A new book by Thomas E. Zordani, Classification: How an Insured Patient Was Made Self-Pay—and Took on Mayo Clinic and Won, will be released on November 1, 2026, detailing his experience as a patient who was unexpectedly classified as self-pay and his subsequent investigation that resulted in a consumer fraud finding against Mayo Clinic. The book is based on Zordani's personal experience and the extensive records he gathered, offering a rare inside look at how a complex healthcare system's classifications and processes can affect patients.
Zordani, a systems-risk analyst with nearly three decades of experience analyzing organizational systems, benefits, compliance, and risk, began his Mayo Clinic experience as a patient in early 2024. A serious neurological condition had progressively disrupted his ability to work, think, and communicate with the precision his career required. Before traveling from Denver to Arizona for an April 3 appointment, Zordani provided Mayo with his insurance information and hundreds of pages of medical records, and was told the organization was "good to move forward." However, when he arrived, he was directed to the Business Office and told he would not be seen unless he paid a $5,000 pre-service deposit. He left without receiving the evaluation he had traveled to obtain.
The next morning, Zordani found an estimate in his Mayo patient portal showing an expected patient cost of $565, with his coverage identified as "Self-Pay." He had active insurance, had provided it to Mayo, and intended to use it. This discrepancy prompted Zordani to apply the analytical skills he had spent his career developing. "My work taught me that when an outcome does not make sense, you do not stop at the outcome," Zordani said. "You trace it backward—through the people, the process, the classifications, the information and the decisions—until you understand where the result was produced."
What began as a spreadsheet evolved into what Zordani calls a "legal genome"—a detailed investigative map linking dates, people, departments, insurance activity, internal notes, telephone records, estimates, and legal positions. This framework allowed him to test chronology, identify contradictions, and trace how information moved through Mayo's systems. One key discovery was a recording of a 2023 call Zordani did not remember making. "I was listening to my own voice in a conversation I had no memory of," he said. "It showed me how badly my condition had affected me—and it taught me something equally important: memory was not enough. I had to follow the evidence."
From that point forward, source records became the benchmark. As more records emerged, the investigation moved beyond individual conversations and into the architecture of the account itself: insurance eligibility, patient classification, internal notes, financial estimates, disputed communications, and the downstream consequences of information moving through different parts of a complex healthcare system. The investigative imbalance was stark—Mayo possessed the systems, employees, internal records, and institutional history, while Zordani had only the evidence he could gather from the outside. Despite that imbalance, Zordani continued building the record while working with a small Arizona legal team. The dispute eventually reached arbitration, resulting in a finding of consumer fraud against Mayo Clinic.
"I cannot undo what happened to me," Zordani said. "But if showing exactly how I reconstructed it helps someone else recognize when the pieces do not fit, then the investigation has value beyond my own case." The book is positioned to resonate with patients, healthcare administrators, and policymakers alike, as it examines broader healthcare, consumer, and systems issues. Zordani's work focuses on tracing visible outcomes back to the rules, processes, classifications, and decision structures that produced them. Classification will be released on November 1, 2026.
