- Medical Cannabis
- Starting January 1, 2025, licensed dispensaries will be allowed to sell medical cannabis, and patients can apply for medical cannabis cards. This indicates a shift in legislation towards the acceptance of medical marijuana, despite it still being illegal at the federal level.
- Vape Products Regulation
- New laws will prohibit retailers from selling vape products that do not have FDA approval or a “safe harbor certification.” As of now, the FDA has only approved a small fraction of vape product applications, suggesting potential limitations for retailers.
- This legislative cycle saw more health-related bills proposed than in previous years, including:
- HB 809, aimed at allowing local health departments to collaborate with schools to implement health curricula, which did not pass.
- HB 309, focusing on hospital price transparency by mandating clear public posting of pricing information by facilities.
- SB 153, concerning prepayment review processes, which was almost passed but shifted to HB 423 focused on Medicaid prior authorizations.
- SB 30 faced challenges related to privacy issues in recovery residences.
- Varying Success Rates: Although many bills were introduced, fewer passed compared to earlier years, indicating potential challenges in legislative agreement or prioritization.
- Midwives and Access to Care: Legislative efforts are ongoing to improve Medicaid coverage for midwifery services and enhance accessibility for birthing facilities.
Safeguarding The Revenue Cycle: Cyber-Resilience Strategies and Lessons from the Front Lines
- The average downtime from cyberattacks is increasing and was 18.7 days in 2023.
- AHA urges hospitals to be ready to run on paper for up to 30 days.
- A 15-hospital Midwest health system was attacked in late 2023, causing:
- 2 weeks of downtime
- Disruption to Epic EHR, internet, and phones
- $4M–$6.5M in remediation costs
- Major issues included:
- Medical record and documentation failures
- Gaps in charge capture and revenue cycle
- Need for additional staffing and consultants
- Financial Impact
- Estimated revenue loss up to $112 million for 4 weeks of downtime
- Charge recovery is slow; coders can review only 15-20 charts/day
- Key challenges:
- Incomplete clinical documentation
- Unstandardized provider records (esp. levels of care)
- Poor backup systems for billing and charge capture
- Underdeveloped continuity plans and disaster recovery
- Recommendations:
- Conduct Cyber Resiliency Assessments: Review disaster recovery, billing, and financial continuity
- Standardize Documentation: Real-time backups and provider training
- Improve Clinical Documentation: Audit compliance, automate and validate
- Strengthen Financial Resiliency: Crisis management teams and updated contingency plans
- Key Takeaways:
- Cyberattacks cause massive disruptions and financial loss
- Gaps in preparedness and documentation systems worsen impact
- Investments in resilience, documentation, and continuity planning are essential
HIPAA Security Rule Gets a Makeover: Let’s Break it Down
- Proposed changes to HIPAA Security Rule update the rule to address changes in the healthcare environment, address common deficiencies, incorporate changes that resulted from court decisions, and clarify elements of the rule.
- All implementation specifications are required. There is flexibility in how they are addressed, but not whether they are met.
- Slide 8 shows an overview of all HIPAA Security Safeguards as they are now, Slide 9 shows them as they are in the proposed rule. Updates include:
- Technology Asset Inventory (Slide 11)
- Patch Management (Slide 15)
- Security Incident Procedures (Slide 16)
- Contingency Plan (Slide 17)
- Compliance Audit (Slide 18)
- Business Associate Contracts and Other Arrangements (Slide 20)
- Access Controls (Slide 22)
- Encryption and Decryption (Slide 23)
- Configuration Management (Slide 24)
- Multi-Factor Authentication (Slide 25)
- Vulnerability management (Slide 26)
- Data Backup and Recovery (Slide 27)
- Information Systems Backup and Recovery (Slide 28)
- The rule is effective 60 days after publication. Organizations must be in compliance 180 days from the effective date.
