2026 LHIMA Annual Convention
High Stakes, High Standards: Betting on Health Information Excellence
Overview
Wednesday — March 11, 2026
Working remotely can be challenging. This presentation builds skills to enhance social capitol and create group cohesion.
Learning Objectives:
- To create cohesive online work groups
Tara Raue
This session will focus on practical ways to improve revenue cycle performance with an emphasis on denial management and other common revenue cycle challenges.
Learning Objectives:
The participant will be able:
- To actionize practice steps that will improve revenue cycle performance.
- To reduce denials with training and workflow redesign.
- To create a functioning revenue cycle team.
Artificial intelligence is transforming how healthcare organizations approach coding and reimbursement. In this session, attendees will explore how AI-driven insights into payer behavior can inform smarter coding strategies and strengthen financial performance. Learn how leveraging historical claims data improves compliance and accuracy during the coding process, while predictive analytics empowers autonomous coding initiatives to operate with greater speed and precision. Walk away with practical strategies to apply these technologies and elevate your revenue cycle outcomes.
Learning Objectives:
- Attendees will gain valuable insights into how AI can enhance their understanding of payer behaviors, ultimately leading to improved coding strategies and enhanced financial performance.
- Attendees will learn how historical analysis of claims data can enhance compliance during the coding process.
- Attendees will leave with a better understanding of how predictive analytics can supercharge their autonomous coding initiatives.
This presentation will serve to update Health Informatics and Information professionals on current data exchange standards as well as present potential cyber risks. A practical approach to improving interoperability will be discussed. Case studies of cyber threats and breaches will be shared to increase awareness of potential cyber vulnerabilities.
Meredith Magee
Artificial intelligence (AI) is rapidly changing how health information management (HIM) professionals work, offering new ways to save time and boost productivity. Yet many educators and practitioners are unsure where to start. This session introduces four practical, beginner-friendly tools—ChatGPT, Claude, Napkin, and Quadratic—that can be used effectively in both educational and workplace settings.
Through demonstrations and real HIM examples, participants will see how ChatGPT can draft instructional materials and professional communications, Claude can summarize lengthy policies and accreditation documents, Napkin can turn text into clear process flowcharts, and Quadratic can analyze and visualize datasets for reporting and decision-making.
The session will highlight prompt best practices, the importance of verifying and correcting AI outputs, and privacy safeguards such as using de-identified or mock data. Attendees will leave with practical strategies to integrate AI responsibly into their daily work—improving efficiency without needing advanced technical skills.
Learning Objectives:
By the end of this session, participants will be able to:
- Identify four beginner-friendly AI tools (ChatGPT, Claude, Napkin, and Quadratic) and describe their practical applications in HIM education and practice.
- Apply prompt engineering best practices to generate accurate, useful outputs for teaching, reporting, and workflow support.
- Evaluate and correct AI outputs to ensure accuracy, compliance, and professional integrity when integrating AI into daily tasks.
As artificial intelligence (AI) continues to transform healthcare, ensuring the security and privacy of patient data becomes increasingly crucial. This presentation explores the intersection of AI innovation and cybersecurity in healthcare, highlighting both the benefits and risks associated with leveraging AI for patient care. We examine the importance of balancing innovation and security in healthcare, providing evidence-based recommendations for healthcare organizations seeking to harness the power of AI while protecting sensitive patient information.
Learning Objectives:
By the end of this presentation, you’ll be able to:
- Understand AI’s Role in Healthcare: Identify the key benefits of AI in healthcare, including improved diagnostic accuracy, personalized treatments, and operational efficiency. Explain how AI technologies are transforming patient care delivery
- Recognize Security Threats and Vulnerabilities: Describe the unique cybersecurity risks associated with AI-powered healthcare systems. Explain why healthcare data is particularly valuable and vulnerable to cyberattacks. Identify common threat vectors including ransomware, insider threats, and algorithmic bias
- Navigate Regulatory Requirements: Understand HIPAA, GDPR, and FDA compliance requirements for AI systems in healthcare. Explain the legal obligations for protecting patient data and ensuring privacy
- Implement Security Best Practices: Apply a multi-layered security framework to protect AI systems and patient data. Develop data governance policies including access controls, vendor management, and audit procedures. Identify appropriate technical controls such as encryption, network segmentation, and threat detection
- Address Ethical and Privacy Concerns: Evaluate AI systems for transparency, accountability, and bias. Implement privacy-enhancing technologies to protect patient information while enabling innovation. Establish ethical frameworks for informed consent and equitable AI deployment
- Balance Innovation with Security: Design strategies that enable AI adoption without compromising patient data protection. Create a culture of security awareness within healthcare organizations. Develop continuous monitoring and improvement processes for AI security and performance
Thursday — March 12, 2026
Updates from the LHIMA Advocacy Committee. Sharing Advocacy initiative from AHIMA and engagement from Louisiana Component Association.
