What is algorithmic bias in healthcare and why does it matter?

Algorithmic bias occurs when systematic errors in data or model design produce outcomes that unfairly disadvantage particular groups. Sources include training data that under-represents minorities, historical bias in clinical records, proxy variables correlating with protected characteristics, and deployment context mismatches. In healthcare, biased algorithms can perpetuate health inequalities — for example, underperforming on darker skin tones in dermatology or underestimating disease risk in minority populations.