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Estimating Optimal Dynamic Treatment Strategies Under Resource Constraints Using Dynamic Marginal Structural Models

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Abstract Background: Existing methods for estimating the optimal treatment or monitoring strategy typically assume unlimited access to resources. However, when a health system has resource constraints, such as limited funds, access to medication, or monitoring capabilities, medical decisions must balance impacts on both individual and population health outcomes. That is, decisions should account for competition between individuals in resource usage. A simple solution is to estimate the (counterfactual) resource usage under the possible interventions and choose the optimal strategy for which resource usage is within acceptable limits. Methods: We propose a method to identify the optimal dynamic intervention strategy that leads to the best expected health outcome accounting for a health system's resource constraints. We then apply this method to determine the optimal dynamic monitoring strategy for people living with HIV when resource limits on monitoring exist using observational data from the HIV-CAUSAL Collaboration. In our example, we identify the optimal CD4 cell count at which to decrease monitoring frequency from every 3-6 months to every 9-12 months among the subset of strategies that satisfy a hypothetical constraint on monitoring. We find the resource constrained dynamic strategy (RCDS) that minimizes the risk of virologic failure given a hypothetical resource constraint where individuals can only be monitored on average every 6 months. Results: Given the hypothetical resource constraint, the optimal monitoring strategy is `monitor CD4 cell count and HIV-RNA every 3-6 months when CD4 is below 320 cells/ml and every 9-12 months when CD4 is above 320 cells/ml.' Conclusions: We describe and and apply a method to identify the optimal RCDS given a hypothetical resource constraint. Similar applications may be useful in settings with limited availability of or capacity for monitoring individuals living with HIV or other chronic diseases.
Title: Estimating Optimal Dynamic Treatment Strategies Under Resource Constraints Using Dynamic Marginal Structural Models
Description:
Abstract Background: Existing methods for estimating the optimal treatment or monitoring strategy typically assume unlimited access to resources.
However, when a health system has resource constraints, such as limited funds, access to medication, or monitoring capabilities, medical decisions must balance impacts on both individual and population health outcomes.
That is, decisions should account for competition between individuals in resource usage.
A simple solution is to estimate the (counterfactual) resource usage under the possible interventions and choose the optimal strategy for which resource usage is within acceptable limits.
Methods: We propose a method to identify the optimal dynamic intervention strategy that leads to the best expected health outcome accounting for a health system's resource constraints.
We then apply this method to determine the optimal dynamic monitoring strategy for people living with HIV when resource limits on monitoring exist using observational data from the HIV-CAUSAL Collaboration.
In our example, we identify the optimal CD4 cell count at which to decrease monitoring frequency from every 3-6 months to every 9-12 months among the subset of strategies that satisfy a hypothetical constraint on monitoring.
We find the resource constrained dynamic strategy (RCDS) that minimizes the risk of virologic failure given a hypothetical resource constraint where individuals can only be monitored on average every 6 months.
Results: Given the hypothetical resource constraint, the optimal monitoring strategy is `monitor CD4 cell count and HIV-RNA every 3-6 months when CD4 is below 320 cells/ml and every 9-12 months when CD4 is above 320 cells/ml.
' Conclusions: We describe and and apply a method to identify the optimal RCDS given a hypothetical resource constraint.
Similar applications may be useful in settings with limited availability of or capacity for monitoring individuals living with HIV or other chronic diseases.

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