The AI Health Audit Team
Heidi Fischer M.D. CHCQM
Founder and CEO
Dr. Heidi Fischer is a board-certified physician with decades of experience in clinical practice and health plan management. Passionate about equity and helping others, she has dedicated her career to improving healthcare outcomes through innovative approaches and rigorous standards.
Dr. Fischer holds multiple active medical licenses and is board certified in Anesthesiology, Health Care Quality Management and Physician Advisor (ABQAURP). She has worked to develop AI powered Prior Authorization tools and is certified by Stanford University School of Medicine -AI for Healthcare.
Her extensive experience in utilization management, health plan services, and NCQA/State audits has equipped her with a deep understanding of the healthcare system’s complexities. As Market Medical Director at a large health plan, she led the implementation and strategy of a large-scale Medicaid MCO plan- ensuring compliance with industry standards. She also has experience with Medicare, Medicare Advantage, Commercial, Exchange and PBM.
At AI Health Audit, Dr. Fischer leverages her clinical expertise and AI knowledge to establish rigorous standards for the responsible use of AI in healthcare. By conducting thorough and confidential audits, the organization ensures that AI systems in healthcare are fair, valid, effective, and safe. Her commitment to transparency, preventing bias, and promoting equitable care drives the mission of AI Health Audit.
Dr. Fischer’s commitment to interdisciplinary collaboration and continuous improvement reflects in the organization’s approach to setting industry benchmarks and safeguarding patient welfare.
Bridging Decades of Clinical Expertise with AI Innovation
Clinical Expertise:
- Real-World Insight: Our team has over forty years of clinical experience, providing deep insights into patient care and clinical decision-making. This ensures that AI recommendations are practical and aligned with medical best practices.
- Patient-Centric Approach: Understanding the nuances of patient interactions and outcomes allows us to tailor AI systems to better serve diverse patient populations.
Health Plan Experience:
- Operational Efficiency: With decades of health plan experience, we ensure that AI systems are not only clinically effective but also operationally efficient, optimizing resource allocation and cost management.
- Policy Alignment: Our experts ensure that AI implementations align with health plan policies and regulatory requirements, promoting sustainable and compliant healthcare practices.
AI and Data Science Expertise:
- Decades of experience: Our team boasts a remarkable track record in the field of artificial intelligence and machine learning. Our engineers hold advanced degrees in computer science and currently/have previously held influential positions at leading technology companies such as Meta, AWS/Amazon, Oracle, Sears Holdings, and Nordstrom, as well as multiple innovative tech startups. This diverse background equips them with the expertise needed to drive groundbreaking advancements in AI.
- Advanced Analytics: Our team of AI engineers and data scientists employ the latest techniques to analyze and refine AI algorithms, ensuring high accuracy and performance.
- Bias Mitigation: We focus on identifying and mitigating biases within AI systems to promote fairness and equity in healthcare outcomes.
Data Scientists:
- Role: Analyze and interpret complex data to identify biases and inconsistencies in AI algorithms.
- Skills: Proficiency in machine learning, statistical analysis, data preprocessing, and data visualization. Knowledge of programming languages like Python and R.
Machine Learning Engineers:
- Role: Develop, test, and refine AI models to ensure they perform as intended without introducing bias.
- Skills: Expertise in machine learning frameworks (e.g., TensorFlow, PyTorch), algorithm development, and model validation techniques.
Ethicists:
- Role: Ensure AI systems adhere to ethical standards, focusing on fairness, transparency, and accountability.
- Skills: Strong understanding of ethical principles in AI, ability to assess the societal impact of AI decisions, and familiarity with ethical guidelines and frameworks.
Healthcare Professionals:
- Role: Provide domain-specific knowledge to ensure AI systems are clinically relevant and effective.
- Skills: Clinical expertise in relevant medical fields, understanding of patient care processes, and ability to evaluate clinical outcomes.
Regulatory Compliance Experts:
- Role: Ensure AI systems comply with healthcare regulations and standards.
- Skills: In-depth knowledge of healthcare regulations (e.g., HIPAA, GDPR), experience with regulatory audits, and ability to navigate legal requirements.
Software Engineers:
- Role: Implement and maintain the technical infrastructure for AI auditing processes.
- Skills: Strong programming skills, software development experience, and familiarity with software testing and debugging.
Security Experts:
- Role: Ensure the security and privacy of data used and produced by AI systems.
- Skills: Expertise in cybersecurity, data encryption, and privacy-preserving technologies.
Human Factors Experts:
- Role: Assess how AI systems interact with human users, ensuring usability and reducing the risk of human error.
- Skills: Knowledge of human-computer interaction (HCI), user experience (UX) design, and cognitive psychology.
Project Managers:
- Role: Coordinate the audit process, manage timelines, and ensure effective communication among team members.
- Skills: Strong organizational and leadership skills, experience in project management methodologies, and ability to manage multidisciplinary teams.
AI Auditors:
Role: Conduct comprehensive audits of AI systems, evaluating their design, implementation, and outcomes.
Skills: Experience in auditing processes, understanding of AI technologies, and ability to identify potential risks and biases.