A Framework for Addressing Structural Uncertainty in Decision Models

2011 ◽  
Vol 31 (4) ◽  
pp. 662-674 ◽  
Author(s):  
Christopher H. Jackson ◽  
Laura Bojke ◽  
Simon G. Thompson ◽  
Karl Claxton ◽  
Linda D. Sharples
Keyword(s):  
Cost Effectiveness ◽  
Probability Distributions ◽  
Predictive Ability ◽  
Decision Models ◽  
Data Uncertainty ◽  
Model Parameters ◽  
Biologic Drugs ◽  
Uncertain Model ◽  
Alternative Scenarios ◽  
Analytic Models

Decision analytic models used for health technology assessment are subject to uncertainties. These uncertainties can be quantified probabilistically, by placing distributions on model parameters and simulating from these to generate estimates of cost-effectiveness. However, many uncertain model choices, often termed structural assumptions, are usually only explored informally by presenting estimates of cost-effectiveness under alternative scenarios. The authors show how 2 recent research proposals represent parts of a framework to formally account for all common structural uncertainties. First, the model is expanded to include parameters that encompass all possible structural choices. Uncertainty can then arise because these parameters are estimated imprecisely from data, for example, a treatment effect of doubtful significance. Uncertainty can also arise if there are no relevant data. If there are relevant data, uncertainty can be addressed by averaging expected costs and effects generated from probabilistic analysis of the models with and without the parameter. The weights used for averaging are related to the predictive ability of each model, assessed against the data. If there are no data, additional parameters can often be informed by eliciting expert beliefs as probability distributions. These ideas are illustrated in decision models for antiplatelet therapies for vascular disease and new biologic drugs for the treatment of active psoriatic arthritis.

scholarly journals Using Bayesian Analysis to Quantify Uncertainty in Radiometer Measurements

2020 ◽  
Author(s):  
Jennifer Spinti ◽  
Sean T. Smith ◽  
Philip J. Smith ◽  
N.Stanley Harding ◽  
Kaitlyn Scheib ◽  
...  
Keyword(s):  
Probability Distributions ◽  
Data Uncertainty ◽  
Model Parameters ◽  
Measured Quantity ◽  
Uncertain Parameters ◽  
Calibration Data ◽  
Narrow Angle ◽  
Point Of Interest ◽  
Radiative Intensity ◽  
Uncertain Model

Abstract We apply Bayesian inference to the issue of instrument calibration and experimental data uncertainty analysis for the specific application of measuring radiative intensity with a narrow-angle radiometer. We develop a physics-based instrument model that describes intensity, the indirectly-measured quantity of interest, as a function of scenario and uncertain model parameters. We identify a set of five uncertain parameters and find their probability distributions (the posterior or inverse problem) given the calibration data by applying Bayes' Theorem. We then employ the instrument model in a new scenario, a 1.5 MW coal-fired furnace. We obtain values for the five uncertain parameters in the model by sampling from the posterior distribution and then compute the intensity with quantifiable uncertainty at the measurement point of interest (the posterior predictive or forward problem).

Classification of evidence in decision-analytic models of cost-effectiveness: A content analysis of published reports

2010 ◽  
Vol 26 (4) ◽  
pp. 458-462 ◽  
Author(s):  
Suzy Paisley
Keyword(s):  
Content Analysis ◽  
Cost Effectiveness ◽  
Methodological Approach ◽  
Model Development ◽  
Three Dimensions ◽  
Model Parameters ◽  
Modeling Framework ◽  
Diverse Range ◽  
Analytic Models

