voiage.methods.implementation.value_of_implementation

value_of_implementation

value_of_implementation([positional or keyword] value_array: ValueArray = None, [positional or keyword] uptake: float = 1.0, [positional or keyword] adherence: float = 1.0, [positional or keyword] coverage: float = 1.0, [positional or keyword] implementation_delay: float = 0.0, [positional or keyword] implementation_uncertainty: float = 0.0, [positional or keyword] discount_rate: float = 0.0, [positional or keyword] time_horizon: float | None = None, [positional or keyword] population: float | None = None, [positional or keyword] strategy_names: list[str] | None = None) -> ImplementationAdjustedResult

Calculate the value of implementation-adjusted adoption.

Parameters

value_array : ValueArray 2D net-benefit samples with shape (n_samples, n_strategies). uptake, adherence, coverage : float, default=1.0 Implementation fraction inputs in the range [0, 1]. implementation_delay : float, default=0.0 Delay before the intervention is implemented, in years. implementation_uncertainty : float, default=0.0 Additional uncertainty penalty in the range [0, 1]. discount_rate : float, default=0.0 Annual discount rate used to discount delayed implementation. time_horizon : float, optional Optional time horizon for reporting and future scaling. population : float, optional Optional population size for population-adjusted reporting. strategy_names : list[str], optional Optional strategy labels.

Returns

ImplementationAdjustedResult Baseline and implementation-adjusted summaries.

Notes

The implementation multiplier combines uptake, adherence, coverage, uncertainty, and delay:

.. math::

m = u \times a \times c \times (1 - \delta) \times (1 + r)^{-t}.

The reported value is the non-negative difference between the baseline optimal expected net benefit and the adjusted optimal expected net benefit, optionally scaled by population and the discounted time horizon.

References

Claxton, K., Sculpher, M., & Palmer, S. (2011). Considerations for modelling implementation and uptake in economic evaluation. Phelps, C., & Mushlin, A. (1991). Focusing technology assessment using medical decision analysis.

Examples

>>> import numpy as np >>> from voiage.methods.implementation import value_of_implementation >>> from voiage.schema import ValueArray >>> values = np.array([[10.0, 12.0], [11.0, 11.5]]) >>> result = value_of_implementation(ValueArray.from_numpy(values, [“A”, “B”])) >>> result.value >= 0.0 True

Parameters:

• value_array ValueArray
• uptake float (default: 1.0)
• adherence float (default: 1.0)
• coverage float (default: 1.0)
• implementation_delay float (default: 0.0)
• implementation_uncertainty float (default: 0.0)
• discount_rate float (default: 0.0)
• time_horizon float | None (default: None)
• population float | None (default: None)
• strategy_names list[str] | None (default: None)

Returns: ImplementationAdjustedResult