Winning the Payer Game by Identifying Your Risks in Coding and Billing
- The "Payer Game" Is Complex
- Payers often deny claims even when accurately coded.
- Multiple appeal levels may be required for payment.
- Payment amounts often don't match contracts, requiring follow-up.
- Success Requires Teamwork
- Involves collaboration among providers, coding, billing, CDI, legal, and finance teams.
- Each plays a role in ensuring documentation and coding meet payer standards.
- Common Pitfalls
- Coding inaccuracies (e.g., unspecified diagnoses, missing modifiers).
- Payer-specific quirks (e.g., preference for certain modifiers or codes).
- Missing or ambiguous documentation.
- Failure to meet administrative deadlines (e.g., filing, appeals, re-billing).
- Strategies for Improvement
- Build payer rules into claim scrubbers.
- Understand the top denial reasons and address high-impact ones first.
- Monitor external audit trends (e.g., CMS CERT data).
- Develop provider education, audit tools, and appeal templates.
- Audit Example: DRG 266 (TAVR Procedures)
- Frequent denials due to unclear documentation on heart failure acuity.
- Solution: Education, queries, and targeted coder/provider training.
340B Threats and Next Steps: The Importance of 340B and the Challenges Ahead
- Purpose and Importance of 340B:
- The 340B program provides drug discounts to safety-net providers to support care for uninsured and low-income patients.
- It improves financial stability for FQHCs like FHC, enabling expanded services and access to medications.
- At FHC, 340B revenue supports operations, reduces expenses, and helps provide care for 40,000+ vulnerable patients.
- Challenges Facing 340B:
- Manufacturer Restrictions: Since 2019, 32 manufacturers have limited 340B drug replenishment, especially for contract pharmacies.
- Criticisms: Concerns include rapid program expansion, lack of transparency, and claims that savings aren't passed to patients.
- Political and Media Campaigns: “Dark money” anti-340B campaigns aim to influence state legislation restricting contract pharmacies.
- Legislative Activity: Several states have passed or are considering pro-340B pharmacy access laws; others face heavy lobbying.
- Emerging Threats:
- Manufacturers propose shifting from discounts to rebates, which would increase upfront costs and reduce flexibility for providers.
- This shift threatens the sliding-fee scales and affordability for patients.
- Call to Action:
- FHC urges advocacy at federal and state levels—inviting legislators to see firsthand the impact of 340B and engaging patients and staff in outreach efforts.
Flying at the Intersection: HIM Meets Public Health Through SDOH
- Health is shaped not just by clinical care but also by upstream factors such as housing, income, education, and social support.
- The presentation distinguishes between upstream (root causes) and downstream (symptom-focused) interventions in public health.
- SDOH Screening & Guidance:
- As of January 2024, Medicare-reimbursed providers (hospital) must screen for SDOH in five domains: food insecurity, interpersonal safety, housing, transportation, and utilities.
- Tools like the SIREN screening comparison tables help evaluate and implement effective screening practices.
- Integration with Annual Wellness Visits and HCPCS coding (G0438, G0439) facilitates structured documentation and reimbursement.
- Intersection with Public Health & Accreditation:
- Public Health Accreditation Board (PHAB) standards (e.g., Domain 7) emphasize equitable access to services and continuous quality improvement, aligning HIM work with population health goals.
- Population-level outcomes are tracked via the PHAB Data Portal, which includes data on mortality, social environment, and health-related quality of life.
- Case Study – Martin County, Kentucky:
- EKU supported a Local Needs Assessment (LNA) required by state law (HB 129) to evaluate the health of the community.
- Community forums collected insights on health outcomes, behaviors, clinical care access, and social/economic conditions.
- Top concerns included mental health, substance use, poverty, and food insecurity; key barriers were access to providers, broadband, affordable care, and childcare.
- Social Vulnerability & Community Risk Factors:
- Martin County showed medium-high vulnerability (SVI = 0.6869).
