The perfect storm: AI self-diagnosis isn't just a rural problem

AI self-diagnosis isn't just a rural problem

It would be easy to frame artificial intelligence (AI) self-diagnosis as a problem confined to underserved rural areas or safety-net clinics. Medical Economics asked Rosemarie Aznavorian, D.N.P., RN, CENP, CCWP, CCRN, executive vice president of client services and chief clinical officer at MedPro Healthcare Staffing, whether that holds up.

"Actually, it's all of those,” she said.It would be easy to frame AI self-diagnosis as a problem confined to underserved rural areas or safety-net clinics. Medical Economics asked Rosemarie Aznavorian, D.N.P., RN, CENP, CCWP, CCRN, executive vice president of client services and chief clinical officer at MedPro Healthcare Staffing, whether that holds up. Her answer was straightforward: "Actually, it's all of those."

In rural communities, the drivers are layered. Patients who are uninsured, underinsured or unable to afford copayments tend to delay care until the situation becomes urgent. In larger facilities and urban settings, the dynamic looks different but leads to the same place — patients waiting until they're sick enough to need the emergency department, which is itself tightly staffed and already strained. "All of that compounds the access problem," Aznavorian said.

She was careful to note that no single specialty or setting is driving patients toward AI. The bigger factor, she said, is simply how accessible these tools have become. What concerns her most is preventive care. Primary care physicians and nurse practitioners are positioned to catch hypertension, diabetes and other chronic conditions before they become crises — but in communities where that access is limited, those conditions go undetected. "Many rural areas have underdiagnosed hypertension, diabetes and other chronic conditions that don't show obvious signs and symptoms until they're already impacting activities of daily living," Aznavorian said. By the time patients feel unwell enough to seek answers, AI is often the first place they turn.

In rural communities, the drivers are layered. Patients who are uninsured, underinsured or unable to afford copayments tend to delay care until the situation becomes urgent. In larger facilities and urban settings, the dynamic looks different but leads to the same place — patients waiting until they're sick enough to need the emergency department, which is itself tightly staffed and already strained. "All of that compounds the access problem," Aznavorian said.

She was careful to note that no single specialty or setting is driving patients toward AI. The bigger factor, she said, is simply how accessible these tools have become. What concerns her most is preventive care. Primary care physicians and nurse practitioners are positioned to catch hypertension, diabetes and other chronic conditions before they become crises — but in communities where that access is limited, those conditions go undetected. "Many rural areas have underdiagnosed hypertension, diabetes and other chronic conditions that don't show obvious signs and symptoms until they're already impacting activities of daily living," Aznavorian said. By the time patients feel unwell enough to seek answers, AI is often the first place they turn.