Clinical documentation in electronic health records (EHRs) is necessary for patient care continuity, legal requirements, billing, and compliance. However, many providers complain about the time needed to complete notes, orders, and coding. Studies show that administrative tasks can take up nearly 55% of clinicians’ time in some places. This can make workdays longer, leading to what is called “pajama time,” when clinicians finish documentation after work hours.
The Permanente Medical Group (TPMG) studied how using ambient AI-enabled scribes affected this workload. Over 63 weeks, with more than 2.5 million patient visits and over 7,200 doctors, AI scribes saved about 15,791 hours of documentation time—equal to 1,794 workdays. Doctors said communication with patients got better (84%) and job satisfaction improved (82%). Also, 47% of patients noticed their doctors spent less time looking at computer screens during visits, and 56% thought the quality of the visits got better.
These results show a clear need for solutions that cut down documentation time without hurting patient care or interaction.
Ambient AI means smart software tools that listen to and watch clinical visits, capturing doctor-patient talks and making clinical notes without doctors having to do extra work. Unlike older AI tools that need manual entries, ambient AI works quietly in the background. It connects with current EHR systems to make draft notes, code claims, and handle orders as the visit happens.
For example, Commure Ambient AI is an AI tool used in many U.S. health systems. It automates clinical documentation and tasks like complexity coding and managing billing processes. It uses advanced machine learning and natural language processing based on large language models. It also combines information from EHRs to make sure notes are accurate and complete.
Doctors using ambient AI have said it can cut documentation time by up to 30%. This helps get charts done within 24 hours after a visit, speeding up workflows and billing.
Several health systems have seen real improvements after starting to use ambient AI technologies.
DRH Health: This 128-bed nonprofit regional system added Commure Ambient AI to its MEDITECH Expanse EHR. Doctors saved up to 90 minutes a day on documentation, which helped them finish charts faster and spend more time with patients. Roger Neal, VP and COO of DRH Health, said the solution helped doctors by cutting paperwork and improving note quality.
Val Verde Regional Medical Center: Located in a rural area, this hospital faced staff shortages like many rural hospitals do. After using ambient AI, their providers cut documentation time by 30 to 90 minutes daily in fields like cardiology and family medicine. This not only reduced doctor workload but also improved patient access to care.
Ob Hospitalist Group (OBHG): OBHG used Commure’s coding AI to cut time spent entering charges by 83% in three months. AI now codes more than 85% of charges, improving coding accuracy while following billing rules. This lowered manual work and increased billing efficiency.
Hughston Clinic: This big orthopedic provider used AI across clinical and billing tasks. Linking ambient AI with multiple EHRs improved patient access, documentation accuracy, and billing performance.
North East Medical Services reached almost perfect note accuracy with a 30% cut in documentation time by using ambient AI with their Epic EHR system. These gains helped reduce language problems and improved care coordination for patients who speak different languages.
Besides ambient AI scribes, workflow automation also helps hospitals run clinical and admin tasks more smoothly. AI-driven automation can speed up jobs like prior authorizations, checking eligibility, managing denials, reconciling charges, handling appeals, and engaging patients.
Prior Authorization Automation: This process usually involves a lot of paperwork and delays care and payments. AI can guess likely denials, check if medical rules are met in real time, and prepare documents automatically. Geisinger Health System used over 110 live AI automations and saved many clinical hours, letting staff focus on harder cases instead of routine forms.
Revenue Cycle Management (RCM): AI improves billing tasks like submitting claims, checking eligibility, coding, and appeals. AI helps claims get approved the first time and lowers the time money sits unpaid. OBHG’s use of autonomous coding cut charge entry time and stayed in line with rules.
Patient Engagement and Scheduling: AI cuts no-shows and cancellations by sending timely, personalized reminders using prediction tools. Yale New Haven Health System reported fewer same-day cancellations thanks to AI-based patient outreach.
Clinical Decision Support and Care Navigation: AI programs guide patients through treatment plans, surgery prep, and recovery. Mount Sinai Health System’s work with AI improved joint replacement care by adding therapy tools directly into EHRs.
Medical administrators and IT managers need to make sure AI tools fit securely and smoothly into healthcare systems.
Top platforms like Commure use standard data-sharing methods based on Fast Healthcare Interoperability Resources (FHIR) to connect with different EHRs without disturbing workflows. This helps data move easily and lets AI help during visits in real time.
Data safety and obeying laws are very important. AI systems use encryption and follow HIPAA, SOC 2, and HITRUST rules to protect patient information. Using AI also means training staff and managing change so doctors accept the new tools and work isn’t interrupted.
Healthcare in rural areas faces extra challenges like fewer providers and harder patient access. Ambient AI and workflow automation offer ways to help with these problems.
At Val Verde Regional Medical Center, using AI cut clinician documentation time a lot, so few staff could spend more time caring for patients. By working more efficiently, rural hospitals can better manage limited resources and serve more patients.
AI also supports remote documentation and telehealth, linking doctors with patients in hard-to-reach places, improving record keeping and tracking care better.
Hospitals and medical groups should look carefully at AI tools that fit their technical setups and address clinical challenges they face. Using ambient AI and related automation is a growing trend in U.S. healthcare. It helps cut documentation work and improve clinical efficiency, while also supporting providers and patient care.
Commure Ambient AI automates provider documentation and revenue cycle management, significantly reducing charting and documentation time by up to 30%, allowing clinicians to focus more on patient care and less on administrative tasks.
Commure Agents use advanced natural language processing and full EHR integration to automate complex administrative and clinical tasks, reducing call volumes and wait times by efficiently handling patient inquiries and appointment management digitally.
AI-powered automation in eligibility verification, appeals, denials, and charge note reconciliation optimizes first-pass rates, reduces days in accounts receivable, and speeds reimbursements, driving financial efficiency for health systems.
These co-pilots automate scribing, note creation, coding, and ordering, integrating deeply with existing EHRs to streamline workflows, reduce provider burnout, and increase accuracy with up to 90% zero-edit notes.
Clinicians, like Dr. Lamberty and Dr. Palakurthy, reported up to 25-30% reduction in documentation time, reclaiming work-life balance and gaining valuable time to respond to patient messages and other clinical activities.
By integrating with systems like Epic, Commure Ambient AI achieves near-perfect note accuracy while reducing transcription time, facilitating better care coordination for patients with diverse language needs.
Commure Agents are fully integrated AI assistants leveraging Large Language Models and real-time EHR data to automate complex, mission-critical tasks in a scalable, security-first healthcare environment.
Mount Sinai Health partnered with Commure Engage to create digital navigation programs guiding pre-surgical preparation and recovery, enhancing patient engagement and clinical outcomes through evidence-based protocols.
Yale New Haven Health System’s use of Commure Engage led to swift reductions in no-shows and same-day cancellations via automated, patient-responsive messaging and appointment management.
Strongline EVP technology merges patient, equipment, and environmental data to create smart hospital workflows that enhance caregiver safety, optimize patient journeys, and improve physical operational efficiency.
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