Many diagnostic errors aren’t caused by “one bad machine result.” In real Farmersville-world scenarios, the problem is often how information was filtered, prioritized, or documented:
- A tool flagged one likely condition but alternative causes weren’t adequately considered.
- Imaging or lab findings were routed or interpreted through automated systems without proper verification.
- Decision support suggested a pathway, and the care team treated it as more certain than it was.
- Follow-up steps were missed because the system didn’t escalate abnormal results quickly enough.
Even if the final diagnosis later proves correct, the legal question is whether the earlier process met the standard of care—and whether the delay or error harmed the patient.


