The Hidden Genius of Gladys

Written by: Matt Burger

What Athenahealth Taught Us About Data, Expertise, and the Power of Context

Introduction

Before Athenahealth became a national healthcare technology leader, it almost went bankrupt. The lesson that saved it wasn’t found in data—but in a woman named Gladys.

This essay builds on the account told by Michael Lewis in his podcast *Against the Rules*, Episode “Six Levels Down,” extending its lessons into the modern age of data, software, and AI.

When Jonathan Bush and Todd Park founded Athena Women’s Health in 1997, their mission was clear: deliver better care for at‑risk pregnant women. What they underestimated was not medicine, but the administrative machinery wrapped around it.

American healthcare billing was—and remains—a maze of payer rules, documentation requirements, and opaque explanations of benefits. Athena had plenty of data. What it lacked was understanding.

Enter Gladys

As Michael Lewis recounts, the breakthrough came not from executives or consultants, but from a billing specialist known internally as “Gladys,” identified in the podcast as Sue Henderson.

Gladys was not a technologist or strategist. She was a subject‑matter expert with an accountant’s rigor and a deep sense of fairness. She knew which insurers could be challenged, which rules were flexible, and which denials were simply wrong.

Her value did not come from dashboards or metrics. It came from lived experience—thousands of claims, countless phone calls, and an intuitive grasp of how the system actually behaved, not how it was documented.

She didn’t just process claims. She solved problems.

From Expert to System

Recognizing this, the founders made an unconventional decision: rather than replace Gladys, they decided to learn from her.

Todd Park’s brother, Ed Park—a Harvard‑trained engineer—was brought in to build software that could replicate Gladys’s judgment at scale. What followed was not a simple automation effort, but years of translating tacit human knowledge into code.

According to Lewis’s reporting, it took three to four years to build systems that could match what Gladys did instinctively. The result became the backbone of Athenahealth’s revenue‑cycle platform and the foundation of the company’s survival and growth.

Why Data Wasn’t Enough

Athenahealth did not succeed because it collected more data. It succeeded because it respected context.

Gladys understood the environment—the incentives, the exceptions, the informal rules that governed outcomes. Data provided visibility. Her judgment provided meaning.

The Lesson for AI and Analytics

In an era obsessed with AI and large language models, Gladys’s story is a warning and a guide.

AI can process vast amounts of information and surface patterns at scale. But without domain framing and expert grounding, it risks producing confident answers without understanding—automating noise instead of insight.

The Enduring Insight

The Athenahealth story reminds us that transformation begins by listening to the people closest to the work.

Before there was machine learning, there was Gladys. And she taught the machines how to think.

Source

Michael Lewis, *Against the Rules* podcast, Episode: “Six Levels Down”
https://www.pushkin.fm/podcasts/against-the-rules/six-levels-down