Saturday, November 30, 2024

New Celebrity Interviews with the Late Michael Parkinson - via AI

Header: In a break from US health news, learn all about the late U.K. broadcaster who is coming back via  AI.

###



Outside of health technology news...

The Economist listed its "Best of 2024," including the category Podcasts, one of which was, "The Rest is Entertainment," in which Richard Osman just discussed his upcoming interview with Michael Parkinson.

Parkinson, as big a figure in the UK as Johnny Carson, Jay Leno, David Letterman in the US, died two years ago at age 88.   

His son, Mike Parkinson, manages the enormous video estate, which now collaborates with an AI company to recreate Michael Parkinson in real time.  Within a few months, an initial series of 8 interviews between AI-Parkinson and Livng-Celebrities will be released.

Read more about it at the sources below.  At bottom, my "AI Corner" discusses.

###

  • Michael Parkinson at Wikipedia.
  • Interview with his son Mike Parkinson here.
  • About the AI project - press release.
  • Coverage at, The Guardian.
  • Episode at "The Rest is Entertainment," Marina Hyde and Richard Osman, here.
    • AI Corner: At this link, two Google-AI voices discuss the news story (here).
    • (Open access, but requires a Google sign-in.)

###



AI Corner

AI discusses the above links [Chat GPT 4o].

##

The Digital Revival: Virtually Parkinson and the AI Reimagining of an Icon

The world of entertainment and artificial intelligence is colliding in fascinating ways, and few projects exemplify this better than the upcoming podcast Virtually Parkinson. An AI recreation of the late Sir Michael Parkinson will host a new generation of conversations, drawing upon the rich legacy of the man once hailed as Britain’s foremost interviewer. This innovative podcast promises not only to entertain but also to spark deeper discussions about the role of AI in preserving cultural icons.

The Concept Behind Virtually Parkinson

The podcast, spearheaded by Deep Fusion Films, will be divided into three parts. First, the guest and host discuss the implications of AI, touching on its capabilities and ethics. In the second segment, the AI version of Michael Parkinson takes the lead, conducting a classic one-on-one interview in the style that endeared him to millions. Finally, the guest and producers debrief, reflecting on the surreal yet thought-provoking experience.

This format allows the project to be more than a nostalgic tribute. It becomes a dialogue about human connection, authenticity, and the evolving interface between technology and culture.

The Making of AI Michael Parkinson

Deep Fusion Films collaborated closely with the Parkinson family and estate to ensure authenticity and ethical boundaries. AI Michael was created using advanced machine learning, trained on thousands of hours of Parkinson's original interviews. The result is an eerily lifelike replication—not just of his voice, but of his pacing, tone, and conversational style.

  • This isn't just a collection of sound bites; it's entirely new content, crafted by the AI in real-time during the interviews. 
  • It’s a cutting-edge way to revisit Parkinson’s style, showcasing his legendary ability to listen, engage, and unearth the most compelling stories from his guests.

Richard Osman and the AI Experience

Richard Osman, the noted author and TV presenter, is set to be one of the first guests on Virtually Parkinson. In a recent podcast, Osman shared his initial hesitation about appearing on the show, describing his unease upon hearing an AI-generated invitation from Michael Parkinson. However, after learning more about the project’s thoughtful approach, Osman reconsidered, intrigued by its potential to explore what it means to interact with an AI personality.

Osman’s upcoming episode will likely highlight the layered experience of conversing with an AI version of a beloved figure. The podcast’s creators hope that moments like these will inspire curiosity and conversation about the intersection of humanity and artificial intelligence.

Ethical Considerations and Legacy Preservation

The Parkinson family played an integral role in shaping this project, ensuring that their father's legacy was honored. Mike Parkinson, Sir Michael’s son, emphasized that the podcast isn’t just a commercial venture—it’s a tribute. The aim is to introduce new audiences to Parkinson’s unparalleled interviewing style while providing a thoughtful exploration of AI's role in storytelling.

The project raises important questions: Should we bring back iconic voices through AI? What are the boundaries of consent and ethical responsibility? The creators’ commitment to transparency—explicitly labeling the AI-generated nature of the host and consulting with the estate—sets a benchmark for similar ventures.

Looking Forward: Entertainment and AI

Virtually Parkinson is not just a podcast; it’s a cultural experiment. As AI continues to evolve, the entertainment industry faces exciting yet complex challenges. This podcast exemplifies how AI can be used to celebrate and extend legacies while prompting necessary debates about authenticity, creativity, and ethics.

Whether you’re a longtime admirer of Sir Michael Parkinson or simply curious about the possibilities of AI, Virtually Parkinson promises to be a landmark in digital innovation. It invites us all to ponder: What does it mean to preserve human legacy in an age where technology can recreate it?



FAQ [Google Notebook LM]

1. What is "Virtually Parkinson"?

"Virtually Parkinson" is a new 8-part podcast series featuring an AI replica of the late Sir Michael Parkinson as the host. The series aims to recreate Parkinson's iconic interview style in conversations with contemporary guests.


2. How does the AI work?

The AI model was developed by Deep Fusion Films. It was trained on thousands of hours of Sir Michael Parkinson's interviews, learning his speech patterns, questioning style, and overall personality. The AI generates new content based on this data, meaning it doesn't simply use snippets of pre-recorded audio.


3. Is this just about using a famous voice for novelty?

While the concept is undeniably attention-grabbing, the podcast has a deeper purpose. It's structured in three parts:

  • Part 1: Discussion about AI and its implications.
  • Part 2: The AI "Michael Parkinson" interviews the guest.
  • Part 3: A reflection on the experience of being interviewed by an AI.

The goal is to explore the evolving nature of human-AI interaction, using the familiar format of a Parkinson interview as a framework.


4. What are the ethical considerations?

The creators are very aware of the ethical complexities of this project. They emphasize four key principles:

  • Informed Consent: The project is fully supported by Michael Parkinson's family and estate.
  • Licensed Data: All training data is legally obtained and licensed.
  • Equal Remuneration: The estate receives fair compensation for the use of Parkinson's likeness.
  • No Passing Off: The podcast clearly identifies the host as an AI replica.

5. How do guests interact with the AI?

The interview is conducted live. The guest hears the AI's questions through headphones and responds in real time, creating a dynamic conversation.


6. Is this a threat to human jobs in the entertainment industry?

The creators argue that this project actually generates jobs. It requires a team of AI specialists, producers, sound engineers, and more to function. It also highlights the potential for AI to enhance and evolve creative processes rather than simply replacing humans.


7. Why is the podcast being made?

There are several motivations:

  • Tribute to Sir Michael Parkinson: The project is seen as a way to honor his legacy and introduce his work to a new generation.
  • Exploration of AI: The podcast provides a platform to discuss and examine the impact of AI on society and human interaction.
  • Entertainment: The creators believe the format can be engaging and thought-provoking for listeners.