- Risk factors with greatest impact included poverty, lack of job opportunities, substance use, and mental health.
- Community strengths were schools, local clinics, churches, and family support systems, though often underutilized due to communication gaps or systemic barriers.
- The integration of SDOH data and public health principles into HIM practice is essential for advancing equity and improving community outcomes. Structured screening, local data, and cross-sector collaboration are key tools for transforming insight into impact.
- Key Themes
- Patient-Centered Care & Autonomy
- Emphasizes respect for patient preferences, shared decision-making, and personalized communication.
- Autonomy supports better outcomes and more efficient use of resources.
- Length of Stay (LOS) as a Key Metric
- Patient-Centered Care & Autonomy
- LOS impacts hospital efficiency, patient outcomes, and healthcare costs.
- Ideal LOS balances:
- Too short: risk of readmission
- Too long: increased costs, complications
- Value-Based vs. Fee-for-Service Models
- Value-based care focuses on outcomes, not volume.
- LOS optimization aligns with quality-based reimbursement (e.g., Medicare VBP, ACOs).
- Data Methods for LOS Analysis
- Traditional methods (regression, stratification) have limitations.
- Propensity Score Matching (PSM) corrects for confounding variables, enabling more accurate comparisons between patient groups.
- Key Findings
- Prolonged LOS is associated with higher costs and morbidity.
- Shorter, well-managed LOS can improve outcomes and reduce expenses.
- ARMC vs. National Data: ARMC generally aligned with national trends, but improvements are possible in care coordination and fragmentation.
- Advanced Tools & Innovations
- AI and predictive analytics support LOS management and discharge planning.
- Health Information Exchange (HIE) reduces care fragmentation and redundant services.
- Blockchain enhances HIE security and patient data control.
- Equity & Disparities
- LOS disparities exist across race, insurance type, and socioeconomic status.
- Vulnerable populations may face longer stays, worse outcomes, or delayed discharge.
- Recommendations
- Use flexible, personalized LOS guidelines.
- Improve care coordination and discharge planning.
- Promote value-based reimbursement and invest in AI tools.
- Address social determinants of health and disparities.
Less Clicking, More Caring: AI’s EHR Revolution
- The Promise of AI in EHRs:
- AI has the potential to automate medical documentation, diagnostics, and treatment planning, significantly alleviating clinician burnout and enhancing patient care by streamlining workflows.
- Historical Context:
- The evolution of EHR systems has gone through distinct phases, from early experiments in the 1960s to widespread adoption and focus on interoperability in the 2020s.
- Challenges in Healthcare:
- Issues like preventable medical errors, rising costs, and clinician burnout remain prevalent. EHR systems are often cumbersome, with physicians spending around 50% of their time on EHR-related tasks.
- Ethical and Operational Concerns:
- The document discusses important ethical considerations regarding AI's role in decision-making, including:
- The risk of over-reliance on AI reducing human intuition and critical thinking.
- Concerns about bias in AI models, particularly when trained on non-representative datasets.
- Questions around data ownership and patient autonomy concerning AI-driven processes.
- AI Implementation Guidelines:
- AI-powered EHRs must ensure:
- Patient data protection and compliance with regulations.
- Reduction of bias to provide equitable care across demographics.
- Support for, rather than replacement of, human decision-making.
- Technological Benefits:
- Specific features of AI in EHRs highlighted include:
- Automated documentation and voice/NLP-driven charting.
- Predictive analytics for early risk detection and improved patient engagement.
- Patient-Centered Approach:
- Emphasis on integrating self-reported data and improving care recommendations, which fosters a more patient-first approach.
- Need for Trust and Accountability:
- Transparency and accountability in AI recommendations are crucial for gaining the trust of both clinicians and patients, along with secure handling of sensitive medical records.
AI in Medical Coding: The Evolution, Impact and Best Practices in 2025
- Current Challenges in Medical Coding:
- Staffing shortages, inconsistent quality, and changing payer rules are driving delays, denials, and compliance risks.
