A systematic review and meta-analysis identify 22 studies that used various methods to predict colonisation with antibiotic-resistant bacteria at the time of hospital admission. The models were chosen to focus on MRSA and CPO colonisation. The “performance” of these tools varied widely, with a sensitivity of 15–100% and specificity of 46–98.6% for MRSA, and sensitivity of 30–81.3% and specificity of 79.8–99.9% for CPO. I think my main take-away from this that simple risk tools for predicting colonisation with MRSA and CPO (which are often used to determine who to test) are pretty blunt instruments. However, the more advanced tools making use of big datasets and machine learning can take us forward in predicting the risk of MRSA and CPO colonisation at the time of admission.