health-economics-eval

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Model health interventions with ICER & PSA.

Authorxjtulyc
Version1.0.0
Installs0

System Documentation

What problem does it solve?

It solves the problem of deciding which healthcare intervention provides better value by estimating costs and health outcomes in a unified cost-effectiveness framework, including uncertainty.

Core Features & Use Cases

  • Markov cohort cost-effectiveness models: simulate state transitions over time and accumulate discounted costs and QALYs with optional half-cycle correction.
  • ICER computation and interpretation: calculate incremental cost-effectiveness ratios between comparator and new intervention strategies.
  • Probabilistic Sensitivity Analysis (PSA): run Monte Carlo simulations using parameter uncertainty to generate a cost-effectiveness plane distribution.
  • Cost-effectiveness planes & CEAC: visualize incremental outcomes and compute the probability of cost-effectiveness across willingness-to-pay (WTP) thresholds.

Typical use cases include preparing an economic evaluation for a public health intervention, comparing treatment strategies over a multi-year horizon, and supporting policy decisions using WHO-style WTP thresholds and Net Monetary Benefit (NMB).

Quick Start

Run a Markov cohort model for a three-state Healthy/Sick/Dead example and compute the ICER for a new intervention versus standard care.

Dependency Matrix

Required Modules

numpyscipypandasmatplotlib

Components

Standard package

💻 Claude Code Installation

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Please help me install this Skill:
Name: health-economics-eval
Download link: https://github.com/xjtulyc/awesome-rosetta-skills/archive/main.zip#health-economics-eval

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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