Objectives: The aim of this study was to assess systematically the scope of evidence and purposes for which evidence is used in decision-analytic models of cost-effectiveness and to assess the implications for search methods.Methods: A content analysis of published reports of models was undertaken. Details of cited sources were extracted and categorized according to three dimensions; type of information provided by the evidence, type of source from which the evidence was drawn and type of modeling activity supported by the evidence. The analysis was used to generate a classification of evidence. Relationships within and between the categories within the classification were sought and the implications for searching considered.Results: The classification generated fourteen types of information, seven types of sources of evidence and five modeling activities supported by evidence. A broad range of evidence was identified drawn from a diverse range of sources including both research-based and non–research-based sources. The use of evidence was not restricted to the population of model parameters but was used to inform the development of the modeling framework and to justify the analytical and methodological approach.Conclusions: Decision-analytic models use evidence to support all aspects of model development. The classification of evidence defines in depth the role of evidence in modeling. It can be used to inform the systematic identification of evidence.

scholarly journals Uncertainties in model predictions of nitrogen fluxes from agro-ecosystems in Europe

2012 ◽  
Vol 9 (5) ◽  
pp. 6051-6094 ◽  
Author(s):  
J. Kros ◽  
G. B. M. Heuvelink ◽  
G. J. Reinds ◽  
J. P. Lesschen ◽  
V. Ioannidi ◽  
...  
Keyword(s):  
Probability Distributions ◽  
Spatial Scales ◽  
Uncertainty Propagation ◽  
Correlation Coefficients ◽  
Monte Carlo Analysis ◽  
N Leaching ◽  
Model Parameters ◽  
Country Level ◽  
Uncertain Model ◽  
Relative Errors

Abstract. To assess the responses of nitrogen and greenhouse gas emissions to pan-European changes in land cover, land management and climate, an integrated dynamic model, INTEGRATOR, has been developed. This model includes both simple process-based descriptions and empirical relationships, and uses detailed GIS-based environmental and farming data in combination with various downscaling methods. This paper analyses the propagation of uncertainties in model inputs and model parameters to outputs of INTEGRATOR, using a Monte Carlo analysis. Uncertain model inputs and parameters were represented by probability distributions, while spatial correlation in these uncertainties was taken into account by assigning correlation coefficients at various spatial scales. The uncertainty propagation was analysed for the emissions of NH3, N2O and NOx and N leaching to groundwater and N surface runoff to surface water for the entire EU27 and for individual countries. Results show large uncertainties for N leaching and N runoff (relative errors of ~19 % for Europe as a whole), and smaller uncertainties for emission of N2O, NH3 and NOx (relative errors of ~12 %). Uncertainties for Europe as a whole were much smaller compared to uncertainties at Country level, because errors partly cancelled out due to spatial aggregation.

scholarly journals Combining regional to local restoration goals in the Brazilian Atlantic forest

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Cassia M.G. Lemos ◽  
Pedro R. Andrade ◽  
Ricardo R. Rodrigues ◽  
Leticia Hissa ◽  
Ana P. D. Aguiar
Keyword(s):  
Cost Effectiveness ◽  
Atlantic Forest ◽  
Natural Regeneration ◽  
Regional Level ◽  
Target Area ◽  
Brazilian Atlantic Forest ◽  
Regeneration Potential ◽  
Allocation Model ◽  
Alternative Scenarios ◽  
The Cost

AbstractTo achieve regional and international large-scale restoration goals with minimum costs, several restoration commitments rely on natural regeneration, a passive and inexpensive strategy. However, natural regeneration potential may vary within the landscape, mainly due to its historical context. In this work, we use spatially explicit restoration scenarios to explore how and where, within a given region, multiple restoration commitments could be combined to achieve cost-effectiveness outcomes. Our goal is to facilitate the elaboration of forest restoration plans at the regional level, taking into consideration the costs for active and passive restoration methods. The approach includes (1) a statistical analysis to estimate the natural regeneration potential for a given area based on alternative sets of biophysical, land cover, and/or socioeconomic factors and (2) the use of a land change allocation model to explore the cost-effectiveness of combining multiple restoration commitments in a given area through alternative scenarios. We test our approach in a strategic region in the Brazilian Atlantic Forest Biome, the Paraiba Valley in São Paulo State. Using the available data for 2011, calibrated for 2015, we build alternative scenarios for allocating natural regeneration until 2025. Our models indicate that the natural regeneration potential of the region is actually very low, and the cost-effectiveness outcomes are similar for all scenarios. We believe our approach can be used to support the regional-level decision-making about the implementation of multiple commitments aiming at the same target area. It can also be combined with other approaches for more refined analysis (e.g., optimization models).

