Clinicians often have too much paperwork, electronic health record (EHR) entries, and other administrative tasks that take a lot of time. Nurses, for example, may spend up to one-third of their shifts on scheduling, data entry, and billing. This leaves less time for direct patient care. Doctors face similar problems because documentation for coding, billing, and rules takes a lot of time.
This heavy workload causes many clinicians to feel tired and stressed. This is a common problem, especially with fewer staff available. When healthcare workers get burned out, it can hurt patient care and make hospitals less efficient. Fixing this problem is important to keep healthcare good and easy to get in the future.
Generative AI is a kind of artificial intelligence that can write text or speak based on what it is given. In healthcare, generative AI is used to help create clinical documents, appeal letters, and other medical records automatically. These tools also help with mid-revenue cycle tasks, which means making sure documents are right and ready on time for payments and checks.
One example is Xsolis. They made an AI platform to help clinicians work faster on mid-revenue cycle tasks. The platform helps create appeal letters and documentation for reimbursement. MultiCare Health System, a large healthcare group in Washington state with 13 hospitals and over 26,000 workers, has used Xsolis’ AI tools since 2017. With this platform, MultiCare cut case review times by 150% and saved more than $8 million.
Debbie Schardt, Assistant Vice President of Revenue Cycle and Utilization Management at MultiCare, says the AI lowered administrative work and clinician burnout by a lot. The platform also helps healthcare teams like their jobs better by removing repetitive tasks and making payment appeals faster.
The link between too much documentation and clinician burnout is well known. Clinicians spend about nine hours a week just on documentation. Using generative AI to reduce this work frees up more time for patient care. This is often why healthcare workers do their jobs and what makes their work meaningful.
Healthcare providers and insurance groups see the benefits of AI in cutting down paperwork. In recent surveys, over 90% of people thought generative AI is useful. They see it as a key tool to spend less time on paperwork, have more time with patients, and improve the quality of care.
Besides generative AI, other AI tools help with documentation. Microsoft Dragon Copilot, for example, is used by over 600,000 doctors worldwide. It changes spoken words into clinical notes. This helps reduce the mental work needed for typing and data entry.
Companies like Xsolis combine generative AI with predictive analytics to help make better decisions about medical care and use of resources. Their tool, Dragonfly®, looks at real-time data to give clear scores on medical necessity. This helps make faster and clearer decisions about what level of care patients need and approvals.
This technology also helps reduce delays between healthcare providers and insurance payers. It cuts down on delays with refunds and lowers the work caused by claims being denied. “Human in the loop” AI means that trained clinicians check AI results to make sure they are correct. This keeps clinical judgment strong while using AI to work faster.
These AI improvements have saved over $1.5 billion for health systems and insurance companies together. This shows both money saved and better operations.
AI’s use is not just for clinical documents and appeals. Health systems and medical practices also use AI on front-office tasks to lower administrative work that slows down clinical flow and patient management.
Simbo AI is one example. They use voice AI to automate front-office phone tasks. Their system handles appointment scheduling, prescription refills, patient sign-ups, and insurance checks. By using a virtual AI assistant for calls, medical offices can save on staff costs and improve patient access and satisfaction.
Automated phone systems also help lower no-shows by sending reminders and confirmations. This helps clinics use time and resources better. It improves appointment keeping and balances workloads, which lowers overtime and staff tiredness.
The Cleveland Clinic uses AI scheduling tools to predict busy times and assign staff better. This helps clinics run smoothly and keep their focus on patient care.
Even with good results, using AI in healthcare has challenges. These include high costs to start, trouble fitting AI with old EHR systems, and strict rules about patient data privacy under laws like HIPAA. Strong security like encryption and controlled access are needed to protect health information when using AI.
AI is not perfect. Differences in audio quality, hard medical terms, and complex contexts mean ongoing human checks are necessary. Tools like AWS HealthScribe use smart algorithms to write patient visit notes but still need clinical review for accuracy.
Healthcare experts, like Dr. Eric Topol, advise careful and complete testing of AI before using it widely. This helps keep safety, data quality, and clinical effectiveness steady.
The AI healthcare market in the U.S. is growing fast. It was worth $11 billion in 2021 and is expected to reach $187 billion by 2030. The need for better efficiency, smoother clinical work, better patient results, and more automation drives this growth.
Healthcare leaders, practice owners, and IT managers play key roles in choosing and using AI solutions. Making sure AI tools fit workflow, follow rules, and match staff skills is important for success.
Healthcare administrators, practice owners, and IT managers should think carefully about generative AI and automation tools. These tools can help lower documentation and administrative work that causes clinician burnout and less job satisfaction.
Using AI platforms like those from Xsolis and Simbo AI can improve efficiency, save money, and raise care quality. Real cases like MultiCare Health System show what savings and gains are possible with these technologies.
As healthcare changes, staying informed about AI tools—their pros and cons—will help organizations manage digital changes while still meeting patient care and legal standards.
By using AI tools made for healthcare workflows, medical groups in the U.S. can better handle clinician workload, cut down administrative work, and keep patient care as the main focus. This move to AI-driven documentation and automation is a step forward in dealing with the challenges faced by healthcare today.
The generative AI solution aims to improve clinician efficiency during the mid-revenue cycle by streamlining documentation processes for appeals, thereby expediting financial relief to health systems.
MultiCare Health System will utilize the solution to enhance clinician documentation, speed up the creation of appeal letters, and ensure adherence to health plan filing deadlines for appropriate reimbursements.
Since implementing Xsolis’ AI platform, MultiCare has decreased case review times by 150% and saved over $8 million through enhanced operational efficiencies.
Clinicians currently spend about 28 hours a week on administrative tasks, with nearly 9 hours dedicated to documentation, contributing to burnout; the AI solution aims to alleviate these burdens.
Over 90% of surveyed providers and payers view generative AI positively, particularly regarding its potential to reduce administrative tasks and improve patient care time.
Xsolis employs ‘human in the loop’ AI practices to enhance medical necessity decision-making, ensuring that AI solutions are developed with clinician insights for better accuracy.
Dragonfly uses real-time predictive analytics to assign objective medical necessity scores and assess care levels, thereby improving operational efficiency in healthcare systems.
Xsolis’ existing predictive AI models have collectively saved health systems and health plans over $1.5 billion by streamlining processes and enhancing decision-making.
Xsolis received the ‘Clinical Efficiency Innovation Award’ in the 2025 MedTech Breakthrough Awards Program for its impact on healthcare efficiency.
Joan Butters, CEO and co-founder of Xsolis, was named a finalist for the Entrepreneur Of The Year® 2025 Southeast Award, highlighting her leadership in healthcare innovation.
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