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Beginnt 6 June 2026 15:46

Endet 6 June 2026

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AI-Driven Electronic Health Records & Data Management

Discover how to integrate GenAI tools into EHR workflows to reduce documentation time, streamline operations, and improve patient care using Glass Health, DoraScribe, and Keragon.
Starweaver via Coursera

Starweaver

2874 Kurse


8 hours 21 minutes

Optionales Upgrade verfügbar

Not Specified

Lernen Sie in Ihrem eigenen Tempo

Paid Course

Optionales Upgrade verfügbar

Übersicht

Clinicians and healthcare professionals are increasingly burdened by Electronic Health Records (EHRs)—navigating complex interfaces, documenting care manually, and missing key insights in siloed data. Generative AI offers a practical path forward.

This course shows you how to integrate GenAI tools into your EHR workflows to reduce documentation time, streamline operations, and improve patient care—without waiting on your EHR vendor. In just 4 hours, you'll move from foundational concepts to hands-on application using tools like Glass Health, DoraScribe, and Keragon.

You’ll explore voice-to-text SOAP notes, AI-generated patient education, no-code automation, and strategies for safe, scalable AI governance in clinical settings. Ideal for physicians, nurses, administrators, and clinical coders, this course equips you to deploy AI responsibly—boosting efficiency, enhancing communication, and laying the groundwork for long-term digital transformation in healthcare.

Lehrplan

  • Course Introduction
  • In this course, you’ll learn how to transform Electronic Health Records (EHR) workflows with Generative AI by automating clinical documentation, enhancing patient communication, and streamlining healthcare operations. You’ll focus on real-world practices such as voice-to-SOAP note transcription, AI-powered patient education, and no-code workflow design with tools like Glass Health, DoraScribe, and Keragon. Through expert instruction, case studies, and hands-on exercises, you’ll gain the skills to reduce documentation time, build scalable AI assistants, and implement governance strategies that ensure safe and effective AI adoption in clinical settings.
  • Introduction & GenAI Readiness for EHRs
  • In this module, you’ll explore why Electronic Health Records (EHRs) need Generative AI support, how leading vendors like Epic, Cerner, and Meditech are embedding AI into workflows, and what it takes to get ready for adoption. You’ll break down common EHR pain points, examine practical AI use cases, and practice foundational prompt engineering. Through expert insights, real-world case studies, and a readiness self-assessment, you’ll gain the skills to evaluate your own environment, build awareness, and set realistic expectations for integrating GenAI into healthcare documentation and operations.
  • Enhancing EHR Documentation & Workflow Efficiency with GenAI
  • In this module, you'll learn how to enhance Electronic Health Record (EHR) documentation and workflow efficiency using Gen AI tools. Through practical demos and exercises, you’ll streamline clinical documentation, automate repetitive tasks, and improve patient-facing content. You will explore tools for structured clinical documentation, ambient scribing, and voice-to-text solutions, enabling you to create accurate and concise clinical notes in real time. The module emphasizes usability, speed, and improving the quality of documentation across healthcare roles, from clinicians to administrators.
  • GenAI-Powered Patient Education, Revenue Cycle Management & Analytics 
  • In this module, you’ll discover how GenAI can transform patient education, revenue cycle management (RCM), and clinical analytics using EHR data. Through hands-on demos and practical exercises, you’ll learn how to use AI tools to create personalized patient narratives, automate billing and coding, and build no-code dashboards to extract actionable insights. The module focuses on enhancing communication, improving operational efficiency, and applying predictive analytics to drive better decision-making in healthcare.
  • GenAI Implementation alongside EHRs, Governance & Sustainability
  • In this module, you’ll gain the knowledge needed to successfully implement and scale GenAI tools alongside Electronic Health Records (EHRs). The focus is on governance, integration, and post-deployment evaluation. You’ll learn about key governance frameworks, bias mitigation strategies, and how to integrate GenAI with EHR systems using standards like SMART-on-FHIR. The module also covers the essential processes for monitoring AI performance and continuous improvement, ensuring a safe, ethical, and sustainable GenAI adoption in your organization.
  • Course Conclusion
  • In this final module, you will synthesize your learning from the entire course and apply it to a real-world challenge involving EHR workflows. You’ll design a GenAI-powered assistant to address documentation, operational, or patient-facing issues. Through this project, you’ll demonstrate your ability to integrate GenAI tools into healthcare workflows while considering governance, risk mitigation, and implementation strategies. This module culminates in a project that showcases your ability to enhance EHR usability, efficiency, and care quality with AI-driven solutions.

Unterrichtet von

Neel Majumder and Starweaver


Fachgebiete

Computer Science