Smarter Patient Care with AI Technology

Results

  • eClinicalWorks® integration with Sunoh.ai: Reduced administrative burdens and improved efficiency in patient encounter documentation with automated medical scribing
  • healow AI-Powered No-Show Prediction Model: Enhanced patient care and outcomes with personalized care plans driven by predictive analytics
  • PRISMA AI: Empowered clinicians with valuable insights through decision support tools
  • AI Assistants: Optimized care delivery and improved patient outcomes by leveraging natural language processing for extracting insights from unstructured data
Dr-Eaton-Med-Peds-Ai-Mashup-NC24-Headshot

“There is such a magic to the whole process by which I can really communicate in such a facile way with the Spanish-speaking patient in a written format. That is just a delight. It really is.”
– Seth Eaton, M.D., MedPeds LLC

Problem

One common problem in healthcare settings is the inefficiency and time-consuming nature of manual note-taking. Healthcare professionals often struggle with the burden of documenting patient information accurately and comprehensively while managing their busy schedules. This manual approach can lead to errors, inconsistencies, and delays in accessing crucial patient data when needed. Additionally, the lack of standardized formats and organization in internal notes can hinder effective communication and collaboration among healthcare team members, potentially impacting patient care and outcomes.

Solution

eClinicalWorks offers a set of AI features aimed at transforming healthcare documentation and decision-making. Through automated medical scribing, healthcare professionals can efficiently streamline patient encounter documentation, alleviating administrative burdens and ensuring accurate records. The platform’s predictive analytics capabilities enable personalized care plans, while decision support tools provide valuable insights. Leveraging natural language processing, eClinicalWorks extracts meaningful information from unstructured data, enhancing data-driven care delivery and improving overall efficiency and quality of patient care.