- Offshore and manual coding methods often result in variability and inefficiency.
- Evolution of Medical Coding:
- Transition from manual coding to Computer-Assisted Coding (CAC) and now to Autonomous Medical Coding, which uses AI technologies like Natural Language Processing, machine learning, and large language models to code medical records with minimal human involvement.
- Technology Overview:
- Nym’s platform provides high-accuracy coding across specialties such as Emergency Medicine, Radiology, and Outpatient Surgery.
- Coders only review flagged charts, dramatically reducing time and improving consistency.
- Ensuring Accuracy:
- Best practices include:
- Customer alignment on coding philosophy
- Technology education to build trust and understanding
- Ongoing auditing to validate performance and compliance
- Case Studies:
- Inova Health: Reduced costs by $500K+, eliminated overtime, and decreased revenue backlog by 50%.
- Genesis Healthcare: Achieved 96%+ coding accuracy, improved job satisfaction, and reduced operational strain.
- Limitations & Best Practices:
- AI tools are not yet a 100% solution—coverage is limited to select specialties and a portion of charts.
- Success depends on organizational readiness, IT infrastructure, cross-functional teams, and governance.
- Checklist for 2025:
- Evaluate technical readiness
- Align coding standards across payers
- Define performance metrics and audit procedures
- Engage stakeholders across HIM, IT, and revenue cycle teams
- Best practices include:
Maximize Impact: Empower CDI and Uncover Every Diagnosis with AI
- AI as a Tool for Clinical Documentation Improvement:
- AI is presented as a powerful resource for CDI teams, aimed at capturing opportunities and alleviating administrative burdens without replacing existing staff or processes. It complements current workflows, especially in a challenging, low-margin healthcare environment.
- Financial Risk Minimization:
- The use of AI can help in second-pass reviews, identifying additional revenue opportunities while managing costs and minimizing financial risks. This ensures that CDI teams can remain effective amidst staffing constraints.
- Augmentation of Existing Workflows:
- AI augments current CDI operations rather than substitute personnel, thereby improving the accuracy and quality of healthcare data
- Comprehensive Review Process:
- The integration of AI facilitates a thorough examination of charts—scanning 100% for revenue and quality issues, which can lead to higher identification rates of key findings
- Educative Functions of AI:
- AI not only aids in operational tasks but also assists CDI teams in learning new clinical concepts and understanding complex situations, ultimately enhancing their expertise and effectiveness.
AI in Prescribing: Navigating Ethics, Risk, and the Physician’s Role
- Enhancement of Physician Role: AI should support and enhance the physician’s role rather than replace it. Physicians must retain control over clinical decisions, using AI as a tool for assistance in decision-making.
- Decision Support: AI in healthcare has the potential to identify risks, optimize treatments, and streamline administrative tasks, particularly in managing controlled substances and reducing misuse. However, AI must support rather than substitute physician judgment.
- Concerns about Bias: AI algorithms risk perpetuating healthcare biases due to limitations in data, including incomplete or biased information, affecting marginalized populations disproportionately.
- Risk Assessment Limitations: AI systems may flag patients as "high-risk" based on historical data, leading to decisions that overlook patient-specific factors and the physician's clinical judgment. This raises liability issues for physicians who may feel pressured to follow AI recommendations over their expertise.
- Need for Thoughtful Use: The rapid development of AI technologies necessitates informed and thoughtful prescribing practices, emphasizing AI as a supportive rather than definitive decision-maker.
- Healthcare Data Interoperability: Effective use of AI in patient care requires improved healthcare data interoperability to ensure that data flows freely between providers, patients, and agencies.
Ethical and Practical Implications: The presentation highlights the ethical, practical, and legal challenges posed by AI in prescribing controlled substances, emphasizing the need for a balance between AI capabilities and physician responsibilities.
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