8. When and where can I listen to "Virtually Parkinson"?

The podcast is expected to launch in late 2024. Further details regarding the platform and specific release date are yet to be announced.


##


At Google LM, Two AI Voices Discuss the Story


https://notebooklm.google.com/notebook/48076761-8114-49cb-b395-15fea35c87d6/audio


The above audio link is open access but requries a google sign-in.


Wednesday, November 27, 2024

CMS Policy for Artificial Intelligence in Medicare Advantage Operations

On November 26, 2024, CMS released its Part D and Part C (Medicare Advantage) annual rulemaking proposals   In an earlier blog, I discussed the proposed new coverage of anti-obesity medications (AOM) like Wegovy.   

  • In the same rulemaking, Medicare has a section called, "Ensuring Equitable Access to Medicare Advantage Services - Guardrails for Artificial Intelligence."  
  • It's Section 16 and page 13-14 of the inspection copy, and also pages178-185, 362-372, 724 (creating regulation 422.2) .  
    • Section 16 points directly to Biden Executive Order October 30, 2023 (EO fact sheet).     
    • (See also how HHS interprets Section 1557 of ACA, in the context of AI - here.)
    • See Healthcare Dive here.

Here's how CMS summarizes its own MA/AI policymaking, on page 13 of the inspection copy:

Given the growing use of AI within the healthcare sector, such as, but not limited to, AI-based patient care decision support tools, vision transformer-based AI methods for lung cancer imaging applications, and AI and machine learning based decision support systems in mental health care settings, we believe it is necessary to ensure that the use of AI does not result in inequitable treatment, bias, or both, within the healthcare system, and instead is used to promote equitable access to care and culturally competent care for all enrollees. 

As such, we propose to revise § 422.112(a)(8) to ensure services are provided equitably irrespective of delivery method or origin, whether from human or automated systems. 

We also clarify that in the event that an MA plan uses AI or automated systems, it must comply with section 1852(b) of the Act and § 422.110(a) and other applicable regulations and requirements and provide equitable access to services and not discriminate on the basis of any factor that is related to the enrollee’s health status.

###

Perhaps the most interesting thing is something that's not said.   The rulemaking is all about AI in Medicare Advantage, and the idea that AI might improve and coordinate health care claims over in Fee for Service Medicare - MACs - seems to be on the far side of the moon as far as CMS is concerned.  Thre's reference to following historic legacy Part A & B LCDs, not any reference to following groundbreaking innovative AI claims processing from Part A & B.

###

The rules regarding AI in medical review are part of a somewhat broader section on transparency in Medicare Advantage medical review (Section U), with potentially burdensome regulations.   The Biden administration, which proposed these rules, knew it would not be around next spring when they are due to be finalized.  

 ###

AI Corner

  • I fed the pages cited above, into Chat GPT 4o, and asked for an analysis.  
    • I then asked for the likely impression being made on an MA plan that uses AI alot.  
    • I then asked for a comment letter to CMS from such a health plan.

Medicare Advantage (MA) Guardrails for Artificial Intelligence (AI) and Automated Systems: Policy Analysis

Overview of the Policy

The Centers for Medicare & Medicaid Services (CMS) has proposed significant updates to Medicare Advantage (MA) policies to regulate the use of Artificial Intelligence (AI) and automated systems. These revisions stem from concerns over potential inequities and discrimination introduced by algorithmic decision-making in healthcare. CMS aims to ensure that AI systems used by MA organizations promote equitable access to care, comply with anti-discrimination laws, and deliver culturally competent services.

Under the proposed rule, MA organizations must:

  1. Ensure equitable delivery of services, irrespective of whether decisions are made by humans or automated systems.
  2. Maintain compliance with existing statutes, such as section 1852(b) of the Social Security Act, which prohibits discrimination based on health status.
  3. Regularly audit and review AI and automated systems to identify and eliminate biases.

This policy applies to all systems defined as "automated systems," which CMS describes as any computational processes—machine learning, statistical modeling, or other AI techniques—capable of influencing decisions, outcomes, or data collection.


Definition of "Automated Systems"

The proposed rule adopts a broad definition of "automated systems" to ensure comprehensive oversight:

  • Definition: Any system, software, or process that uses computational methods (in whole or part) to determine outcomes, assist decisions, inform policies, collect data, or interact with individuals or communities. This includes AI tools for patient care, risk prediction, diagnosis, and resource allocation.
  • Exclusions: Passive computing infrastructure (e.g., web hosting, domain registration, data storage) that does not influence decisions or actions.

This definition emphasizes the potential societal impact of such systems, particularly on vulnerable populations, and aims to mitigate risks of biased or inequitable care delivery.


Key Legal and Policy Implications

As a law professor specializing in healthcare policy, I see this rulemaking as a landmark regulatory effort with both strengths and weaknesses.

Strengths

  1. Addressing Algorithmic Discrimination: CMS acknowledges evidence showing that AI systems can perpetuate bias. For example, studies indicate that incomplete or biased datasets disproportionately impact marginalized groups. By requiring regular audits, CMS aims to prevent such disparities.

  2. Alignment with Broader Equity Goals: This policy aligns with the Biden administration's Executive Orders on racial equity and the "AI Bill of Rights." It ensures that technological advancements in healthcare support, rather than hinder, equity and access.

  3. Accountability for Third-Party Vendors: MA organizations are held responsible for compliance, even when using AI systems developed by third-party vendors. This avoids loopholes where organizations could disclaim responsibility for biases embedded in outsourced tools.

  4. Transparency: The proposed rules include public posting requirements for internal decision-making tools and coverage criteria, enabling beneficiaries, researchers, and policymakers to scrutinize these systems.

  5. Balancing Innovation with Regulation: By focusing on compliance rather than banning AI outright, CMS fosters innovation while safeguarding patient rights.


Weaknesses or Concerns

  1. Broad Scope of Automated Systems: The definition of "automated systems" is intentionally broad, but it may result in overregulation. For example, simpler tools like statistical models could face the same scrutiny as complex AI algorithms, potentially stifling innovation.

  2. Lack of Specificity in Standards: While the policy emphasizes equity and non-discrimination, it lacks detailed benchmarks for auditing or evaluating AI systems. Without clear standards, enforcement may vary widely, leading to inconsistent compliance.

  3. Resource Burden: MA organizations, particularly smaller ones, may struggle to meet the rigorous compliance requirements, such as regular audits and transparency mandates. These requirements may disproportionately favor larger organizations with more resources.

  4. Unclear Enforcement Mechanisms: While CMS outlines penalties for non-compliance, it does not provide detailed enforcement strategies or timelines. This could weaken the rule's efficacy.

  5. Potential for Data Misuse: Publicly posting internal coverage criteria and algorithms could inadvertently reveal proprietary information, raising concerns about data misuse or intellectual property theft.

