The workforce math in healthcare doesn’t work. It hasn’t worked for years, and the gap between clinical demand and available talent isn’t closing. Most health system leaders are managing that reality through recruitment, retention programs and compensation adjustments — all necessary, all insufficient on their own.
Imran Qadeer, MD, president and CEO of Allegheny General Hospital, is approaching it differently. The Pittsburgh-based hospital — part of Highmark Health’s Allegheny Health Network — spent 2024 and 2025 deploying AI not as a technology initiative, but as a time-recovery strategy. The premise is if you can’t hire your way out of a staffing shortage, you can at least give your team hours back in their day to focus on direct patient interaction.
Results-driven AI
The centerpiece of Allegheny General’s AI deployment is Care.ai, a proactive detection system built around cameras installed in patient rooms. The technology continuously monitors vital signs, activity levels and behavioral indicators — catching subtle changes that might otherwise go unnoticed at the bedside.
But the most immediate operational impact has come from virtual nursing.
Allegheny General is using Care.ai to have virtual nurses handle patient admissions and discharges, historically two of the most time-intensive tasks in a nurse’s shift. The result is an average of 50 minutes saved per nurse, per shift. The system is also deploying virtual sitters through the platform, freeing bedside nurses and patient care technicians to focus on higher-acuity patients while virtual staff handle monitoring.
Running in parallel is an ambient listening deployment through Abridge, the voice-to-text clinical documentation platform that’s becoming a fixture in academic medical centers. The impact at Allegheny General mirrors what’s being reported across health systems that have gone live: one to two hours of saved time per clinician per day.
“These initiatives offer a transformative approach to healthcare delivery by leveraging artificial intelligence,” said Dr. Qadeer. “These solutions aim to optimize workflow, enhance patient safety and free clinicians to focus on direct patient interaction.”
The downstream effects extend beyond time savings. More accurate documentation means better communication across interdisciplinary teams, fewer errors tied to oversight or miscommunication, and a cleaner billing trail. Dr. Qadeer expects roughly a 5% increase in claim submission accuracy and a corresponding reduction in denials, a hard financial return on top of the clinical benefits.
The burnout argument is harder to quantify but equally important to Dr. Qadeer.
“I believe — and we haven’t measured this yet — but reducing burnout, alleviating documentation burdens and alert fatigue, contributes to a less stressful work environment, potentially reducing clinician burnout,” he said.
The harder problem: Deployment
None of this is easy to execute. Deploying AI at the bedside — in patient rooms, in clinical workflows, in the EHR — requires a level of change management that goes well beyond a software rollout. It takes education, hands-on training for frontline staff and continuous monitoring against the outcomes the technology was deployed to achieve.
“We’re constantly looking at whether the technology is delivering on the promise that it’s set to do,” he says. “We want a very result-oriented launch of these products.”
Healthcare operates with no margin for technology that doesn’t perform. Every implementation carries an opportunity cost — dollars and attention that could have gone elsewhere.
“The hardest thing we’ll have to do in the coming year will likely be making tough decisions regarding resource allocation in the face of ongoing economic pressures and expanding patient needs while simultaneously maintaining our commitment to innovation and growth,” he said. “This will involve balancing competing priorities such as investing in new technologies, expanding crucial service lines, and adequately compensating our dedicated workforce, all within the constraints of a challenging financial environment.”
Allegheny General’s growth strategy runs on two tracks. The first is internal — deepening its position as a regional destination for complex care in neurosciences, cardiovascular surgery, and oncology. The second is AI-specific: Dr. Qadeer wants to build out a center of excellence for AI in healthcare, translating the system’s early deployments into a research and talent magnet.
“Given our success with predictive analytics and AI tools, we have an opportunity to further solidify a position as a leader in applying AI to improve clinical care, operational efficiency and even medical education, attracting top talent and research funding,” he said. “I’m confident that by focusing on these strategic priorities, navigating the challenges effectively and continuing to foster a culture of innovation and excellence, we can achieve significant growth and continue to serve our community at the highest level.”
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