Automated systems can appear in many parts of care, including imaging review, triage or routing, lab result workflows, and “clinical decision support” tools meant to flag risk. The legal question usually isn’t whether technology was used—it’s how the care team responded to the tool’s output and whether the overall process met the accepted standard of care.
In real Easthampton scenarios, the problem often looks like this:
- A patient presents with symptoms that should trigger additional testing, but the workup stalls after a risk score or automated recommendation.
- A clinician treats an AI-flagged result as definitive even when the patient’s history or objective findings should have required verification.
- Abnormal results aren’t communicated clearly or quickly enough, and follow-up instructions are missed—especially when care spans urgent care visits, hospital stays, and outpatient appointments.