  6. Lag in Implementation: The policy is set to take effect in 2026. Given the rapid evolution of AI technologies, this timeline may leave gaps in regulation, especially as new, unregulated AI tools emerge.


Broader Implications for the Healthcare System

The proposed rule reflects a pivotal moment in the intersection of healthcare, technology, and civil rights. While it tackles urgent issues related to equity and AI, it also signals a shift in the regulatory landscape:

  • Precedent-Setting: The rule could influence other federal agencies to adopt similar guardrails for AI in sectors like insurance and public health.
  • Global Impact: By aligning with international frameworks like the EU's AI Act, this policy could position the U.S. as a leader in ethical AI governance.
  • Challenging the Private Sector: The rule pushes private insurers to prioritize equity, which may require significant restructuring of existing AI systems.

Conclusion

CMS’s proposed guardrails for AI and automated systems in Medicare Advantage plans mark a critical step toward ensuring fairness in healthcare. By addressing algorithmic discrimination and emphasizing equitable care, CMS seeks to align technological innovation with civil rights principles. However, the policy’s broad scope, lack of specific enforcement mechanisms, and resource burdens present challenges that will require further refinement.

As legal scholars, it is our responsibility to critically assess these developments, ensuring that regulatory frameworks strike the right balance between innovation, equity, and accountability. These policies will likely shape the future of AI governance in the U.S., making this a case study for both healthcare and administrative law.


##

How would a Medicare Advantage plan that is ahead of the curve on using AI in medical review, and health policy, react to the new proposed rule?  

This health plan is excited about the accuracy and cost savings and efficiency of AI in medical benefit coordination and adjucation.  It doesn't want to turn the clock backward.

A Medicare Advantage (MA) plan that is advanced in using AI for medical review and health policy might have a mixed reaction to CMS's proposed rule. While the plan would appreciate the rule's focus on equitable care and transparency, it would likely express concerns about the additional compliance burdens and potential limitations on innovation. Below is a detailed analysis of how such a plan might react and adapt:


Positive Reactions

  1. Validation of AI's Role in Healthcare:

    • The proposed rule formally acknowledges the growing importance of AI in healthcare decision-making. By regulating rather than banning AI, CMS legitimizes the use of AI tools in Medicare Advantage, which aligns with the plan's forward-thinking adoption of technology.
  2. Opportunity to Demonstrate Leadership:

    • An advanced MA plan would see this as a chance to showcase its AI systems as models of compliance, equity, and efficiency. 
    • This could differentiate the plan in the marketplace, attracting beneficiaries who value cutting-edge technology and transparency.
  3. Support for Equity Goals:

    • The plan may support CMS’s emphasis on reducing bias and promoting equitable access. This aligns with broader healthcare goals and could improve patient outcomes, especially for underserved populations. 
    • Additionally, plans which are already committed to addressing algorithmic bias might welcome this push as a way to level the playing field across their competitors.
  4. Potential to Reduce Long-Term Risk:

    • By addressing biases and complying with regulatory requirements now, the plan could avoid future penalties or reputational damage associated with inequitable or discriminatory AI use.

Concerns and Challenges

  1. Compliance and Auditing Burdens:

    • The plan might find the required audits and reviews of AI systems resource-intensive. Regularly assessing algorithms for biases and publishing internal coverage criteria could divert resources from other priorities, such as expanding services or enhancing patient care.
  2. Transparency Requirements:

    • Publicly posting decision-making criteria may reveal proprietary information about the plan’s AI tools, potentially exposing trade secrets or intellectual property to competitors.
  3. Balancing Cost Savings with Equity:

    • While the plan values AI for its efficiency and cost savings, addressing biases in algorithms may reduce some of those efficiencies. For example, eliminating biased data inputs could require retraining AI systems with more diverse, higher-quality datasets, which is expensive and time-consuming.
  4. Increased Oversight of Vendor Systems:

    • If the plan uses third-party AI vendors, it would now be responsible for ensuring those systems comply with CMS regulations. 
    • This adds a layer of complexity, as the plan must audit vendor algorithms and ensure their compliance. [See also my November 14 blog re: other HHS regulations re hospitals rather than health plans.]
  5. Risk of Overregulation:

    • The broad definition of "automated systems" might result in overregulation, creating unnecessary barriers for relatively simple AI tools. The plan might argue for clearer distinctions between different types of AI systems to reduce unnecessary oversight.

Strategic Adjustments

To adapt to the proposed rule, the MA plan would likely undertake the following steps:

  1. Strengthening Compliance Infrastructure:

    • The plan would establish robust systems to audit AI algorithms, document decision-making processes, and ensure compliance with anti-discrimination rules. This could include hiring equity-focused data scientists or compliance experts.
  2. Proactive Transparency:

    • Rather than resisting transparency requirements, the plan might develop user-friendly ways to communicate how AI tools support equitable and efficient care. This could involve creating public-facing materials that explain the algorithms in plain language.
  3. Collaborating with CMS:

    • The plan could actively engage in the public comment process to suggest practical modifications to the rule. For example, it might advocate for clearer standards for identifying and mitigating bias or propose tiered requirements based on the complexity of AI systems.
  4. Enhancing Vendor Oversight:

    • If the plan relies on third-party AI tools, it would establish stricter vendor management protocols, including regular audits and requirements for vendors to provide bias assessment reports.
  5. Marketing the Benefits of AI:

    • The plan could leverage its compliance with the new rules as a marketing point, emphasizing that its AI systems not only save costs but also promote equitable, culturally competent care.
  6. Piloting New AI Models:

    • The plan might pilot alternative AI models or datasets designed to meet CMS equity goals. For instance, using more diverse training datasets or implementing explainable AI tools that provide clear, actionable insights without sacrificing accuracy.

Balanced Position

While the plan may view some aspects of the rule as burdensome, it would likely recognize the long-term benefits of aligning with CMS’s equity and transparency goals. By proactively addressing potential challenges and positioning itself as a leader in responsible AI use, the plan could turn compliance into a competitive advantage.

The key for the MA plan will be to strike a balance between innovation and regulation—leveraging AI’s accuracy and efficiency while meeting CMS’s expectations for equitable, non-discriminatory care delivery.


##

Provide a comment letter on this proposal, written by the SVP for Government Affairs of a large national health plan that is  ahead of the curve in using AI to improve efficiency, care coordination, and claims processing.


Administrator Chiquita Brooks-LaSure
Centers for Medicare & Medicaid Services (CMS)
Department of Health and Human Services
7500 Security Boulevard
Baltimore, MD 21244-1850

Subject: Comments on Proposed Rule CMS-4208-P – Guardrails for Artificial Intelligence and Automated Systems in Medicare Advantage Plans

Dear Administrator Brooks-LaSure,

On behalf of [Health Plan Name], one of the nation’s largest Medicare Advantage (MA) organizations, I am writing to provide comments on the proposed rule CMS-4208-P, which includes new requirements and guardrails for the use of Artificial Intelligence (AI) and automated systems in Medicare Advantage plans.

