In real healthcare settings, the issue typically isn’t that “AI made a decision.” Instead, the problem often arises from how clinical teams and facilities use automated workflows—for example:
- Triage and risk scoring that routes you to the wrong level of care or delays escalation
- Clinical decision support suggestions that are treated as definitive rather than reviewed critically
- Imaging or lab workflow issues where flagged findings are buried, delayed, or communicated incompletely
- Electronic documentation shortcuts that unintentionally omit symptoms relevant to diagnosis
In Marana, residents commonly interact with a mix of providers and facilities—urgent care visits, emergency department evaluations, outpatient imaging, and specialist follow-ups. Diagnostic errors can happen at any handoff, and the gaps between systems are often where evidence becomes crucial.


