contentious technique, so, if we find unbridgeable problems with it, we can be fairly sure that the other techniques will also unravel under a detailed analysis.
Cost-effectiveness of enzalutamide versus apalutamide versus androgen deprivation therapy alone for the treatment of metastatic castration-sensitive prostate cancer in Canada
Published in Journal of Medical Economics, 2022
Fred Saad, Andrew Chilelli, Benny Hui, Sergey Muratov, Arijit Ganguli, Scott North, Bobby Shayegan
Aligned with the Canadian Agency for Drugs and Technologies in Health economic evaluations guidelines, we conducted a cost-utility analysis to compare the costs and quality-adjusted life-years (QALYs) across the comparators. Expected costs and QALYs for each comparator were derived through probabilistic analysis performed in Excel using a Monte Carlo simulation with 5,000 iterations. LYs, QALYs, and costs were discounted at 1.5% per year as per best-practice norms recommended by the International Society for Pharmacoeconomics and Outcomes Research35,36 and the National Institute for Health and Care Excellence37. Uncertainty was presented using a cost-effectiveness acceptability curve (Supplementary Figure S2) demonstrating the probability of interventions to be cost-effective at different willingness-to-pay (WTP) thresholds. As the model had more than one comparator, sequential analysis was used to exclude interventions that were either dominated or subject to extended dominance. The results of sequential analysis were presented on a cost-effectiveness frontier. A full description of model parameters and settings used for the base-case analysis is shown in Supplementary Table S5. Key inputs in the model base case are shown in Supplementary Table S6.
Economic Evaluation of the SOS Training to Reduce Victimization in Dual Diagnosis Patients
Published in Journal of Dual Diagnosis, 2021
Marleen M. de Waal, Matthijs Blankers, Nick M. Lommerse, Martijn J. Kikkert, Jack J. M. Dekker, Anna E. Goudriaan
We extracted 5000 nonparametric bootstrapped samples with 125 participants per trial arm from the MI dataset, in accordance with the sample size of the original dataset. For each of these bootstrapped samples, we calculated the incremental costs, incremental effects, and incremental cost-effectiveness ratio (ICER). The ICER was calculated as (CostsCAU+SOS – CostsCAU)/(EffectsCAU+SOS – effectsCAU), with effects defined as treatment response for victimization in the cost-effectiveness analysis and as QALYs in the cost-utility analysis. The ICERs of all 5000 bootstrapped samples were plotted on cost-effectiveness planes for both outcomes separately. Next, cost-effectiveness acceptability curves (CEACs) were drawn based on the distribution of the ICERs over the cost-effectiveness planes. The CEAC shows the probability that CAU + SOS is cost-effective in comparison with CAU as a function of the willingness-to-pay (WTP) for one additional unit of effect (1 person with treatment response for victimization or 1 QALY), since the WTP is generally unknown. At a probability of 0.5, the indifference point is reached. Above this indifference point, CAU + SOS has a better likelihood to be preferred over CAU with regard to cost-effectiveness.
Impact of growing up with a sibling with a neurodevelopmental disorder on the quality of life of an unaffected sibling: a scoping review
Published in Disability and Rehabilitation, 2021
There are many pediatric generic health profile QoL/HRQoL instruments (a type of generic instrument) and disease-specific QoL instruments designed for different conditions and purposes that do not always allow comparison of results across studies or clinical contexts. For instance, Vieria and Fernandes [52] and Ferria Marciano [50] both studied the impacts of siblings’ ASD on unaffected siblings; however, their results cannot be compared because they used two different generic health profile QoL instruments, AUQEI and WHOQOL-BREF. Moreover, the results were not consistent even with the same instruments used for unaffected siblings of children with different NDD [51,53]. This suggests that researchers might have to check the validity and reliability of the QoL/HRQoL instruments before using in unaffected siblings of children with NDD. Only one study used preference-based generic HRQoL instruments (CHU-9D and EQ-5D-Y) to measure QoL of unaffected siblings of children with ADHD [42]. The advantage of using the preference-based HRQoL instrument is that it facilitates the estimation of health state values that is used to calculate the Quality-adjusted life years (QALYs). The QALY is used in economic evaluation to assess the benefits of interventions. An economic evaluation with benefits expressed in QALYs-called a cost-utility analysis- enables the comparison of the value of interventions across clinical areas for resource allocation purposes [34].