4 legal-ethical CE Credit Hour Presentation on Practical, Ethical AI Use in Clinical Practice
Beyond Hype and Anxiety: A Practical Framework for Ethical AI Use in Clinical Practice
Join Dr. Maelisa McCaffery and Liath Dalton for a structured, real-world framework for the ethical, effective, and efficient integration of AI into clinical workflows while upholding HIPAA requirements, ethical standards, and clinical standards of care.
Participants will leave with actionable tools, decision-making frameworks, and implementation strategies to make informed, defensible decisions about AI use in their practice — enhancing efficiency while protecting clinical integrity, client trust, and compliance.
This course is designed to meet requirements for legal and ethical continuing education, with a focus on applying regulatory, ethical, and risk management frameworks to the use of AI in clinical practice.
On-Demand Self-Study Course
Real feedback from the live event:
“Well, count me in as the President of the PCT Fan Club. Every presentation, team member, and presenter is knowledgeable, warm, and sooooo positive. Maelisa and Liath made a great presentation team… I’m sure this won’t be the last AI workshop you offer since the landscape is changing so rapidly. I have such confidence that you all will provide accurate, thoughtful information about all tech innovations related to therapy. You’ve helped me have confidence to keep increasing my tech competencies and look forward to future offerings. This was a comprehensive workshop and I always love the detailed examples Maelisa provides about documentation. Thank you!”
“Very organized, clear explanations, and the handout was very helpful. Thanks!”
“I appreciated the clarity both presenters provided, the examples, and all of the research behind the scenes. I feel more capable of addressing AI usage as well as using it.”
“Excellent training! Because of what I learned, I feel more prepared to incorporate the use of AI in my practice in an ethical and professional manner.”
A structured, real-world framework for the ethical, effective, and efficient integration of AI into clinical workflows while upholding HIPAA requirements, ethical standards, and clinical standards of care.
Artificial intelligence (AI) tools are rapidly entering clinical practice—but most guidance focuses either on possibility or prohibition, leaving clinicians without clear, practical direction for ethical and compliant use.
This course provides a structured, real-world framework for the ethical, effective, and efficient integration of AI into clinical workflows while upholding HIPAA requirements, ethical standards, and clinical standards of care.
Co-presented by Dr. Maelisa McCaffrey (founder of QA Prep and documentation expert) and Liath Dalton (Director of Person Centered Tech), this training bridges compliance, ethics, and clinical documentation practice. It emphasizes practical application, including platform selection considerations, prompt and template design, quality assurance processes, and risk mitigation strategies for both solo and group practices.
Participants will learn how to evaluate AI tools, establish appropriate policies, obtain informed client consent, and implement safeguards that support both privacy and quality care. Participants will develop a clear understanding of what constitutes protected health information (PHI), why most AI-assisted clinical tasks involve PHI, and the critical limitations of de-identification in clinical contexts. The course also addresses the growing reality of client use of AI tools, offering guidance for ethically and clinically integrating these dynamics into therapeutic work.
Includes Supportive Handouts
- Platform-Specific Prompting Guides for AI Supported Clinical Documentation Workflows
- (EHRs: SimplePractice, TherapyNotes, Jane. Dedicated Platforms: Quill, Berries, Blueprint, Mentalyc)
Who is this event for?
This course is designed for solo practitioners, group practice leaders, and group practice clinical staff members. It is also suitable for practices that consist of 100% in-person, 100% telehealth, or a mixture of in-person and telehealth treatment.
In-person Practices
Hybrid Practices
Teletherapy Only Practices
Target Audience:
This course is intended for licensed mental health professionals, including clinical psychologists, counselors, marriage and family therapists, and clinical social workers, as well as other behavioral health professionals providing clinical services.
Level:
Introductory to Intermediate. This course is appropriate for clinicians with little to no prior experience using AI, as well as those seeking to deepen their understanding of ethical, compliant, and clinically sound implementation.
I’ve been watching several of your CE programs and, while I’ve always been impressed with your services, I just have to say, your programs are excellently done with production and content and simultaneously warm and accessible. I really appreciate what you do!
Deidentification and AI
Identify what constitutes protected health information (PHI) and differentiate between informal anonymization and HIPAA-compliant de-identification, including key limitations in clinical contexts.
Key Considerations
Describe key HIPAA, ethical, and state law considerations relevant to AI use in clinical practice.
AI Tool Implications
Evaluate AI tools for appropriateness based on privacy, security, and documentation implications.
Ethical Frameworks
Apply ethical decision-making frameworks to evaluate and implement AI use in clinical practice.
Informed Consent
Explain requirements for informed consent related to AI-use in clinical application assisted clinical services.
Documentation Strategies
Apply strategies for maintaining documentation quality, accuracy, and clinical integrity when using AI tools.
