Dataset Information

Estimating cost-effectiveness from claims and registry data with measured and unmeasured confounders.

ABSTRACT: The analysis of observational data to determine the cost-effectiveness of medical treatments is complicated by the need to account for skewness, censoring, and the effects of measured and unmeasured confounders. We quantify cost-effectiveness as the Net Monetary Benefit (NMB), a linear combination of the treatment effects on cost and effectiveness that denominates utility in monetary terms. We propose a parametric estimation approach that describes cost with a Gamma generalized linear model and survival time (the canonical effectiveness variable) with a Weibull accelerated failure time model. To account for correlation between cost and survival, we propose a bootstrap procedure to compute confidence intervals for NMB. To examine sensitivity to unmeasured confounders, we derive simple approximate relationships between naïve parameters, assuming only measured confounders, and the values those parameters would take if there was further adjustment for a single unmeasured confounder with a specified distribution. A simulation study shows that the method returns accurate estimates for treatment effects on cost, survival, and NMB under the assumed model. We apply our method to compare two treatments for Stage II/III bladder cancer, concluding that the NMB is sensitive to hypothesized unmeasured confounders that represent smoking status and personal income.

SUBMITTER: Handorf EA

PROVIDER: S-EPMC7673459 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Estimating cost-effectiveness from claims and registry data with measured and unmeasured confounders.

Handorf Elizabeth A EA Heitjan Daniel F DF Bekelman Justin E JE Mitra Nandita N

Statistical methods in medical research 20180222 7

The analysis of observational data to determine the cost-effectiveness of medical treatments is complicated by the need to account for skewness, censoring, and the effects of measured and unmeasured confounders. We quantify cost-effectiveness as the Net Monetary Benefit (NMB), a linear combination of the treatment effects on cost and effectiveness that denominates utility in monetary terms. We propose a parametric estimation approach that describes cost with a Gamma generalized linear model and ...[more]

PMID: 29468944

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Project description:1. Demographic rates can vary not only with measured individual characters like age, sex and mass but also with unmeasured individual variables like behaviour, genes and health. 2. Predictions from population models that include measured individual characteristics often differ from models that exclude them. Similarly, unmeasured individual differences have the potential to impact predictions from population models. However, unmeasured individual differences are rarely included in population models. 3. We construct stage- and age-structured models (where stage is mass) of a roe deer population, which are parameterized from statistical functions that either include, or ignore, unmeasured individual differences. 4. We found that mass and age structures substantially impacted model parameters describing population dynamics, as did temporal environmental variation, while unmeasured individual differences impacted parameters describing population dynamics to a much smaller extent once individual heterogeneity related to mass and age has been included in the model. We discuss how our assumptions (unmeasured individual differences only in mean trait values) could have influenced our findings and under what circumstances unmeasured individual differences could have had a larger impact on population dynamics. 5. There are two reasons explaining the relative small influence of unmeasured individual differences on population dynamics in roe deer. First, individual body mass and age both capture a large amount of individual differences in roe deer. Second, in large populations of long-lived animals, the average quality of individuals (independent of age and mass) within the population is unlikely to show substantial variation over time, unless rapid evolution is occurring. So even though a population consisting of high-quality individuals would have much higher population growth rate than a population consisting of low-quality individuals, the probability of observing a population consisting only of high-quality individuals is small.

Dataset Information

Estimating cost-effectiveness from claims and registry data with measured and unmeasured confounders.

Publications

Estimating cost-effectiveness from claims and registry data with measured and unmeasured confounders.

Similar Datasets

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