[Health Plan Name] has been at the forefront of integrating AI into care coordination, medical review, and claims processing. We are committed to using AI responsibly to enhance efficiency, improve member experiences, reduce healthcare costs, and promote equitable care. While we appreciate CMS’s focus on equity and non-discrimination, we are deeply concerned that the proposed policies are overly broad, impose significant compliance burdens, and may inadvertently hinder innovation in ways that are ultimately detrimental to beneficiaries.


General Support for Equity Goals

We share CMS’s commitment to ensuring that all MA beneficiaries receive equitable, culturally competent care. AI has tremendous potential to address disparities by analyzing complex data patterns, identifying gaps in care, and enabling earlier interventions. For example, our AI-powered care coordination tools have flagged undiagnosed chronic conditions among vulnerable populations, connecting members with critical services.

We also support CMS’s emphasis on transparency and accountability. Ensuring beneficiaries and providers understand how decisions are made is essential for building trust in AI tools. However, we believe that the current proposal risks undermining the very goals of efficiency and equity that AI is uniquely equipped to advance.


Key Concerns with the Proposed Rule

  1. Overly Broad Definition of "Automated Systems"
    The proposed definition of "automated systems" as “any system, software, or process that uses computation...to determine outcomes or assist decisions” is too expansive. This definition includes not only advanced AI models but also simpler tools, such as statistical algorithms or basic decision-support systems.

    Recommendation: CMS should refine the definition to distinguish between high-impact AI systems (e.g., machine learning algorithms used for predictive analytics) and low-impact tools (e.g., rule-based decision engines). Tailoring regulatory requirements to the complexity and risk level of the system would prevent unnecessary compliance burdens while maintaining safeguards for equity.

  2. Transparency Requirements Create Intellectual Property Risks
    Requiring plans to publicly disclose internal coverage criteria and the rationale behind AI-based decisions risks exposing proprietary information. Many AI tools rely on advanced, trade-secret algorithms developed at great expense. Public disclosure could inadvertently allow competitors or third parties to reverse-engineer these tools, discouraging future investment in innovative technologies.

    Recommendation: CMS should implement transparency requirements that protect proprietary information while still enabling beneficiaries and stakeholders to understand decision-making. For example, plans could disclose the general principles and objectives of their AI systems without revealing detailed algorithms or training data.

  3. Compliance and Auditing Burdens
    The proposed requirement for ongoing audits of AI systems and data inputs would impose significant administrative and financial burdens on MA organizations, particularly those that already adhere to best practices. These requirements may deter smaller plans from adopting AI tools, reducing competition and innovation.

    Recommendation: CMS should adopt a risk-based approach to audits, focusing compliance efforts on systems with a higher likelihood of bias or inequity. Low-risk systems that have demonstrated accuracy and fairness through initial validation should not require frequent re-auditing.

  4. Stifling Innovation
    By imposing sweeping and ambiguous restrictions on AI, the proposed rule risks discouraging plans from pursuing innovative uses of technology. AI has delivered measurable benefits to our members, including faster claims adjudication, reduced administrative burdens, and proactive care interventions. Over-regulation may slow progress and harm beneficiaries by delaying these advancements.

    Recommendation: CMS should establish a framework that encourages innovation while ensuring accountability. This could include pilot programs or regulatory sandboxes for testing new AI tools under CMS oversight before broader implementation.

  5. Lack of Clarity on Bias Mitigation Standards
    While the rule emphasizes the need to address bias in AI systems, it does not specify how plans should measure or mitigate bias. This creates uncertainty and could lead to inconsistent interpretations of compliance requirements.

    Recommendation: CMS should collaborate with stakeholders to develop clear, evidence-based standards for bias detection and mitigation in AI systems. These standards should include practical guidelines for collecting diverse datasets and conducting fairness testing.


Proposed Path Forward

Rather than treating AI as a potential liability, CMS should embrace its transformative potential. We urge CMS to:

  • Promote Responsible Innovation: Incentivize plans to adopt AI tools that have demonstrated value in improving care delivery and addressing disparities.
  • Encourage Industry Collaboration: Work with MA organizations, technology developers, and researchers to create practical guidelines for AI governance.
  • Adopt Flexible Regulations: Recognize the diversity of AI systems and tailor oversight to their complexity and impact on beneficiaries.

We also recommend that CMS include a phased implementation timeline to allow plans to adapt their AI systems and compliance processes to meet these new requirements.


Conclusion

[Health Plan Name] believes that AI is a critical tool for advancing the goals of the Medicare Advantage program. With the right regulatory framework, AI can drive efficiency, reduce costs, and improve equity for millions of beneficiaries. We urge CMS to refine its proposal to strike a better balance between safeguarding equity and fostering innovation.

We appreciate the opportunity to comment on this important issue and look forward to working with CMS to shape a forward-thinking policy that benefits all stakeholders.

Sincerely,

[Name]
Senior Vice President, Government Affairs
[Health Plan Name]


##

Minor notes.  Above, I abstracted 362-372 on AI in Medical Review; the whole section on that topic, and matching coverage in LCDs NCDs, is 354-372 (Section U, Enhancing Rules for Internal Coverage Criteria.).


CMS Policy Reversal, re Coverage of Weight-Loss Drugs

On November 26, 2024, CMS announced a 180-degree turn in its coverage of weight loss drugs like Wegovy, based on a policy re-interprertation.  The policy flip also goes opposite the interpretation of law in a Congressional Budget Office (CBO) report in October 2024.

##

See the CMS fact sheet here.

See the CMS proposed regulation here.   

See the October 2024 CBO interpretation and analysis here.

##

The CBO report from October states the classic view of the law.  A clause prohibiting weight loss drug coverage exists in Medicaid law, and is adopted by reference in Medicare Part D law as well (Medicare Modernization Act, 2003). [*]

Part D plans, which administer Medicare’s outpatient prescription drug program, are prohibited from covering AOMs as part of the standard prescription drug benefit under the terms of the Medicare Prescription Drug, Improvement, and Modernization Act of 2003.11 Those plans can cover such drugs as a supplemental benefit, but that coverage is not subsidized by the federal government and must be funded entirely by beneficiaries through additional premiums.

I don't believe that this Part D law prevents coverage of Part B physician-injected drugs, but Wegovy and similar drugs are classed as "self administered drugs" by Medicare MACs, and therefore, aren't eligible to escape into Part B coverage.

##


##

Here's the summary of the change, which the rule goes on to discuss at more length.   Page 5-6 of inspection copy version.

