The perfect storm: Staffing is the answer, but sicker patients are raising the stakes

Staffing is the answer, but sicker patients are raising the stakes

Solving the artificial intelligence (AI) self-diagnosis problem may ultimately come down to something more fundamental: putting enough nurses in the building. 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 better staffing is the most immediate lever for slowing patient reliance on AI health tools. "Staffing is really, really critical," she said.

Her point goes beyond the ratio debates that dominate policy discussions. The number of nurses a unit needs on a given shift depends less on patient headcount than on how sick those patients are. A floor full of patients preparing for discharge has different demands than one carrying post-surgical cases, telemetry patients and ICU step-downs. Mandated ratios, she said, don't always capture that distinction.

The AI trend compounds the problem in a specific way. When patients attempt to manage their conditions at home using AI tools before seeking care, they tend to arrive sicker than they would have otherwise — which means they need more intensive nursing once they do show up.

Aznavorian closed with a framework she developed over nearly five decades in nursing, including a decade as chief nursing officer of a large Texas health system. She calls it the 80/10/10 rule: 80% of a hospital's workforce should be its own permanent staff, 10% should be international nurses and medical technologists on 36-month assignments who integrate into the core team, and the remaining 10% should be short-term travelers covering leaves, new service lines or staffing gaps during hiring. When vacancies push a facility's own staff below that 80% threshold, she said, the balance of international and short-term staff has to shift accordingly.

Her broader message to hospital leaders is to treat staffing companies as partners rather than a last resort. "What's the risk if you don't have enough nurses or medical technologists?" she said. "You won't have the revenue because you can't provide care for the patients." The downstream consequences — missed care, falls, poor outcomes, regulatory scrutiny from The Joint Commission and CMS — make understaffing a strategic risk, not just an operational one.