Transforming Clinical Documentation with Real-Time Conversation Intelligence
Our client, a medical practice with multiple doctors and specialists, struggled with the time-consuming nature of medical documentation. Doctors, especially in orthopedics and rehabilitation, were spending large amounts of time writing patient notes, preparing follow-up instructions, and generating discharge summaries. Although they were using an Electronic Health Record (EHR) system, it lacked automation and AI capabilities. As a result, doctors felt overburdened with paperwork, patients experienced delays in receiving their visit notes, and overall clinic efficiency was affected. The client sought an innovative solution that could listen to doctor–patient conversations in real time, automatically generate clinical notes and patient summaries, and integrate with their existing systems while staying fully compliant with healthcare regulations.
SUMMARY
Our client, a medical practice with multiple doctors and specialists, struggled with the time-consuming nature of medical documentation. Doctors, especially in orthopedics and rehabilitation, were spending large amounts of time writing patient notes, preparing follow-up instructions, and generating discharge summaries. Although they were using an Electronic Health Record (EHR) system, it lacked automation and AI capabilities. As a result, doctors felt overburdened with paperwork, patients experienced delays in receiving their visit notes, and overall clinic efficiency was affected. The client sought an innovative solution that could listen to doctor–patient conversations in real time, automatically generate clinical notes and patient summaries, and integrate with their existing systems while staying fully compliant with healthcare regulations.
Challenges
Time Drain on Doctors:
Physicians were spending 2–3 hours daily on paperwork, reducing time for patient care.
Unstructured and Inconsistent Notes:
Different note-taking styles created inefficiencies in collaboration and follow-up.
Delayed Communication with Patients:
Patients often left without a clear written summary of what was discussed, leading to confusion.
EHR Limitations:
The existing system required manual data entry and offered no smart features.
Regulatory Compliance:
Any new solution had to be HIPAA-compliant and ensure patient data security.
Implementation Approach
Workflow Mapping
Conducted interviews with doctors and staff to understand documentation pain points.
Prototype Development
Built a pilot for one orthopedic clinic with conversation capture and note generation.
AI Model Training
Fine-tuned AWS Bedrock and Comprehend Medical for healthcare-specific accuracy.
Compliance & Security
Deployed HIPAA-compliant architecture on AWS.
Scalable Rollout
Provided staff training and rolled out to multiple clinics.