Part D Coverage of Anti-Obesity Medications (§ 423.100) and Application to the Medicaid Program

The statutory definition of a covered Part D drug at section 1860D-2(e)(2) of the Social Security Act (the Act) excludes certain drugs and uses—specifically, those that may be excluded by Medicaid under section 1927(d)(2) of the Act. This includes, at section 1927(d)(2)(A) of the Act, “agents when used for anorexia, weight loss, or weight gain.” Historically, drugs used for weight loss have been excluded from the definition of covered Part D drug, regardless of their use for treatment of individuals with obesity, and have been an optional drug benefit for Medicaid programs. Increases in the prevalence of obesity in the United States and changes in the prevailing medical consensus towards recognizing obesity as a disease since the beginning of the Part D program in 2006 have compelled CMS to re-evaluate Part D coverage of anti-obesity medications (AOMs) for Medicare Part D enrollees with obesity where the drug’s prescribed use is not for a medically accepted indication (MAI) that is currently covered under Part D. We are proposing to reinterpret the statutory exclusion of agents when used for weight loss to allow Part D coverage of AOMs when used to treat obesity by reducing excess body weight or maintaining weight reduction long-term for individuals with obesity who do not have another condition for which the prescribed use is an MAI that is covered under the current Part D policy. The proposed reinterpretation would also apply to the Medicaid program. Thus, AOMs could not be excluded from Medicaid coverage under this interpretation when used for weight loss or chronic weight management for the treatment of obesity. Coverage of AOMs and drugs that contain the same active ingredient as AOMs that meet the definition of a covered outpatient drug are already subject to section 1927 requirements when used for an indication, other than weight loss, that is an MAI, and Medicaid must cover those products when they are medically necessary. Under our proposed reinterpretation, AOMs approved for weight loss and chronic weight management that are used for weight loss in individuals who do not have obesity or another condition that is an MAI for the AOM would remain excluded from the definition of covered Part D drug and would remain optional benefit for Medicaid programs. 

##

  • I asked Chat GPT to rewrite this CMS summary in even simpler English.  
  • Further below, under "AI Corner," I ask Chat GPT to write an essay about the policy, in the style of a law school professor.

Simple English Summary:

  • Historically, Medicare Part D and Medicaid have excluded coverage for drugs used for weight loss. This was based on a rule that allowed Medicaid to exclude drugs used "for anorexia, weight loss, or weight gain." However, with rising obesity rates and a shift in medical thinking that recognizes obesity as a disease, CMS is proposing a new approach.
  • The change would reinterpret the rules to allow Medicare Part D and Medicaid to cover drugs specifically prescribed to treat obesity. These drugs would help individuals with obesity reduce or maintain their weight over the long term. Importantly, the reinterpretation distinguishes between using drugs for general weight loss (still excluded) and using them for treating obesity (now potentially covered).
  • This proposal also applies to Medicaid, meaning drugs for managing obesity would no longer be excluded if prescribed to treat the condition. However, drugs used for weight loss in people without obesity or another qualifying condition would still not be covered by Part D and would remain an optional Medicaid benefit.

##

Other flip-flops.  

HHS's interpretation of whether the term sex discrimination (in the ACA, 2010) includes transgender issues has flip-flopped from Obama, to Trump I, to Biden, and no doubt another flip with Trump II.

## 

Trump II

Commenters have noted this leaves a hot potato for the Trump administration.   If finalized as proposed, it could have budget implications.   If canceled, it could be framed as a withdrawal of coverage under Trump II.   

##

Voluntary Plan Coverage of AOM Described as Minimal by CMS

The budget projections generally focus on drug cost and not health benefit savings (see October CBO report on this.)  However, Medicare Advantage plans appear to have rarely covered AOM voluntarily (remarks in proposed rule), suggesting Medicare Advantage plans see commercial doubt that the drugs save the plans lots of money and simply pay for themselves.  On page 541, CMS notes, as did CBO, "Magnitude and timing of any potential savings [are] highly uncertain" and states that costs will have a larger impact on the financials...savings will be much slower to emerge.

[*]  

Defining Part D: SSA 1927, SSA 1860D.

See page 5 of the  Part D proposed rule, inspection version, stating that Part D  drugs are defined at 1860D-2 (e)(2) which points to Medicaid law at SSA 1927(d)(2)(A) which blocks coverage of "agents when used for anorexia, weight loss, or weight gain."  CMS states on page 525 of the inspection copy, "Rulemaking is required for CMS to amend its longstanding interpretation [of 1927...]."  Financial estimates follow (p. 525ff).  While "rulemaking" with notice and comment is required, no regulatory change (in the Code of Federal Regulations) is being made.

The FDA label for Wegovy states it is for "an adjunct to [diet] for..chronic weight management," so to some, it will seem facile for CMS to define it as a treatment for obesity that is not impacted by the statute against meds for weight loss.  

##

Obesity as Illness 2003

A 2003 CMS review concluded that obesity should be classsified as an illness - here, here.  But the current NCD for bariatric surgery (100.1) requires you have both morbid obesity AND a second illness (like diabetes) to get surgery.  That is an NCD that could be revised in light of this month's Wegovy reasoning.   

The new Part D rulemaking doesn't define obesity, which could be a hot potato in terms of recent controversies about "BMI" being an outdated, dysfunctional, or even racially discriminatory term. A Lilly drug just had BMI removed from its label (Zepbound).  The CMS bariatric surgery NCD requires BMI.

For Part A/B bariatric surgery,  the debate would hing on whether obesity is "an illness," because 1862A1a defines Medicare benefits for "treatment of illness."   However, for Part D, and other forums, the issue would be whether obesity is "a disease."  Sometimes illness and disease are treated as synonyms, but in common usage it would sometimes sound odd to interchange one for the other, and in areas like medical sociology, "illness" and "disease" might be defined distinctively.

###

AI Corner

I asked Chat GPT 4o to take the stance of a law school professor and discuss the sections of the rule regarding anti-obesity medications (inspection copy pages 109-123).  Here is the result.

##

Detailed Discussion of CMS Rulemaking on 

Part D Coverage of Anti-Obesity Medications


Background and Policy Shift

CMS's recent proposal to reinterpret the statutory exclusion of weight-loss drugs under the Social Security Act (SSA) §§ 1860D-2 and 1927 represents a significant policy reversal. Historically, Medicare Part D and Medicaid excluded coverage of drugs "used for anorexia, weight loss, or weight gain," a stance reinforced as recently as October 2024 in a Congressional Budget Office report. 

CMS now proposes that anti-obesity medications (AOMs) should be covered when used to treat obesity, reflecting shifts in medical consensus that recognize obesity as a chronic disease rather than a cosmetic issue.