Explore the latest Medicare regulation changes impacting home health, including PDGM, OASIS-E, compliance risks, and reimbursement updates. Learn strategies to strengthen documentation, reduce denials, and prepare for value-based purchasing and future regulatory shifts.
No details available.
Friday — March 13, 2026
This presentation “Brevity: The Power of Concise Communication” emphasizes that clear, concise communication is a powerful skill in today’s noisy, distracted world. It explores how long-winded messages waste attention, create confusion, and increase costs, while brevity strengthens impact and connection. To achieve this, communicators should map their ideas for structure, use stories to make messages relatable, engage in true dialogue, and reinforce key points with visuals. By adopting these strategies—whether in meetings, conversations, or writing—leaders can cut through noise, deliver memorable messages, and foster stronger understanding.
This presentation has been prepared to educate and empower workers to take care of their mental health through setting professional boundaries in the workplace.
Learning Objectives:
- The attendees will learn about the importance of boundaries in the workplace.
- The attendee will learn how having boundaries in the workplace can prevent and remedy symptoms of burnout.
- The attendee will learn about the health risk and consequences of not having boundaries in the workplace and how to develop them.
- The attendee will learn the impact of self-care on work productivity.
On-Demand Sessions
Health systems often address identity management through one-time cleanups, but lasting success requires a broader strategy. This session will emphasize the importance of clean, reliable data as the foundation for analytics, AI, and value-based care initiatives. Without trusted data, organizations risk inaccurate insights, missed opportunities with advanced technologies, and disruptions to care coordination. To address these challenges, we will highlight how data governance models create accountability, staff training provides the skills, tools, and knowledge for both in-person and remote teams to succeed, and proactive prevention strategies stop duplicates before they occur.
Learning Objectives:
- Understand how sustainable identity practices support analytics, AI, and value-based care initiatives.
- Identify best practices for developing governance structures and training programs that support long-term identity integrity.
- Evaluate key considerations when outsourcing identity management to safeguard sustainability and accountability.
Step into the world of theme park medicine and discover the unique challenges of coding for injuries, illnesses, and emergency care. This session focuses on applying accurate diagnostic and procedural coding, interpreting complex documentation, and maintaining compliance. This session offers a fun and educational look at a variety of scenarios that keep coders sharp, engaged, and confident in their skills.
Learning Objectives:
1. Apply accurate codes to theme park related injuries and illnesses
2. Interpret complex clinical documentation to ensure correct and compliant coding
3. Implement best practices for coding integrity and compliance in unique or challenging scenarios
4. Analyze real world case studies to strengthen critical thinking and problem-solving skills in medical coding
Generative AI is ushering in a new era of innovation across industries, and healthcare stands at the forefront of this transformation. As enterprises strive to turn complex datasets into actionable intelligence, Generative AI provides powerful new methods for data synthesis, automation, and insight generation. This session explores practical strategies for integrating large language models (LLMs) and multimodal systems into healthcare analytics and enterprise architectures. Drawing from real-world implementation experience, the talk highlights how organizations can leverage GenAI to streamline data workflows, enhance predictive accuracy, and enable personalized care—while maintaining privacy, compliance, and human oversight. Attendees will gain a comprehensive understanding of both the architectural and ethical dimensions of Generative AI, with actionable guidance on designing scalable, trustworthy, and human-centered AI ecosystems that drive measurable business and clinical outcomes.
Learning Objectives:
- Understand how Generative AI transforms data intelligence and operational efficiency in healthcare.
- Learn frameworks for integrating LLMs and multimodal AI into enterprise workflows.
- Explore real-world applications of GenAI in healthcare data processing and decision support.
- Gain insights into designing scalable, compliant, and ethical AI systems.
- Discover how to foster human-AI collaboration for sustainable innovation.
Drawing from her experience leading compliance education, Cate will share how to transform audit findings into effective training programs. This session will cover adult learning principles, curriculum development, and strategies for engaging providers and coders alike in coding education that drives measurable improvement.
Learning Objectives:
- Identify key audit findings that signal educational gaps.
- Review audit data and construct a targeted coding/documentation education plan using adult learning theory.
- Discuss methods to evaluate the effectiveness of training programs.
Every piece of information, whether stored in a physical filing cabinet or a digital server, represents both potential value and significant liability. This session tackles the most critical and often avoided aspect of information governance: disposition. We will address the urgency of identifying and eliminating information, both paper and digital, that is no longer required for compliance, operational, or patient care purposes. Keeping unnecessary data, referred to as ROT (Redundant, Obsolete, Trivial), drives up storage costs, degrades analytics quality, and dramatically increases risks associated with data breaches, regulatory penalties, and the burden of legal hold requests. Learn how to transform data reduction from a compliance chore into a powerful strategic driver for cost savings and organizational efficiency.
