Humans are ancient storytelling machines; computers are binary processors. The friction between the two is where informatics thrives—but not without significant risks.
The Narrative Fallacy: Chasing Ghosts in the Noise
Humans are ancient storytelling machines; computers are binary processors. The friction between the two is where informatics thrives, but not without significant risks.
Humans are masters of Apophenia—the innate tendency to perceive meaningful patterns within random data. This cognitive shortcut helped our ancestors survive because they could spot a predator in the rustling grass; today, we use that same hardwiring to spot “trends” in a noisy EHR dashboard.
When we see a three-day spike in “Length of Stay,” the brain doesn’t see a statistical outlier—it sees a story. We immediately build a narrative: “It was the holiday weekend,” “The new residents just started,” or “The pharmacy interface must have lagged.” We fall in love with the story because stories feel like “actionable insight.” The data might be pure random noise—a standard deviation doing its job—but our brains refuse to accept the true answer:
“I don’t know; it’s just variance.”
The danger of the Narrative Fallacy is that we begin building expensive, complex operational “fixes” for ghosts. We iterate on the technology to solve a problem that never actually existed. When we follow the story instead of the statistics, we aren’t practicing informatics; we’re practicing digital creative writing.
Even the hallucinations of AI aren’t new to medicine—they are just a new way for stories to be told. AI isn’t glitching; it’s just doing what we’ve always done: prioritizing a coherent narrative over a chaotic reality.
The Pitfall: Patternicity
Avoid “Patternicity.” To operationalize this, never present a “trend line” without a baseline for Statistical Significance. If you can’t prove the spike is outside the realm of normal variation, don’t build a story around it. Stop chasing ghosts and start interrogating the noise.