Clinical documentation has always been essential to patient care, capturing everything from histories to treatment plans and enabling critical downstream functions like coding, billing, and reporting. But as expectations and data requirements have increased, so has the documentation burden on clinicians. Even with the support of electronic health records (EHRs), the volume and complexity of inputs can take valuable time away from patient care. Artificial intelligence (AI) is helping shift that balance by introducing new tools that ease the load, improve accuracy, and give clinicians more time for what matters most.
And according to C. Becket Mahnke, MD, CMIO of Confluence Health, the impact is already being felt:
“We created a Teams channel for the 25 users [of our ambient documentation tool] … It is the most chatty group I’ve ever seen. They answer each other’s questions and they’re giving each other tips. And they’re sharing recordings of what they’re doing. It’s an experience I’ve literally never had. This has been such a transformative technology.”
The excerpt below from our recent eBook explores how AI is reimagining clinical documentation – from ambient notetaking to smarter summarization and coding.
Clinical documentation
Clinical documentation at-a-glance
Clinical documentation is an essential tool for healthcare providers as it forms the foundation of a comprehensive record used to detail and inform patient care. The precise accounting of patient information, including medical histories, symptoms, and treatment plans, is also used to support downstream initiatives such as billing and coding, population health reporting, and analytics. Unfortunately, a host of factors, from burdensome regulatory requirements to inconsistencies in terminology and documentation make this critical point-of-care task an ongoing challenge for many.
AI in action
A large-scale study on ambient AI scribes demonstrated their effectiveness in reducing clinical documentation burdens and improving patient interactions. Conducted across a multidisciplinary physician group, the study assessed the technology’s ability to transcribe real-time clinician-patient encounters and generate structured clinical notes. In just ten weeks, 3,442 physicians used the technology in over 300,000 patient encounters. Physicians reported spending less time on documentation and more time engaging with patients. The AI-generated notes received an average quality score of 48 out of 50, highlighting the scribes’ accuracy, though physician oversight remains necessary for consistency and reliability.
How AI is being applied
AI is transforming clinical documentation, automating tedious tasks, saving clinicians time, and allowing them to focus more on patients instead of process. AI is being used for:
Automated transcription and note-taking
Ambient AI voice recognition systems can turn conversations between clinicians and patients into structured medical notes.
EHR integration and data extraction
AI can streamline the cumbersome process of entering, retrieving, and organizing clinical data in the EHR.
Contextual summarization
Lengthy clinical documentation and interactions can be quickly summarized with AI to produce concise, meaningful notes.
Clinical coding
AI can take on the time-consuming task of assigning medical codes for billing and compliance, minimizing errors and accelerating revenue cycles.
