Many online tools are built around generic inputs (injury severity, length of recovery, bills, and broad categories like pain and suffering). That’s fine for education. But for a claim in Sandy, Oregon, the outcome often turns on details that don’t fit neatly into a form:
- Whether the medical record supports a missed diagnosis or a delayed escalation (and when it should have happened)
- How clearly causation is documented—for example, whether later conditions were likely caused by the earlier error
- Whether treatment gaps and follow-up decisions match standard practice
- How the injury changed real-life functioning—work attendance, mobility, sleep, caregiving responsibilities, or ability to manage ongoing care
An AI estimate is best treated like a starting worksheet, not a forecast.