scholarly journals Cost-effectiveness of TAS-102 plus bevacizumab versus TAS-102 monotherapy in patients with metastatic colorectal cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kiyoaki Sugiura ◽  
Yuki Seo ◽  
Takayuki Takahashi ◽  
Hideyuki Tokura ◽  
Yasuhiro Ito ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Health Care ◽  
Sensitivity Analysis ◽  
Cost Effectiveness ◽  
Combination Therapy ◽  
Metastatic Colorectal Cancer ◽  
Cost Effective ◽  
Model Parameters ◽  
Combination Regimen ◽  
The Cost

Abstract Background TAS-102 plus bevacizumab is an anticipated combination regimen for patients who have metastatic colorectal cancer. However, evidence supporting its use for this indication is limited. We compared the cost-effectiveness of TAS-102 plus bevacizumab combination therapy with TAS-102 monotherapy for patients with chemorefractory metastatic colorectal cancer. Method Markov decision modeling using treatment costs, disease-free survival, and overall survival was performed to examine the cost-effectiveness of TAS-102 plus bevacizumab combination therapy and TAS-102 monotherapy. The Japanese health care payer’s perspective was adopted. The outcomes were modeled on the basis of published literature. The incremental cost-effectiveness ratio (ICER) between the two treatment regimens was the primary outcome. Sensitivity analysis was performed and the effect of uncertainty on the model parameters were investigated. Results TAS-102 plus bevacizumab had an ICER of $21,534 per quality-adjusted life-year (QALY) gained compared with TAS-102 monotherapy. Sensitivity analysis demonstrated that TAS-102 monotherapy was more cost-effective than TAS-102 and bevacizumab combination therapy at a willingness-to-pay of under $50,000 per QALY gained. Conclusions TAS-102 and bevacizumab combination therapy is a cost-effective option for patients who have metastatic colorectal cancer in the Japanese health care system.

scholarly journals Cost Effectiveness of a Home-Based Intervention That Helps Functionally Vulnerable Older Adults Age in Place at Home

2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Eric Jutkowitz ◽  
Laura N. Gitlin ◽  
Laura T. Pizzi ◽  
Edward Lee ◽  
Marie P. Dennis
Keyword(s):  
Cost Effectiveness ◽  
Community Dwelling ◽  
Sensitivity Analyses ◽  
Model Parameters ◽  
Potential Cost ◽  
Functional Difficulties ◽  
Age In Place ◽  
Home Based ◽  
Occupational And Physical Therapy ◽  
Home Based Intervention

Evaluating cost effectiveness of interventions for aging in place is essential for adoption in service settings. We present the cost effectiveness of Advancing Better Living for Elders (ABLE), previously shown in a randomized trial to reduce functional difficulties and mortality in 319 community-dwelling elders. ABLE involved occupational and physical therapy sessions and home modifications to address client-identified functional difficulties, performance goals, and home safety. Incremental cost-effectiveness ratio (ICER), expressed as additional cost to bring about one additional year of life, was calculated. Two models were then developed to account for potential cost differences in implementing ABLE. Probabilistic sensitivity analyses were conducted to account for variations in model parameters. By two years, there were 30 deaths (9: ABLE; 21: control). Additional costs for 1 additional year of life was $13,179 for Model 1 and $14,800 for Model 2. Investment in ABLE may be worthwhile depending on society's willingness to pay.

scholarly journals A Hail Growth Trajectory Model for Exploring the Environmental Controls on Hail Size: Model Physics and Idealized Tests

