Jefferson Health Is Using AI to Buy Back Clinician Time
The health system is using governed AI to cut administrative work across 23,000 clinicians.
Jefferson Health has tied its artificial intelligence strategy to a single operational goal: returning 10 million hours to patient care. The commitment is tied to a newly announced collaboration with Qualified Health, which Jefferson says will support the development and deployment of governed AI tools across its clinical and administrative workflows.
The collaboration is part of a broader effort by Jefferson Health to reduce the time clinicians spend on documentation and other administrative tasks. Rather than framing AI as a research initiative, the system has positioned it as an operational tool to address daily constraints on care delivery across a large, multi-hospital network.
Those constraints are well defined internally. In an interview with HIMSS TV, Jefferson president Baligh Yehia described documentation as one of the largest drains on clinician capacity. “Our nurses document 40 to 50% of their time,” Yehia said. He added that clinicians “also spend a majority of time documenting,” linking that burden directly to reduced time with patients and after-hours charting.
At Jefferson’s scale, the impact compounds quickly. The system employs more than 23,000 clinicians. Small reductions in documentation and administrative work across that population translate into millions of hours over time. Jefferson leadership has framed the 10-million-hour target as a way to return clinicians to the bedside and reduce work completed outside scheduled shifts.
Using AI to give clinicians time back
Jefferson has already begun deploying AI tools tied to that goal. According to reporting, about 1,300 clinicians across the system are using ambient documentation tools that automatically generate clinical notes from patient encounters. Those users are producing roughly 30,000 AI-assisted clinical notes each week, placing AI inside routine clinical workflows rather than isolated pilots.
The use cases Jefferson is prioritizing are narrow and operational. Yehia described AI being applied to documentation, appointment scheduling, clinical decision support, and the identification of missed screenings such as mammograms or colonoscopies. He also pointed to administrative areas, including call centers and revenue cycle work, where automation can reduce manual effort without shifting clinical responsibility.
The collaboration with Qualified Health aligns with that approach. Jefferson said the partnership will focus on co-developing and deploying AI tools across the enterprise, with attention to clinical workflows, administrative processes, and care gap identification. The announcement does not include financial targets or staffing reductions, instead emphasizing support for clinicians and operational teams through governed deployment.
“Our goal is not to use AI for AI’s sake,” Yehia said. He described technology as a way to remove friction from healthcare work that keeps clinicians from direct patient care. Jefferson’s AI initiatives are framed around reducing low-value tasks rather than expanding automation into clinical decision-making.
Technology alone is not expected to deliver those gains. Yehia compared the current AI push to earlier transitions, including the shift from paper records to electronic health records and the expansion of virtual care. In each case, outcomes depended on changes to workflow and staffing models alongside new tools. “Technology is never the answer alone,” he said. “It’s always around people, process, and technology.”
Governance, access, and the limits of automation
Jefferson put formal governance in place before expanding AI use. The system established an AI Center of Excellence in 2022, bringing together clinical, technical, and operational leaders to review AI tools before they are deployed at scale. The group evaluates safety, bias, and workflow fit, according to Jeffersone.
That structure has shaped how AI is introduced into care delivery. Tools are designed to assist with documentation, information retrieval, and workflow coordination, while clinicians retain responsibility for diagnosis and treatment decisions. Jefferson has described this approach as necessary to maintain consistency and trust as AI use expands across the organization.
Access to care is another driver behind the strategy. Yehia described affordability and access as two of the largest pressures facing healthcare systems. AI, he said, can help surface open appointment slots, improve scheduling, and reduce delays caused by administrative bottlenecks.
Affordability remains part of the context. Yehia pointed to rising healthcare costs for patients and the growing share of national GDP spent on healthcare as forces shaping Jefferson’s priorities. AI is positioned as one tool to make care delivery more sustainable, rather than a standalone solution to financial pressure.
Jefferson has avoided tying its AI strategy to cost savings or headcount changes. Instead, leadership has returned consistently to time as the primary metric. According to the healthcare provider, the 10-million-hour goal gives the system a concrete benchmark to assess whether its AI deployments, and partnerships such as the collaboration with Qualified Health, are changing how clinicians spend their days.