Course Details
4 CE Credit Hour. Self Study
Title: Beyond Hype and Anxiety: A Practical Framework for Ethical AI Use in Clinical Practice
Authors/Presenters: Dr. Maelisa McCaffrey, PsyD; Liath Dalton, Director of Person Centered Tech
CE Length: 4 CE credit hours, legal-ethical
Legal-Ethical CE Hours: 4 legal-ethical CE hour
Educational Objectives:
Participants will be able to:
- Identify what constitutes protected health information (PHI) and differentiate between informal anonymization and HIPAA-compliant de-identification, including key limitations in clinical contexts.
- Describe key HIPAA, ethical, and state law considerations relevant to AI use in clinical practice.
- Evaluate AI tools for appropriateness based on privacy, security, and documentation implications.
- Apply ethical decision-making frameworks to evaluate and implement AI use in clinical practice.
- Explain requirements for informed consent related to AI-use in clinical application assisted clinical services.
- Apply strategies for maintaining documentation quality, accuracy, and clinical integrity when using AI tools.
Syllabus:
Module 1: Setting the Foundation — AI in Clinical Practice
- Overview of AI tools and use cases
- Current landscape and common misconceptions
- AI as part of clinical and operational systems
Module 2: PHI, HIPAA, Ethics & State Law Integration
(Core regulatory foundation)
2.1 Understanding PHI in AI Use
2.2 The Reality of De-Identification
2.3 HIPAA & AI Tools
2.4 Ethical Standards & Clinical Responsibility
2.5 State Law Overlay & Emerging AI Regulations
Module 3: Informed Consent & Client Communication
- Informed consent requirements and considerations
- Client communication and documentation
Module 4: Practice Policies, Boundaries & Technology Controls
- Practice-level policies and safeguards
- Group practice and technology management considerations
Module 5: Documentation Integrity & Clinical Quality
- Maintaining documentation standards and clinical accuracy
- Ethical use of AI in documentation workflows
Module 6: Client Use of AI — Clinical & Ethical Integration
- Clinical and ethical considerations of client AI use
- Integrating client-generated AI content into therapy
Module 7: Practical Implementation — Tools, Prompts & Workflows
- AI tool evaluation and selection
- Workflow integration and prompt design
Module 8: Quality Assurance & Ongoing Risk Management
- Quality assurance processes
- Ongoing monitoring and risk mitigation
Module 9: Case Scenarios & Applied Decision-Making
- Application of frameworks to real-world scenarios
- Clinical, ethical, and compliance decision-making
On-Demand Self-Study
Meet Our Presenters
Presented by
Dr. Maelisa McCaffery, PsyD and Liath Dalton
Dr. Maelisa McCaffery is a licensed psychologist, nail design enthusiast, and multi-passionate entrepreneur. With her business QA Prep, she empowers therapists with training and consultation on clinical documentation. Maelisa focuses on the “why” behind the usual recommendations and encourages clinicians to think outside the box, while also keeping their ethics intact. As a true ENFP, Maelisa aims to make sure all of her endeavors are meeting a need in the community while also allowing for plenty of laughter and fun.
Website/Business Links:
QA Prep https://www.qaprep.com/
Liath Dalton is PCT’s director and a co-owner. Liath is especially passionate about helping therapists be resourced and supported in navigating the security compliance process and identifying the solutions and processes that meet the particular needs of their practices. Liath’s consultation area of expertise is focused on selecting the right combination of services and tech that not only meet the legal-ethical needs of mental health practices, but also the functionality, efficiency, and cost-effectiveness needs as well.