2020 ◽  
Vol 77 (8) ◽  
pp. 2765-2791 ◽  
Author(s):  
Matthew R. Kumjian ◽  
Kelly Lombardo
Keyword(s):  
Residence Time ◽  
Vertical Wind Shear ◽  
Squall Line ◽  
Model Parameters ◽  
Convective Storms ◽  
Environmental Controls ◽  
Supercell Storm ◽  
Uncertain Model ◽  
Supercell Storms ◽  
Microphysical Processes

Abstract A detailed microphysical model of hail growth is developed and applied to idealized numerical simulations of deep convective storms. Hailstone embryos of various sizes and densities may be initialized in and around the simulated convective storm updraft, and then are tracked as they are advected and grow through various microphysical processes. Application to an idealized squall line and supercell storm results in a plausibly realistic distribution of maximum hailstone sizes for each. Simulated hail growth trajectories through idealized supercell storms exhibit many consistencies with previous hail trajectory work that used observed storms. Systematic tests of uncertain model parameters and parameterizations are performed, with results highlighting the sensitivity of hail size distributions to these changes. A set of idealized simulations is performed for supercells in environments with varying vertical wind shear to extend and clarify our prior work. The trajectory calculations reveal that, with increased zonal deep-layer shear, broader updrafts lead to increased residence time and thus larger maximum hail sizes. For cases with increased meridional low-level shear, updraft width is also increased, but hailstone sizes are smaller. This is a result of decreased residence time in the updraft, owing to faster northward flow within the updraft that advects hailstones through the growth region more rapidly. The results suggest that environments leading to weakened horizontal flow within supercell updrafts may lead to larger maximum hailstone sizes.

scholarly journals Cost-effectiveness of implementing objective diagnostic verification of asthma in the United States

2019 ◽  
Author(s):  
Mohsen Yaghoubi ◽  
Amin Adibi ◽  
Zafar Zafari ◽  
J Mark FitzGerald ◽  
Shawn D. Aaron ◽  
...  
Keyword(s):  
Quality Of Life ◽  
United States ◽  
Cost Effectiveness ◽  
The United States ◽  
Model Parameters ◽  
List Type ◽  
Asthma Diagnosis ◽  
Verification Algorithm ◽  
Input Parameters

AbstractBackgroundAsthma diagnosis in the community is often made without objective testing.ObjectiveThe aim of this study was to evaluate the cost-effectiveness of implementing a stepwise objective diagnostic verification algorithm among patients with community-diagnosed asthma in the United States (US).MethodsWe developed a probabilistic time-in-state cohort model that compared a stepwise asthma verification algorithm based on spirometry and methacholine challenge test against the current standard of care over 20 years. Model input parameters were informed from the literature and with original data analyses when required. The target population was US adults (≥15 y/o) with physician-diagnosed asthma. The final outcomes were costs (in 2018 $) and quality-adjusted life years (QALYs), discounted at 3% annually. Deterministic and probabilistic analyses were undertaken to examine the effect of alternative assumptions and uncertainty in model parameters on the results.ResultsIn a simulated cohort of 10,000 adults with diagnosed asthma, the stepwise algorithm resulted in the removal of diagnosis in 3,366. This was projected to be associated with savings of $36.26 million in direct costs and a gain of 4,049.28 QALYs over 20 years. Extrapolating these results to the US population indicated an undiscounted potential savings of $56.48 billion over 20 years. Results were robust against alternative assumptions and plausible changes in values of input parameters.ConclusionImplementation of a simple diagnostic testing algorithm to verify asthma diagnosis might result in substantial savings and improvement in patients’ quality of life.Key MessagesCompared with current standards of practice, the implementation of an asthma verification algorithm among US adults with diagnosed asthma can be associated with reduction in costs and gain in quality of life.There is substantial room for improving patient care and outcomes through promoting objective asthma diagnosis.Capsule summaryAsthma ‘overdiagnosis’ is common among US adults. An objective, stepwise verification algorithm for re-evaluation of asthma diagnosis can result in substantial savings in costs and improvements in quality of life.

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