Inside the CMS Quality Conference: What Quality Professionals Need to Know

I recently attended the CMS Quality Conference, where some of the most influential leaders in healthcare shared their visions and strategies for transforming the industry. Here are the most important insights and revelations that you, as a quality professional, should know.

The opening keynote featured Dora Hughes, MD, MPH, Chief Medical Officer and Director of the Center for Clinical Standards and Quality at CMS, and Mehmet Oz, MD, Administrator of CMS. Dr. Oz began with his assessment of the U.S. healthcare system. He first highlighted that the Medicare Trust Fund is on a critical path, with a potential bankruptcy looming by 2029, sooner than previously projected. Despite hopes for post-COVID normalization, healthcare costs have continued to rise, growing by 9% last year. Meanwhile, he continued, Medicaid expenditures have doubled over the past five years.

Dr. Oz's key insight was that the most expensive thing in healthcare is bad care. He talked about medical errors as the third leading cause of death in the country. He emphasized the urgent need to improve patient care and safety, calling for a shift towards prevention, digital innovation, and greater accountability.  

He highlighted the urgent need for upstream interventions like nutrition and physical activity, early cancer and chronic disease screenings, and empowering patients and their families. He also stressed the importance of reducing administrative burdens, leveraging AI to enhance care, and implementing smarter payment models to combat fraud, waste, and abuse, ensuring that every tax dollar is spent on high-quality, value-based care. 

He then outlined his vision for CMS to become "the best payer in the world." These four themes below were emphasized through various panels and speeches during the conference. I've summarized the major themes below.

1. Prevention as the Bedrock for Health

Dr. Hughes and Dr. Oz both emphasized the importance of prevention in healthcare. They highlighted the need for upstream interventions, such as promoting nutrition, physical activity, and early screenings, to reduce the incidence of chronic diseases and lower healthcare costs.  

During Dr Oz’s speech, he played a message from Secretary Kennedy where he said, “my uncle [President Kennedy] would be ashamed to know that 70% of the young people can’t qualify for the military because of a medical condition.”  

Throughout the conference, many speakers emphasized that our healthcare system is designed for disease. We are incentivized to solve for diseases, such as blood pressure medication instead of helping patients understand nutrition. They even featured a speaker from Food is Medicine.  

I wasn’t 100% clear what message Quality was supposed to take home from all of this, but the theme of primary care physicians at the heart of all things and changing incentives was evident. So, they asked the audience; “how do we measure preventative health?” 

Our health system only measures things like lab tests where bad results indicate the need for intervention. Good results are invisible. They asked for our ideas on how we can measure preventative care. CMS did not offer any concrete solutions at the conference, but they did point to several ideas about how to better connect information to patients and thereby enable patients to have a more active role in their own health. 

Key Takeaways 

Takeaway 1: CMS is emphasizing prevention as a key strategy to reduce chronic disease and healthcare spending, focusing on upstream interventions like nutrition, physical activity, and early screenings. 

Takeaway 2: The provider directory and digital identity tools are essential for improving coordination and trust in the healthcare system. And this will function as a key part of enabling patients to better participate in their own health. 

Takeaway 3: CMS is looking to create a bidirectional communication system with beneficiaries to empower them and gather their feedback. 

2. Digital Transformation, AI, and Interoperability

The conference couldn’t stop talking about digital transformation in healthcare.  

What did they say? Everything and nothing.  

Dr. Oz spoke about the development of AI-driven tools, telehealth, and clinical decision support systems to reduce administrative burden and enhance patient engagement.  

There was a panel dedicated to the topic of how they are using AI. Boy was everyone excited about AI. One panelist said, “I think it's like Amazon 1997, they're selling books, and it takes about 10 days to get a book. Meaning like - it's gonna get better." 

They talked about getting access to all of your data in your EHR and simply calculating your measure performance for you instead of you having to submit measure performance to different programs. Are any of you rolling your eyes yet? I certainly was. Especially when in a different session, Dr. Oz bemoaned the fact that CMS only has 13 engineers.

Ah hah! So that’s why you’ve reissued the Hybrid measure and the Hospital Star Rating Hospital Specific Reports this year…twice.  

Dr. Michelle Schreiber, Deputy Director of the Center for Clinical Standards and Quality (CCSQ) and Director of the Quality Measurement and Value-based Incentives Group (QMVIG), then asked the sanest question of the day to the panel: 'Well, that all sounds great, but if the underlying data in the EHR isn’t any good, what good will tapping into the EHR for measurement do"

For which, literally no one had an answer and I’m sending Amens to Heaven in the 3rd row. 

Put your hand down, crazy lady! 