Learning Objectives:
- Explore ways to identify and justify the disposition of irrelevant paper and digital information (ROT), aligning destruction with organizational retention policies.
- Evaluate and quantify how data reduction lowers cyber risks, improves compliance, and maximizes cost savings and operational efficiency.
- Discover ways to implement defensible procedures to ensure destruction protocols comply with all active legal hold requirements and retention schedules.
AI is impacting all industries, including healthcare, in positive and negative ways. The privacy of information entered into AI software or systems should be a high priority for all privacy officers. If your institution has not addressed AI, or is just beginning to do so, now is the time to push it to the top of the list. Please join this session to learn more about options for doing so in any size organization.
Learning Objectives:
- Discover what you should be looking for to determine where AI is being used by your institution.
- Explore options for creating privacy guard rails while supporting approved uses of AI.
- Establish protocols for privacy reviews prior to initiation of future AI projects.
Sallie Bissette Jara
In late May 2025, the Centers for Medicare & Medicaid Services (CMS) announced an initiative to combat fraud, waste and abuse in Medicare Advantage (MA) plans. CMS accelerated the completion of outstanding Risk Adjustment Data Validation (RADV) audits and launched a significantly expanded round of new audits in September 2025. These audits are meant to ensure the accuracy and integrity of health plan data, with far-reaching consequences for providers, plans and patients.
While many health information professionals are familiar with the Affordable Care Act (ACA) and MA risk adjustment reviews, RADV audits remain relatively new territory for most. After eight years as a limited program, the current administration aims to complete all remaining RADV audits for payment years 2018–2024 by early 2026. The scope of these audits is expanding dramatically: CMS will increase the number of medical records audited per health plan from 35 to 200, and all MA plans—about 550 nationwide—will be required to participate, up from a previous sample of just 65 plans.
This expanded RADV initiative will disrupt established routines for providers and payers. Join us as we outline the new requirements so you can prepare your teams and ensure compliance with CMS regulations.
Learning Objectives:
1. Understand the importance of maintaining accurate records, ensuring all diagnosis data is accurately documented and updated.
2. Realize the significance of providing ongoing training on proper documentation practices, releasing appropriate records, and RADV compliance requirements.
3. Recognize how to create an action plan to identify RADV audits and notify management when they’re received to maintain compliance with CMS regulations.
Jeannie Hennum
This timely session explores how HIPAA privacy and security regulations intersect with the growing use of Artificial Intelligence (AI) in healthcare. With AI technologies like machine learning and large language models rapidly advancing, healthcare organizations must understand how to apply existing privacy and security frameworks—especially HIPAA—to these new tools.
Kelly McLendon delivers a clear, jargon-free overview of AI governance, compliance, and risk management, tailored for health information professionals. The presentation includes real-world use cases, operational strategies, and updates on federal and state regulations, including the anticipated HIPAA Security Rule revisions. Attendees will receive a comprehensive, up-to-date slide deck with references and supplemental resources.
Learning Objectives:
Attendees will learn to:
- Understand HIPAA’s role in AI governance without technical complexity
- Apply HIPAA rules to AI development, use, and vendor selection
- Integrate AI oversight into existing compliance programs
- Identify privacy and security risks in clinical and non-clinical AI use cases
- Explore AI risk management, transparency, and trustworthiness principles
- Prepare for regulatory changes and civil liability concerns
- Access curated resources for continued learning
Course Info
Published Date
April 2026
Total CEs
18.0
Domain(s)
Clinical Foundations
Data Structure, Content and Information Governance
Evolving Topics
Health Law and Compliance
Informatics, Analytics and Data Use
Information Protection: Access, Disclosure, Archival, Privacy and Security
Organizational Management and Leadership
Revenue Cycle Management
Pricing
LHIMA Member
$160
Non-Member
$360
Students
$50
LHIMA Member – an AHIMA dues-paying member who has selected Louisiana as their Component Association (CA)
Non-Member – includes AHIMA dues-paying members from other AHIMA Component Associations (CA) as well as AHIMA Credentialed Non-Members
Speaker
Name
Additional Information
AHIMA
This educational offering has been approved for continuing education credit for use in fulfilling the continued education requirements of the American Health Information Management Association (AHIMA).
AAPC
CEUs are accepted from programs sponsored by AHIMA national offices and the state or regional AHIMA branches. One hour of instruction is worth one CEU. A certificate of attendance or completion is necessary to show participation.
ACDIS
AHIMA CEUs that are CDI-related are accepted.
Register
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Registration will close at 11:59 PM CT on December 31, 2027.
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You will have 60 days to access the course after access has been granted.
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You must click on the button labeled “Mark Complete” at the bottom of each course page before the CE will appear on the My Certificates page.
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- You must click on the button labeled “Mark Complete” at the bottom of each course page before the CE will appear on the My Certificates page.
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Course Content
Course Includes
- 22 Lessons
- Course Certificate
