Analyzing U.S. prescription lists with RxNorm and the ATC/DDD Index

Area of Science:

• Pharmacology
• Health Informatics
• Drug Utilization Research

Background:

• The Anatomical Therapeutic Chemical (ATC) Classification System and Defined Daily Dose (DDD) Index are widely used for drug utilization research.
• Analyzing U.S. prescription data requires a robust classification system capable of handling diverse drug information.

Purpose of the Study:

• To assess the suitability of the ATC/DDD Index for analyzing prescription lists within the United States.
• To determine the extent to which U.S. prescription data can be classified and analyzed using the ATC system.

Main Methods:

• Mapping of RxNorm clinical drugs to the ATC classification system.
• Classification of a large U.S. prescription drug dataset using ATC codes.
• Comparison of prescribed daily doses with the defined daily doses (DDD) from the ATC index.

Main Results:

• A precise mapping was achieved for 64% of 11,422 clinical drugs to ATC.
• 97% of 87,001 RxNorm codes from the prescription dataset were successfully classified using ATC.
• Assessment of prescribed daily doses was feasible for 97% of the analyzed prescriptions.

Conclusions:

• Despite incomplete ingredient mapping, the ATC system covers the most frequently prescribed drugs in U.S. datasets.
• The study confirms the feasibility of using ATC in conjunction with RxNorm for analyzing U.S. prescription data.
• ATC facilitates drug classification and the assessment of prescribed daily doses in U.S. pharmaceutical datasets.