Build Cost-Effectiveness Frontier

Constructs a cost-effectiveness frontier from a set of interventions by finding the optimal sequence of solutions moving both up (more costly) and down (less costly) from a specified starting point. The algorithm uses incremental cost-effectiveness ratios (ICERs) and willingness-to-pay thresholds to determine acceptability.

Usage

frontier(
  x,
  threshold = Inf,
  start_index = 1,
  up_filter = NULL,
  down_filter = NULL
)

Arguments

x

A data.frame containing cost and impact data for interventions

threshold

Numeric. Willingness-to-pay threshold for ICER acceptability. Solutions with ICERs above this threshold will be rejected. Default is Inf.

start_index

Integer. Row index of the starting solution in the x. The algorithm builds the frontier from this point. Default is 1.

up_filter

Function. Optional user-defined filter function for cost-increasing solutions. Should take arguments (candidates, current) and return filtered candidates.

down_filter

Function. Optional user-defined filter function for cost-saving solutions. Should take arguments (candidates, current) and return filtered candidates.

Value

A data.frame containing the frontier solutions with an additional 'step' column indicating the sequence (negative values for cost-saving steps, positive for cost-increasing steps, 0 for the starting solution).