Papers in this group
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Many cost-effectiveness analyses (CEAs) use data from observational studies. Statistical methods can only address selection bias if they make plausible assumptions. No quality assessment tool is available for appraising CEAs that use observational…
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Net health benefits: a new framework for the analysis of uncertainty in cost-effectiveness analysis.In recent years, considerable attention has been devoted to the development of statistical methods for the analysis of uncertainty in cost-effectiveness (CE) analysis, with a focus on situations in which the analyst has patient-level data on the…
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The objective of this study was to determine utility scores for various chronic conditions.
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Utilities are numeric measurements that reflect an individual's beliefs about the desirableness of a health condition, willingness to take risks to gain health benefits, and preferences for time. This report discusses the approaches to assess and…
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Simulation models that support decision and cost-effectiveness analysis can further the goals of evidence-based medicine by facilitating the synthesis of information from several sources into a single comprehensive structure. The Stroke Prevention…
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Preference elicitation tasks for better than dead (BTD) and worse than dead (WTD) health states vary in the conventional time trade-off (TTO) procedure, casting doubt on uniformity of scale. 'Lead time TTO' (LT-TTO) was recently introduced to…
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BACKGROUND Disease-specific estimates of medical costs are important for health policy decision making. OBJECTIVE To identify predictors of health care costs associated with hepatitis C virus (HCV) seropositivity across disease phases. METHODS HCV…
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OBJECTIVE: To estimate the total healthcare costs and costs attributable to prostate cancer across all stages of disease, and to determine the predictors of those costs, as describing the cost of care for patients with prostate cancer is useful to…
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It is proper to preamble an essay of this sort with the observation that anyone who has received health care for a serious illness is likely to agree that, with few exceptions, health care sectors in the USA and elsewhere tend to be staffed with…
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n addition to statistical significance, it is important to evaluate the magnitude of differences in health-related quality of life over time. Interest in establishing the minimal difference that is clinically important or the minimally important…
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Accounting for uncertainty is now a standard part of decision-analytic modeling and is recommended by many health technology agencies and published guidelines. However, the scope of such analyses is often limited, even though techniques have been…
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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…