In my opinion, it begins and hinges on good data. FHIR eCQMs are on the horizon. CMS, ONC, HL7, and whoever else is involved needs to ensure ALL the data elements required for eCQM calculations are standardized. Then all EHRs must adhere to those standards. Then all hospitals must update their systems and confirm that all data is within these standards. Then CMS needs to update their data storage to consume this giant amount of data. Then we can accomplish this vision of immediate measurement using data streams from EHRs. Sounds like a quick project… 

Key Takeaways 

Takeaway 1: The sky is the limit on how AI might solve healthcare problems right now. A few things they mentioned:

• AI to help with clinical documentation, streamlining insurance claims, and optimizing hospital operations 

• AI scans to pick up unstructured fields and turn them into structured fields 

• Patients using AI to help with their own health situation (medication management, navigating the healthcare system, safety issues) 

• Clinical decision support systems helping doctors by analyzing patient data to suggest diagnoses, flag potential drug interactions, and recommend evidence-based treatments

• AI to assist the drug discovery process by predicting how molecules behave, what medications can be used for other treatments, identifying promising drug candidates, and designing clinical trials more efficiently 

• Deep learning models to augment medical imaging and diagnostics 

• AI to monitor and detect fraud and abuse 

• AI to help patients detect health issues with continuous health monitoring through wearables and smart devices 

• AI-powered robotic surgeries 

• Using AI for mental health support, especially in areas with provider shortages such as rural areas 

• AI on all our measurement data – uncovering trends, interacting with the data to discover patterns, troubleshooting ways to resolve issues, setting plan reminders… the list goes on and on

Takeaway 2: AI in healthcare promises significant improvements in patient safety and provider efficiency, but trust and training are critical for successful implementation. 

Takeaway 3: Standardization and robust data management are essential for the effective use of AI in healthcare processes. 

Takeaway 4: Ensuring data quality and patient trust are crucial for the success of AI in healthcare. Patients should be involved in the planning of how we use these AI tools with (on?) patients.

3. Value-Based High-Quality Care and Accountability

Dr. Oz stressed the importance of value-based care and accountability. He mentioned the implementation of smarter payment models and real-time analytics to ensure that healthcare dollars are spent effectively.

They featured the WiSER model (Wasteful and Inappropriate Service Reduction). This is a new model CMS just released all around fixing the issues with prior authorization. Essentially, they are enrolling prior auth tech companies who have previously done this work. Once enrolled, these tech companies will use AI to streamline the review process for certain items and services (such as skin and tissue substitutes, electrical nerve stimulators, and knee arthroscopy for knee osteoarthritis).  

Here’s something they complained a lot about during the conference. The Quality Payment Program. No one is happy about it. They don’t feel like they got what they were looking for out of that program. CMS feels like they spent a lot of money on the program, and everyone who participates in the MIPS program feels like they didn’t get any real incentive money. So, what are they going to do? 

Well, they’re gonna think…real hard. They will think about incentives and measurement, and goals. READ: they don’t know yet OR they’ve got something up their sleeves, and they aren’t showing their cards yet. 

Key Takeaways 

Takeaway 1: CMS is focused on eliminating waste, fraud, and abuse, and they are working to act as quickly as they can by introducing things like the WiSER model. 

Takeaway 2: The Quality Payment Program has failed to meet expectations for both CMS and participants. Expect changes. 

Takeaway 3: CMS leadership acknowledges the need for fundamental reform in payment models but has not yet articulated a clear path forward, suggesting either ongoing deliberation or strategic planning behind the scenes.

4. Care for Vulnerable Populations

Addressing the healthcare needs of underserved communities was another critical theme. Dr. Oz and Dr. Hughes discussed the importance of caring for vulnerable populations. 

You know what I didn’t hear during this conference? Equitable care. It was the weirdest thing. Last year, all they could talk about was how outcomes were different for different people. This year…crickets. Instead, we talked a lot about “vulnerable populations.”  

Ok, cool, cool. I can get hip with the lingo.  

It was kind of weird because everyone acted as if the screening of patients for health-related social needs (food insecurity, transportation difficulty, etc.) was still fully on.

Which it technically is so don't stop screening! CMS just proposed to remove it. It's not finalized.

So don’t give up on those screening questions. Just consider telling everyone at work that you’re “screening for vulnerable populations.”  

Key Takeaways 

Takeaway 1: CMS has shifted its messaging from "equitable care" to "vulnerable populations," though the underlying focus on addressing healthcare disparities appears to remain unchanged. 

Takeaway 2: Quality professionals should adapt their communication to align with current CMS terminology while maintaining existing screening protocols for now. 

The CMS Quality Conference revealed an organization at a crossroads, grappling with systemic challenges while searching for transformative solutions.

While Dr. Oz's vision of making CMS "the best payer in the world" through prevention, digital innovation, and accountability is ambitious, the conference exposed significant gaps between aspiration and implementation.

The enthusiasm for AI solutions contrasted sharply with the lack of concrete answers about data quality which raises concerns about the feasibility of their digital transformation goals.

Perhaps most telling was the shift from "health equity" to "vulnerable populations" – a semantic change that may signal evolving political priorities while the underlying work continues.

For quality professionals, the message is clear: prepare for continued uncertainty in payment models, maintain focus on prevention and social determinants of health regardless of terminology, and approach AI implementation with both optimism and healthy skepticism about data integrity and standardization challenges.