AI+ Healthcare Administrator™
Transform Healthcare Management with Intelligent Administration
This course focuses on building operational excellence by exploring how AI streamlines billing, scheduling, claims management, and staff workflows to reduce administrative burden. It develops expertise in resource optimization through predictive analytics, demand forecasting, and data-driven decision-making for more efficient hospital operations. Learners will also gain a clear understanding of compliance and privacy, covering regulatory frameworks, data security, and ethical standards essential for AI-powered administration. With a leadership-oriented approach, the course equips participants to confidently drive organizational change, from digital record-keeping to optimized patient flow and cost control.
Enrollment Fee:
MUR 5,980
What You'll Learn
1.1 Understanding of AI
1.2 AI in Healthcare Operations
1.3 Case Study
1.4 Hands-On: No-Code AI-Based Chest X-ray Classification for COVID-19 and Lung Conditions Using Google Teachable Machine
2.1 Understanding Healthcare Data Types
2.2 Using Data for Decisions
2.3 Case Study 1: Apollo Hospital’s AI-Based Discharge Management System
2.4 Case Study 2: Cleveland Clinic’s AI Integration for Medical Billing Optimization
2.5 Hands-On: No-Code Exploration of a Hospital Analytics Dashboard Using Vizly.ai
3.1 Streamlining Patient Flow and Resource Optimization
3.2 Inventory, Maintenance, and Procurement
3.3 Case Study 1: AI-Powered Emergency Interhospital Transfers
3.4 Case Study 2: AI for Inventory Waste Reduction in Hospital Supply Chains (Mayo Clinic, Cleveland Clinic & Rush University)
3.5 Hands-On: AI-Driven Hospital Operations Optimization: A No-Code Predictive Interface Using Julius AI
4.1 Foundations of NLP and Chatbots
4.2 Writing and Communication Tasks with Generative AI
4.3 Case Study: Alleviating Physician Burnout via Clinical Documentation Assistance
4.4 Hands-On: Meeting Summarization Assistant for Healthcare Admin
5.1 AI in Medical Coding and Documentation
5.2 Claims Management and Fraud Detection
5.3 Hands-On: No-Code AI-Powered Medical Claims Denial Prediction
6.1 Identifying Bias in Administrative AI Tools
6.2 Legal & Compliance Considerations
6.3 Case Study: AI Triage Failure and Legal Exposure at North Bridge Hospital
6.4: Hands-On: Analyzing Hospital Admission Bias with Claude AI
7.1 Assessing AI Tools for Quality and Relevance
7.2 Implementation Planning and Procurement
7.3 Case Study 1: AI-Powered Cancer Detection at Tata Memorial Hospital
7.4 Case Study 2: AI-Powered Eye Screening by Forus Health and Microsoft
7.5 Hands-On: Healthcare Data Visualization with No-Code BI Tools
8.1 Understanding Cyber Threats in AI-Driven Healthcare
8.2 Building a Secure AI-Operations Environment
8.3 Case Study 1: WannaCry Attack on NHS (2017)
8.4 Case Study 2: Universal Health Services Ransomware Attack (2020)
8.5 Hands-On: AI Cybersecurity Risk Dashboard Implementation Using Google Looker Studio
9.1 Introduction: Why This Module Matters Now
9.2 Leading Small-Scale AI Pilots
9.3 Identifying Pilot Opportunities in Departments
9.4 Stakeholder Alignment: IT, Compliance, Frontline Staff
9.5 Building Organizational Readiness
9.6 Step-by-Step Guide: No-Code AI for Medical Claim Denial Prediction Using Relevance AI
Prerequisites
- Basic Understanding of Healthcare Systems: Familiarity with healthcare operations and structures.
- Fundamental Knowledge of AI Concepts: Understanding machine learning and AI fundamentals.
- Data Privacy and Security Awareness: Knowledge of HIPAA and data protection laws.
- Project Management Skills: Ability to manage healthcare AI implementation projects.
- Familiarity with Healthcare Software: Experience with electronic health records (EHR) and healthcare platforms.
Exam Details
Duration:
90 minutes
Passing Score:
70% (35/50)
Format:
50 multiple-choice/multiple-response questions
Delivery Method:
Online via proctored exam platform (flexible scheduling)
Unlock Self-Paced Online Learning
- Unlock Self-Paced Online Learning
- Access learning anytime, anywhere, with built-in quizzes to measure progress.
- Enrollment Fee: MUR 5,980