The Power of SAS Macros in Antibiotics : Data From Inconsistent Inputs to Insightful Outputs
From Contaminated Data to Clinical Clarity: Automating Antibiotics Dataset Cleaning in SAS with Macros 1. Introduction Imagine you are working as a clinical SAS programmer in a pharmaceutical company. A new antibiotics trial dataset lands on your desk. It looks promising patient demographics, drug dosages, outcomes all neatly structured. But the moment you start exploring, reality hits. A patient aged -5 years . Treatment dates occurring before enrollment . Drug names like amoxicillin , AMOX , null , and even blanks representing the same medication. Duplicate patient records with slightly different spellings. Suddenly, your “clean dataset” turns into a minefield. This is not hypothetical this is daily reality in clinical trials. Dirty data is not just inconvenient it is dangerous. It can lead to: Incorrect efficacy conclusions Regulatory rejection (FDA/EMA compliance issues) Misleading safety signals This is where data cleaning becomes a critical scientif...