Resources & Citations
- • Abrams, Z. (2023). AI is changing every aspect of psychology. APA Monitor on Psychology, 54(5). https://www.apa.org/monitor/2023/07/psychology-embracing-ai• Abrams, Z. (2024). Addressing equity and ethics in artificial intelligence. APA Monitor on Psychology, 55(3). https://www.apa.org/monitor/2024/04/addressing-equity-ethics-artificial-intelligence• Allen, S. (2023). Improving psychotherapy with AI: From the couch to the keyboard. IEEE Pulse. https://www.embs.org/pulse/articles/improving-psychotherapy-with-ai-from-the-couch-to-the-keyboard/• American Association for Marriage and Family Therapy. (2015). AAMFT code of ethics. AAMFT.American Counseling Association. (2014). ACA code of ethics. https://www.counseling.org/resources/aca-code-of-ethics.pdf• American Mental Health Counselors Association. (2023). AMHCA code of ethics. https://higherlogicdownload.s3-external-1.amazonaws.com/AMHCA/2%20AMHCA%20Code%20of%20Ethics-2020-2.pdf• American Psychological Association. (2017). Ethical principles of psychologists and code of conduct. American Psychological Association.• American Psychological Association. (2025, October 24). Balancing promise and risk: Ethical considerations for GenAI in mental health care. https://www.apaservices.org/practice/ce/expert/ethical-genai-mental-health-care• Bunge, E. L., & Desage, C. (2025). A framework for evaluating mental health artificial intelligence-based conversational agents.Journal of Technology in Behavioral Science.• Dalton, L. (2025). There is no such thing as a de-identified transcript [Audio podcast episode]. Practice Tech Podcast. Person Centered Tech.• Dalton, L. (2025). Turning compliance into a competitive advantage: How HIPAA security and privacy ethics support a thrivingpractice [Conference presentation]. Savvy Practice Summit.• Dalton, L., Higdon, K., & Palmer, M. (2025). De-identified transcripts, AI scribes, and clinical risk [Audio podcast episode]. GroupPractice Tech. Person Centered Tech.• Dehbozorgi, R., Zangeneh, S., Khooshab, E., et al. (2025). The application of artificial intelligence in the field of mental health: A systematic review. BMC Psychiatry, 25, 132. https://doi.org/10.1186/s12888-025-06483-2• Forester-Miller, H., & Davis, T. E. (2016). Practitioner’s guide to ethical decision making (Rev. ed.). American Counseling Association. http://www.counseling.org/docs/default-source/ethics/practioner’s-guide-toethical-decision-making.pdf• McGraw, D. (2013). Building public trust in uses of Health Insurance Portability and Accountability Act de-identified data. Journal of the American Medical Informatics Association, 20(1), 29–34. https://doi.org/10.1136/amiajnl-2012-001303• National Association of Social Workers. (2021). Code of ethics of the National Association of Social Workers. https://www.socialworkers.org/About/Ethics/Code-of-Ethics/Code-of-Ethics-English• National Association of Social Workers. (2021). NASW, ASWB, CSWE & CSWA standards for technology in social work practice. https://www.socialworkers.org/Practice/Informatics/Standards-for-Technology-in-Social-Work-Practice• Office for Civil Rights. (2016). Guidance on HIPAA and cloud computing. U.S. Department of Health & Human Services. https://www.hhs.gov/hipaa/for-professionals/special-topics/cloud-computing/index.html• Office for Civil Rights. (n.d.). Business associates. U.S. Department of Health & Human Services. https://www.hhs.gov/hipaa/for-professionals/privacy/guidance/business-associates/index.html• Office for Civil Rights. (n.d.). Guidance regarding methods for de-identification of protected health information in accordance with the HIPAA Privacy Rule. U.S. Department of Health & Human Services. https://www.hhs.gov/hipaa/for-professionals/privacy/special-topics/de-identification/index.html• Office for Civil Rights. (n.d.). HIPAA Privacy Rule and sharing information related to mental health. U.S. Department of Health & Human Services. https://www.hhs.gov/sites/default/files/hipaa-privacy-rule-and-sharing-info-related-to-mental-health.pdf• Office for Civil Rights. (n.d.). Summary of the HIPAA Privacy Rule. U.S. Department of Health & Human Services. https://www.hhs.gov/hipaa/for-professionals/privacy/laws-regulations/index.html• Office for Civil Rights. (n.d.). Summary of the HIPAA Security Rule. U.S. Department of Health & Human Services. https://www.hhs.gov/hipaa/for-professionals/security/laws-regulations/index.html• U.S. Department of Health & Human Services. (2013). Modifications to the HIPAA Privacy, Security, Enforcement, and Breach Notification Rules under the Health Information Technology for Economic and Clinical Health Act and the Genetic Information Nondiscrimination Act; Final Rule. Federal Register, 78(17), 5566–5702. https://www.govinfo.gov/content/pkg/FR-2013-01-25/pdf/2013-01073.pdf
Accuracy, Utility, and Risks Statement:
This course is designed to provide accurate, current, and practical information regarding the ethical, legal, and clinical considerations of using artificial intelligence (AI) in mental health practice. Content is based on existing federal regulations (including HIPAA), generally accepted ethical standards, and emerging guidance related to AI technologies. However, laws, regulations, and professional guidelines are evolving rapidly, and requirements may vary by jurisdiction.
The information presented is intended for educational purposes to support clinical decision-making and is not a substitute for individualized legal, regulatory, or clinical consultation. Participants are responsible for determining the applicability of course content to their specific practice setting, licensure requirements, and client populations.
While the course provides frameworks and strategies to support ethical, effective, and compliant use of AI, improper application of AI tools may introduce risks, including but not limited to breaches of confidentiality, inaccurate documentation, over-reliance on automated outputs, and potential impacts on clinical judgment and quality of care. Participants are encouraged to apply critical thinking, professional judgment, and appropriate safeguards when considering the use of AI in practice.