AI tools typically generate a range based on broad categories and the inputs you enter. The problem is that spinal cord injury cases turn on details that don’t fit neatly into a questionnaire.
In Harrison and surrounding areas, injuries frequently follow patterns tied to real-world travel and work conditions—crash severity, vehicle impact, delay in symptom recognition, and how quickly emergency care begins. Those factors can affect:
- Documented causation (how clearly the medical record ties your current impairment to the incident)
- Functional limitations (transfer ability, mobility, bowel/bladder function, skin risk, medication needs)
- Future care intensity (equipment, therapy cadence, caregiver hours, home/vehicle modifications)
When those details aren’t captured accurately, an AI output may drift too high or too low.


