Health Technology Assessment (HTA) involves evaluating the relevance and value of health technologies, such as drugs, within health care systems. Supporting this process from a biostatistical perspective requires a different mindset and distinct analytical methods compared to those used in regulatory submissions.

One approach to HTA is the German AMNOG process, which requires extensive data slicing to produce the necessary statistical material. This approach necessitates significant programming and orchestration effort, especially when following a traditional "one output - one program" methodology.

Compounding the challenge, the EU's joint initiative to streamline the HTA process across Europe, known as EU HTA, allows all member countries to bring forward similar individual requirements. This implies a significant increase in number of data slices and analyses required and a substantial workload for statistical programmers in the future. However, many of these analyses are repetitive and suitable for automation.

At Novo Nordisk we are involved in the HTA-R workstream under openstatsware where we are developing an open source ecosystem of R packages called {ramnog} to address the current challenges of AMNOG and the future demands of EU HTA. The goal is to automate repetitive tasks, allowing our colleagues more time to focus on complex analyses.

In our presentation, we will guide you through the practical aspects of specifying an analysis required for a typical AMNOG output and demonstrate how the package runs the analysis. Additionally, we will provide a technical overview of the ecosystem, detailing the roles and considerations of the individual components.
Matthew Phelps | Christian Haargard Olsen
Novo Nordisk | Novo Nordisk
ramnog: R package suite for automating statistical analyses
Health Technology Assessment (HTA) involves evaluating the relevance and value of health technologies, such as drugs, within health care systems. Supporting this process from a biostatistical perspective requires a different mindset and distinct analytical methods compared to those used in regulatory submissions.  One approach to HTA is the German AMNOG process, which requires extensive data slicing to produce the necessary statistical material. This approach necessitates significant programming and orchestration effort, especially when following a traditional "one output - one program" methodology.  Compounding the challenge, the EU's joint initiative to streamline the HTA process across Europe, known as EU HTA, allows all member countries to bring forward similar individual requirements. This implies a significant increase in number of data slices and analyses required and a substantial workload for statistical programmers in the future. However, many of these analyses are repetitive and suitable for automation.  At Novo Nordisk we are involved in the HTA-R workstream under openstatsware where we are developing an open source ecosystem of R packages called  ramnog  to address the current challenges of AMNOG and the future demands of EU HTA. The goal is to automate repetitive tasks, allowing our colleagues more time to focus on complex analyses.  In our presentation, we will guide you through the practical aspects of specifying an analysis required for a typical AMNOG output and demonstrate how the package runs the analysis. Additionally, we will provide a technical overview of the ecosystem, detailing the roles and considerations of the individual components.