Pros of the Proposed Rule

  1. Alignment with Modern Medical Standards

    • The reinterpretation reflects the growing recognition of obesity as a chronic disease that contributes to numerous serious conditions, such as diabetes, cardiovascular disease, and certain cancers. By including AOMs in coverage, CMS aligns its policy with medical guidelines and organizations like the AMA, which classified obesity as a disease in 2013.
  2. Addressing a Public Health Crisis

    • Obesity rates have risen dramatically, with approximately 42% of the U.S. population now classified as obese. The policy could help mitigate health disparities, particularly in populations disproportionately affected, such as Black and Hispanic communities.
  3. Potential for Cost Savings

    • While initially costly, AOM coverage might reduce long-term healthcare costs by lowering rates of obesity-related diseases, such as type 2 diabetes and cardiovascular complications, which are expensive to treat.
  4. Equity in Access

    • The reinterpretation ensures that low-income populations covered by Medicaid and Medicare have access to AOMs, potentially addressing health inequities exacerbated by limited access to effective obesity treatments.
  5. Consistency in Statutory Interpretation

    • CMS aims to harmonize its approach to weight-loss agents with existing policy that permits coverage of drugs used for "weight gain" in conditions like AIDS-related cachexia. This consistency enhances the credibility of the reinterpretation.

Cons and Weak Points

  1. Deviation from Congressional Intent

    • The longstanding exclusion of weight-loss drugs under SSA § 1927 was likely intended to prevent coverage for medications perceived as elective or cosmetic. Critics may argue that CMS's reinterpretation undermines Congressional intent and sets a precedent for reinterpreting statutory exclusions.
  2. Budgetary Concerns

    • Expanding coverage to include AOMs could lead to significant short-term cost increases for Medicare and Medicaid. The CBO's recent acknowledgment of the exclusion as "settled law" highlights uncertainty about the fiscal impact of such a reversal.
  3. Potential Abuse or Misuse

    • The expanded coverage could lead to inappropriate prescriptions for individuals without obesity, particularly in cases where AOMs are prescribed for minor weight management or for off-label uses. CMS acknowledges this risk and seeks comment on implementation strategies.
  4. Complex Implementation

    • For Medicaid, aligning state coverage policies with the new rule may be challenging, particularly for states that already operate on tight budgets or that may resist mandates perceived as federal overreach. The rule also leaves room for states to exercise discretion in some cases, which could lead to variability in access.
  5. Unclear Criteria for Obesity

    • CMS does not propose a universal definition of obesity for coverage purposes, deferring to Part D sponsors to set prior authorization criteria. This could lead to inconsistent access and potential administrative burdens for providers and beneficiaries.
  6. Perverse Incentives

    • By limiting coverage to individuals with obesity (e.g., BMI ≥ 30, although the CMS proposal doesn't quote "BMI"), the policy may inadvertently encourage individuals with overweight (BMI 27–29.9) to gain weight to qualify for treatment. CMS recognizes this risk but has not proposed clear safeguards.

Implications for Broader Policy

The proposed rule is a watershed moment in healthcare policy, signaling a broader shift toward treating obesity as a public health priority. However, it also reflects the tension between evolving medical science and historical legislative frameworks. By seeking public comment, CMS acknowledges the complexities of implementation and the need to balance medical advances with fiscal responsibility.

From a legal standpoint, this rule raises questions about agency authority to reinterpret statutes without Congressional approval, which could invite judicial scrutiny. The decision, if finalized, will likely serve as a test case for CMS's regulatory flexibility under the Social Security Act.


Conclusion

The CMS proposal to cover AOMs under Medicare Part D and Medicaid marks a critical step in addressing obesity as a chronic disease. While it offers substantial public health benefits, the policy shift raises questions about statutory interpretation, cost management, and implementation logistics. As this rulemaking progresses, it will be important to watch how stakeholders—states, insurers, and beneficiaries—respond to the proposal and how CMS addresses these challenges through its final rule.


Monday, November 25, 2024

CAP and More: Coalition for Effective Diagnostics Wants New Laws ASAP

If you followed CAP's comments on the ACLA/FDA lawsuit about LDT regulation, you noticed that CAP was strongly and persistently in favor of new legislation (which would replace the FDA LDT regulation).

But wait, there's more.

CAP, Friends of Cancer Research, and others have come together as Coalition for Effective Diagnostics, wanting to make it loud and clear to Congress that the time for legislation reform is "now."

  • Find the home page at CAP here.
  • Find their letter to Congress here.
  • Find a lengthy subscription article at 360Dx (November 25) here.
  • See also a separate letter to Congress directly on CAP letterhead (November 20) here.
Members of the CED Coaliton for Effective Diagnostics - are CAP, Friends of Cancer Research, Thermo Fisher, Mayo, Roche, and Alexion.


AI Corner

A few months ago, I asked Chat GPT to summarize the 400-page VALID act.  Here.

CMS Posts New Lab Prices for CY2025

On Monday, November 25, 2025, CMS posted over 100 prices for new lab tests for CY2025.

This is the traditional cycle of posting proposed prices in September, taking public comment, and posting final prices around Thanksgiving week.   CMS will also release a complete fee schedule for lab tests for 2025 (including the 1500 ongoing codes plus the new ones) in the next ten days.

Find the CMS Clin Lab Fee Schedule page here:

https://www.cms.gov/medicare/payment/fee-schedules/clinical-laboratory-fee-schedule-clfs/annual-public-meetings

Scroll down for the heading, CLFS Test Codes Payment Determinations, and see CY  2025 Final Payment Determinations (ZIP for Excel).

https://www.cms.gov/files/zip/cy-2025-final-payment-determinations.zip

See a subscription article at 360dx.

##

A few comments.

Actions in Overview

In total, 40 of 129 codes are in gapfill for 2025.

7 of the crosswalked codes were other than a single crosswalk.  One code was crosswalk to 0.5X, one code was crosswalked to 2X.  5 codes were crosswalked to a code stack, of which 1 was crosswalked to the sum of 4 codes (0430U=82103+83993+82653+84376).  I believe this was the 2nd time in 4 years (about 400 codes) that a fractional (0.5X) multiplier was used.  

In total, only 17 codes of the 129 varied from the September proposal (based on an automated Excel comparison.)  In 1 case, the test became an ADLT, in 2 cases, codes were deleted (3 codes dropped).   Of the remaining 14 codes, 8 were converted to gapfill (such as Alzheimer codes).  That leaves 7 codes that landed on a different crosswalk.   

CMS Looks to Code Text, Not "Under-the-Hood"

In an explanation that reiterates CMS looks at "code text" and not underlying variables, PLA code 0451U, a mass spec myeloma test from Mayo, remains crosswalked to 0077U.   CMS received complaints, but found that the complaints fell outside of the available code text.  CMS writes, "Finalize as proposed; the comments we received stated the specific tandem mass spectrometry technology is different.  However, looking at the CPT descriptors these differences are not outlined; meaning CMS cannot ascertain a difference.  In addition, commenters did not have an alternative crosswalk recommendation."   Similarly 0450U.

Additional Comments

Of very high interest to the Alzheimer community, a number of new codes for Alzheimer tests (Category I or 80,000-series codes) are now Gapfill rather than crosswalked to 83520 for only about $18.

