AMR

AMR provides R-based functions to clean, validate, and analyze antimicrobial resistance (AMR) laboratory data using evidence-based rules and reference data to support standardized resistance surveillance and reporting.

Key Features:

• R implementation: Implemented in R for programmatic analysis of laboratory AMR data.
• Data cleaning and validation: Cleans and validates laboratory data from various laboratory information systems.
• Standardized analysis: Applies evidence-based rules aligned with international guidelines for consistent and reproducible analyses.
• First isolate and MDR identification: Determines first isolates and identifies (multi-drug) resistant microorganisms using evidence-based rules.
• Code translation: Translates codes used to identify microorganisms and antimicrobial agents.
• Resistance prevalence and trend projection: Calculates resistance prevalence and projects future resistance trends.
• Reference data integration: Includes scientifically curated reference data for contextualizing laboratory results.
• WHONET compatibility: Compatible with WHONET workflows from the World Health Organization (WHO) for global reporting.
• System independence: Operates independently of specific laboratory information systems.

Scientific Applications:

• Epidemiological studies: Supports epidemiological analyses of antimicrobial resistance by enabling standardized data processing and prevalence calculations.
• Surveillance programs: Facilitates routine surveillance of resistance patterns and trend monitoring.
• Public health reporting and policy-making: Provides standardized metrics and trends to inform public health reporting and policy decisions.
• Laboratory data analysis and reporting: Enables laboratories to clean, validate, translate codes, and analyze AMR testing results for reporting purposes.

Methodology:

Implemented in R; performs data cleaning and validation; applies evidence-based rules to determine first isolates and identify (multi-drug) resistant microorganisms; translates microorganism and antimicrobial agent codes; calculates resistance prevalence and projects future trends; integrates curated reference data and supports WHONET-compatible workflows.