Can I use this skill to create oncology models?

Yes, it includes specific patterns for Partitioned Survival Analysis (PSM), which is the standard methodology for modeling progression-free and overall survival in oncology economic evaluations.

How does this skill handle model uncertainty?

It provides comprehensive workflows for Probabilistic Sensitivity Analysis (PSA), allowing you to define parameter distributions and generate CE planes and Cost-Effectiveness Acceptability Curves (CEAC).

Does it support Value of Information (VOI) analysis?

Yes, it includes implementation methods for calculating the Expected Value of Perfect Information (EVPI) and Expected Value of Partial Perfect Information (EVPPI) to prioritize future research.

Which R packages does this skill primarily use?

This skill provides guidance and code patterns for industry-standard packages including BCEA for cost-effectiveness, heemod for Markov modeling, hesim for PSM, and flexsurv for survival analysis.

Health Economics Analysis in R

Name: Health Economics Analysis in R
Author: choxos

bychoxos

0•

データサイエンスとML

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

This skill provides specialized implementation patterns for health economists and researchers to conduct rigorous economic evaluations within the R environment. It covers foundational metrics like ICERs and NMB, advanced disease modeling using Markov cohorts and Partitioned Survival Analysis (PSM), and comprehensive uncertainty quantification via Probabilistic Sensitivity Analysis (PSA). By integrating industry-standard packages such as BCEA, heemod, and hesim, it streamlines the creation of health technology assessment (HTA) models and visualizations like Cost-Effectiveness Acceptability Curves (CEAC).

主な機能

01Advanced Markov cohort modeling with time-dependent parameters and cycle corrections

02Comprehensive ICER, QALY, and Net Monetary Benefit (NMB) calculations

03Value of Information (VOI) analysis including EVPI and EVPPI calculations

040 GitHub stars

05Partitioned Survival Analysis (PSM) for oncology and chronic disease simulations

06Probabilistic Sensitivity Analysis (PSA) with automated CEAC and CE Plane plotting

ユースケース

01Conducting budget impact analyses for new medical interventions and pharmaceutical products

02Simulating long-term patient health outcomes and costs from clinical trial data

03Developing health technology assessment (HTA) models for regulatory and reimbursement submissions

主な機能

01Advanced Markov cohort modeling with time-dependent parameters and cycle corrections

02Comprehensive ICER, QALY, and Net Monetary Benefit (NMB) calculations

03Value of Information (VOI) analysis including EVPI and EVPPI calculations

040 GitHub stars

05Partitioned Survival Analysis (PSM) for oncology and chronic disease simulations

06Probabilistic Sensitivity Analysis (PSA) with automated CEAC and CE Plane plotting

ユースケース

01Conducting budget impact analyses for new medical interventions and pharmaceutical products

02Simulating long-term patient health outcomes and costs from clinical trial data

03Developing health technology assessment (HTA) models for regulatory and reimbursement submissions