A pre-eclampsia test (sFIT-1, PIGF), 0482U, was originally proposed CW to 81512 $69, but was shifted to 0243Ux2 ($64x2).   This is what Mayo had originally requested in June.

Two codes for special tests on whole-slide imaging (0512U, 0513U) were both crosswalked to 0220U, $706.

The Colosense FDA CRC screening test (stool), 0421U, asked for a crosswalk to Cologuard, 81528, $509,  and received it.   Cologuard Plus, 0464U, was initially offered a crosswalk to Cologuard, 81528.  However, in the final, Cologuard Plus got a more complex crosswalk, 81327x3 +82274.     This is $192x3 plus $16 or just short of $600.   
 
BillionToOne had 3 codes in play, 0449U (carrier screening x 5), 0486U (a methylation MRD test), and 0487U (an 84-gene LBx CGP test for driver oncogenes).   0449U shifted from gapfill to 81162 $1825 based on comments.  0486U remained as gapfill.  0487U was shifted from gapfill to 0409U [Lucence LBx] at $2919 based on public comment.   

RVU Relative Value Has Dropped by Half in Twenty Years

Over the twenty years that my main job has been to "follow Medicare," I've always noticed that RVU adjustments, or conversion factors, tend to lag inflation.  

It's true, and it's severe.   John Leppard of Capitol Policy Partners has published a graphic that shows slippage of RVU values (only half-heartedly adjusted for inflation) against the Consumer Price Index.  Basically, normalize the Conversion Factor and you'll find it's dropped 50% against inflation beginning around 2002.   That is, let's say Medidcare paid $120 for a 40 minute office visit in 2002, and the modestly raised amount it pays today has lost a lot due to inflation.   

Here's the graphic:


See similarly a subscription article in 360Dx by Adam Bonislawski on the frozen lab fee schedule, since 2016, and how far it has lagged below inflation.  Here.



Personalized Medicine Coalition: Conference Streams Online

For those who were unable to attend the Personalized Medicine Coalition conference in Boston earlier in November, it streams online at YouTube.

https://www.youtube.com/@personalizedmedicine


Next year (2025) will be November 13-14 in Laguna Niguel, California.

##

AI Corner.

I noticed the YouTube videos had auto transcripts at YT, and I wondered what Chat GPT would make of them.  Below. (I haven't watched the 9 hours of video, so, the Auto Summary is offered as-is.).

##

DAY ONE

Headline: "18th Annual Personalized Medicine Conference Highlights Innovations and Leadership"

Boston, MA — The 18th Annual Personalized Medicine Coalition (PMC) conference convened at Harvard Medical School, bringing together leaders from healthcare, biotechnology, and diagnostics to explore pivotal advancements and challenges in personalized medicine. Hosted by PMC President Edward Abrahams, the event focused on bridging the gap between cutting-edge science and patient care.

Key Themes:

  • Pivotal Moment in Medicine: Abrahams emphasized the ongoing struggle to integrate rapid scientific and technological advancements into healthcare systems. He noted that PMC's mission remains focused on addressing this critical gap, underscoring the need for collaborative efforts across government, education, clinical adoption, and payer systems.

  • Hinge Moment in Biotech: David Reese, Chief Technology Officer at Amgen, described a "hinge moment" in biotech, where revolutionary technologies like CRISPR, AI, and proteomics are poised to transform drug development. Reese highlighted Amgen’s advancements, including single-cell experiments and protein therapeutics driven by machine learning.

  • Personalized Cardiovascular Care: Reese spotlighted Amgen's innovative program targeting LP(a), a genetic driver of cardiovascular disease. This approach exemplifies the precision medicine movement, aiming to deliver tailored therapies that significantly improve patient outcomes.

  • Illumina's Vision for Multi-Omic Integration: Jacob Thaysen, CEO of Illumina, outlined the future of whole genome sequencing and its integration with proteomics and epigenomics. Despite dramatic cost reductions in genome sequencing, he noted barriers to adoption, including interpretation challenges and disparities in community healthcare settings.

Leadership Award: A highlight of the conference was the PMC's Leadership in Personalized Medicine Award, presented to Emily Kramer-Golinkoff, founder of "Emily's Entourage." This nonprofit has raised nearly $10 million to accelerate research and treatment for cystic fibrosis patients excluded from existing therapies. Accepting the award virtually, Kramer-Golinkoff shared her vision for a future where no patient is left behind.

The conference concluded with discussions on cultural and systemic barriers to widespread adoption of personalized medicine. Experts called for collaborative ecosystems, standardized practices, and innovative reimbursement models to support long-term healthcare transformation.

The next session promises to delve deeper into investment strategies for diagnostics, highlighting the financial backbone needed to sustain innovation in personalized medicine.

DAY TWO

Headline: "Day 2 of Personalized Medicine Conference Spotlights Patient-Centric Innovations and Policy Challenges"

Boston, MA — The second day of the 18th Annual Personalized Medicine Coalition (PMC) conference at Harvard Medical School brought further insights into the evolving landscape of personalized medicine. Attendees explored the real-world applications of groundbreaking diagnostics and grappled with the implications of current healthcare policies.

Key Highlights:

  • A Personal Story of Progress: The day opened with a poignant story about Alex, a cancer survivor whose life was saved by precision medicine. Diagnosed with a rare cancer in 2021, Alex’s genomic profiling revealed a targetable ALK rearrangement, enabling successful treatment. Today, he is cancer-free and preparing for medical school.

  • Policy Challenges in Focus: Cynthia Benz, PMC's Senior Vice President of Policy, detailed the complex policy landscape impacting personalized medicine, including the Inflation Reduction Act (IRA) and its potential unintended consequences on drug development. She emphasized efforts to quantify the impact of these policies on patient access and innovation, with results expected in early 2025.

  • The Role of Advocacy: Dr. Mikey Bara of the Pharmaceutical Research and Manufacturers of America (PhRMA) discussed the importance of supporting innovation through robust intellectual property protections and patient-centered reimbursement models. He highlighted the detrimental effects of the IRA on small molecule drug development and called for reforms in areas like PBMs and the 340B program.

  • Real-World Applications of Multi-Cancer Early Detection: A panel featuring Grail and Point 32 Health explored the implementation of Grail’s groundbreaking Gallery test, which detects over 50 types of cancer through blood-based DNA methylation analysis. The partnership pilot demonstrated that even in real-world conditions, the test's diagnostic pathway is efficient, often resolving cases within three months. The discussion underscored the test's potential to transform early cancer detection while complementing existing screenings.

  • Equity and Access: Discussions throughout the day repeatedly highlighted disparities in cancer outcomes and access to cutting-edge diagnostics, calling for targeted efforts to ensure broader adoption and equity in cancer care.

