AI estimators typically work from simplified inputs—injury category, age, and a few assumptions about future care. In real Cheney cases, insurers often focus on details that AI tools can’t accurately capture, such as:
- How the injury affected mobility and transfers (especially for people who relied on stairs, vehicles, or mobility aids)
- Whether bowel/bladder issues and skin risk were documented early
- Whether the medical timeline shows a clear link between the incident and neurological findings
- What Washington providers recommended for ongoing care (and whether those recommendations were followed)
When those pieces are missing—or when the tool assumes they exist—the estimate can swing dramatically.


