Which R packages does this skill support?

It provides implementation patterns for leading health economics packages including BCEA for Bayesian cost-effectiveness, heemod for Markov models, and hesim for partitioned survival analysis.

Can I generate visualizations for health economics reports?

Yes, the skill includes specialized plotting functions for cost-effectiveness planes, acceptability curves (CEAC), and expected incremental benefit (EIB) plots.

Does it support sensitivity analysis?

Absolutely. The skill covers Probabilistic Sensitivity Analysis (PSA), Expected Value of Perfect Information (EVPI), and Expected Value of Partial Perfect Information (EVPPI).

Can I calculate QALYs and ICERs with this skill?

Yes, it includes standardized code for calculating Quality-Adjusted Life Years (QALYs), Incremental Cost-Effectiveness Ratios (ICERs), and Net Health Benefits (NHB).

Health Economics Analysis in R

Name: Health Economics Analysis in R
Author: choxos

bychoxos

0•

Ciencia de Datos y ML

Performs advanced health economic evaluations including cost-effectiveness analysis, Markov modeling, and sensitivity analysis using R.

This skill equips Claude with specialized knowledge for health economic evaluations (HEE) within the R ecosystem. It provides implementation patterns for core metrics like ICERs and QALYs, while supporting advanced modeling techniques such as Markov cohort models, partitioned survival analysis (PSM), and probabilistic sensitivity analysis (PSA). Ideal for health economists and biostatisticians, it streamlines the creation of cost-effectiveness planes, acceptability curves, and Value of Information (VOI) assessments using industry-standard packages like BCEA, heemod, and hesim.

Características Principales

01Generates cost-effectiveness planes and acceptability curves (CEAC) using BCEA

02Performs Probabilistic Sensitivity Analysis (PSA) and Value of Information (VOI) calculations

03Builds multi-state Markov cohort models with time-dependent parameters

040 GitHub stars

05Conducts Partitioned Survival Analysis (PSM) for long-term health state projections

06Calculates Incremental Cost-Effectiveness Ratios (ICER) and Net Monetary Benefit (NMB)

Casos de Uso

01Comparing the cost-effectiveness of a new medical intervention against standard care

02Assessing decision uncertainty for Health Technology Assessment (HTA) submissions

03Simulating long-term patient outcomes and healthcare costs using Markov models

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add choxos/biostatagent health-economics

For use in Claude.ai and ChatGPT

Características Principales

01Generates cost-effectiveness planes and acceptability curves (CEAC) using BCEA

02Performs Probabilistic Sensitivity Analysis (PSA) and Value of Information (VOI) calculations

03Builds multi-state Markov cohort models with time-dependent parameters

040 GitHub stars

05Conducts Partitioned Survival Analysis (PSM) for long-term health state projections

06Calculates Incremental Cost-Effectiveness Ratios (ICER) and Net Monetary Benefit (NMB)

Casos de Uso

01Comparing the cost-effectiveness of a new medical intervention against standard care

02Assessing decision uncertainty for Health Technology Assessment (HTA) submissions

03Simulating long-term patient outcomes and healthcare costs using Markov models