The conference continues to serve as a critical forum for aligning stakeholders in the pursuit of transformative advancements in personalized medicine, with discussions pointing toward a promising yet challenging future.

Thursday, November 21, 2024

STAT and WaPo: Will RFK "Blow Up" CMS Payment Systems?

According to new reports in STAT and Washington Post, the Trump administration might want to blow up CMS payment systems.  Per RFK Jr, the proposed Secretary of Health, the payment systems encourage resources spent on chronic illness rather than health and prevention.

##

Find the Washington Post here (Dan Diamond).   
Find STAT here (Rachel Cohrs Zhang).

See also, my November 20 blog on Trump health nominees & UCSF's Vinay Prasad.  
See also, my November 14 blog on RFJ Jr as health secretary.

##

click to zoom

According to the two articles, RFK Jr's team is exploring vigorous reforms to Medicare’s physician payment system to prioritize preventive care and health promotion over the current “sick care” model. Sources conveyed that the incoming leadership views the existing coding framework as rewarding expensive procedures and surgeries, while discouraging primary care and chronic disease prevention. Kennedy and his team view this as a core issue driving poor U.S. health outcomes compared to other countries. 

A range of proposals, not systemically unveiled yet, could reduce the influence of the AMA, which dominates both coding and Part B (RVU) pricing.  The initiative syncs with the new administration's broader “Make America Healthy Again” agenda, which would focus on sources of chronic disease and rebalancing health care priorities to support wellness and prevention.

##

The WaPo article quotes Columbia University's Prof. Miriam Laugesen, whose book, "Fixing Medical Prices," is a favorite of mine (Harvard Univ Press).

The new HHS effort may harvest earlier thinking in this space.  See, (1) Center for Public Integrity (2010), "Little-Known AMA Group...".  See (2) Fuchs, SLU Journal of Health Law (2013), Medicare Price Problems.  See (3) Center for American Progress (2018), Rethinking the RUC.  (4) But see AMA (2018), Criticism of RUC Needs Rethinking.   AI CORNER: See these four articles discussed by AI here.

Medicare Nerd Note: The NCD "Effective Date" & Whence it Comes

Here's a small Medicare policy mystery.   I've always said that NCD's are effective on the date published, and I recalled that was written right in the Medicare statute.    

However, I can't currently find it in the Medicare statute, even though there are CMS documents from 2013 that state, the NCD effective date rule IS based on the Medicare statute.

### 01 Policy Page

Medicare has a policy page for the NCD process, including six downloadable documents.

https://www.cms.gov/medicare/coverage/determination-process

### 02 Fed Reg 2003

One of the older documents is 68 Fed Reg 55634, which was (back on September 26, 2003) a revised processed for NCDs.   This document distinguished a national determination memo, from the "actual" NCD, which could appear several months later, and would include implementation instructions, such as the effective date.   That is, the 2003 document detaches the implementation date from the NCD review process.

https://www.cms.gov/medicare/coverage/determinationprocess/downloads/fr09262003.pdf

### 03 MMA

A couple months later, along comes the Medicare Modernization Act (which introduced Medicare Part D) in December 2003, Public Law 108-173.   Section 731 is "improvements in national and local coverage determination process."  This introduced timelines, such as a 30-day public comment period and a final NCD not later than 60 days after the 30 day comment period.   It also gives CMS authority to make temporary or permanent codes for NCDs.

### 04 Ten year gap: Fed Reg 2013

With a curious ten-year gap following (1) the NCD process (September 2003), and (2) the MMA (December 2003), CMS issued a revised NCD process on August 7, 2013.   This one begins by acknowledging updates required by the MMA ...of 2003.  78 Fed Reg 48164.

https://www.cms.gov/medicare/coverage/determinationprocess/downloads/fr08072013.pdf

At page 48169, this publication states that the effective date of the NCD is the date of publication However, it specifically refers this to SSA 1862(l) [1862 el] which has no explicit remark about the effective date of an NCD. 

With publication of the final decision memorandum, the NCD is effective for claims with dates of service beginning with the effective date of the NCD. The memorandum contains, among other materials, the analysis and conclusions and also the NCD that becomes a part of the Medicare National Coverage Determination Manual (Pub. 100–3) of the CMS Internet Only Manual. After enactment of section 1862(l) of the Act [MMA], the effective date for the NCD is the same date as the publication date of the final decision memorandum. Therefore, we have found it expedient and practical to include the NCD that is [eventually] included in the Medicare National Coverage Determination manual in the final decision memoranda and to use that date as the effective date for Medicare coverage and payment purposes. 

The text above, regarding NCD dates, is crystal clear except for one thing.  There's no explicit remark about the coverage date at 1862(l).  Maybe it can be legally inferred from the requirement, at 1862(l), that the NCD be completed no more than 60 days after the 30 day comment period.  

### 05 Other Sources Ruled Out

To my knowledge, neither 21st Century Cures Act of 2016 (which altered LCDs) nor the Protecting Access to Medicare Act of 2014 (PAMA pricing), tinkered with NCD rules at SSA 1862.

### 

Here's Chat GPT's reading of my blog converted to an illustration.


###

Typically, nowadays, an NCD  might be issued on July 1, and CMS issues instructions to implement it on October 1.   The October 1 instructions will say the NCD coverage has an effective date of July 1, and an implementation date of December 1.  That means MACs have to be able to correctly process claims, with computer updates, not on July 1, not on October 1, but by December 1.

See CR 10878, issued April 10, 2019, in regard to an NCD issued on March 16, 2018, 13 months earlier.  The implementation date is April 9, 2019, which was 120 days after a different transmittal issued November 30, 2019, about six months after the March 2018 NCD publication.  Ouch.

https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/2019Downloads/R215NCD.pdf

In this unusual CR, CMS notes that stakeholders have complaints about the intrepretation of the NCD which CMS staff promise to address in the future with their MACs.

##

SSA 1871 says that Medicare can't make retroactive rules.  The Constitution generally bans retroactive laws.




Wednesday, November 20, 2024

CAP to Trump Transition: Dump FDA LDT Regulation

College of American Pathologists has sent two letters, one to Congress and one to the Trump Transition team, asking that the FDA regulation of LDTs, in its current form, be stopped.

  • The CAP Webpage is here.
  • The CAP letter to Trump Transition is here.  November 19.
  • The CAP letter to Congress is here.  November 20.
    • (Update:  ADLM, another lab org, also protests here.)

The presidential take-home message is pretty direct:

  • The CAP urges the Trump Administration to rescind the regulation and work with Congress to enact legislation to establish a regulatory framework at the FDA uniquely tailored to diagnostic tests.

And for the Hill:

  • The College of American Pathologists (CAP) urges [Congress] to include legislation in an end-of-year package preventing the implementation of the U.S. Food and Drug Administration’s (FDA) “Medical Devices; Laboratory Developed Tests” final rule.