Medical diagnostic errors don’t usually look like a single dramatic “mistake.” In day-to-day practice, the failure often happens through a chain of events—especially when patients are seen in a busy outpatient setting, urgent care style visits, or hospital workflows with multiple handoffs.
In Grenada, common real-world scenarios can include:
- Abnormal test results not acted on promptly after a visit (for example, lab work that should have triggered escalation or follow-up)
- Imaging or report delays—the scan may occur, but the interpretation and communication may lag
- Symptoms that worsen after discharge because the next steps weren’t clearly documented or followed
- Automated tools influencing triage or documentation, where a clinician relies on a risk score or decision support output without fully reconciling it with the patient’s history and exam findings
When AI or automated systems are part of the workflow, the legal question becomes less about whether the tool “was wrong” and more about how clinicians and the facility used it—and whether safeguards and verification steps were followed.


