Rewriting Healthcare’s Foundation: The HHS Reorg’s Potential Impact on Value-Based Care and APMs

11 min readApr 21, 2025

The leaked reorganization of the Department of Health and Human Services represents a fundamental restructuring that will significantly impact value-based care models, data infrastructure, and healthcare stakeholders across the spectrum. This analysis explores the potential winners and losers in this new landscape, with particular focus on the implications for care delivery, technology adoption, and patient outcomes.

The Reorg Blueprint: What’s Really Changing

The new structure consolidates legacy CMS functions with those of the Office of the Assistant Secretary for Planning and Evaluation (ASPE) under the umbrella of the newly proposed Office of Health Policy and Payment Innovation (OHPPI).

This reorganization has ripple effects:

CMMI (Center for Medicare and Medicaid Innovation) appears to be integrated into OHPPI, alongside the budget, quality, and analytics teams.
A formal Health System Innovation and Analytics group would consolidate data, strategy, and policy oversight.
AI and emerging technology functions are being centralized within the Office of Technology & Digital Transformation, signaling a push for integrated infrastructure and modernization.

This is not a reshuffling for efficiency alone; it is an ideological repositioning toward centralized innovation governance, ostensibly to align budget, care quality, and data with VBC and APM frameworks.

Value-Based Care and APMs: Still a Fragile Majority

According to CMS data, over 70% of Medicare Advantage beneficiaries were aligned with a value-based care (VBC) model in some capacity as of 2023. However, true upside/downside risk-bearing models, such as capitation or episode-based payments, represent a smaller segment of the ecosystem. Humana’s 2023 VBC Trends report noted that only 33% of their individual MA members were in full risk arrangements — a number that has plateaued.

When looking at the broader market, 14% are in capitation, true upside/downside risk. As we approach 2025, employers are looking to embrace VBC to help combat the expected large US Health Care Inflation Rate (USHCIR) and medical cost trend by focusing more on advanced primary care and centers of excellence. Coupled with the administration’s campaign discussions about moving all of Medicare to Medicare Advantage, value-based care arrangements are expected to grow significantly in the next couple of years.

So, how could this reorg accelerate or derail that momentum?

Potential Positives

Alignment of Budget + Innovation = Strategic Cohesion

Merging CMMI functions with analytics and quality oversight under one roof may finally enable “accountability budgeting” — tying payment model experimentation to long-term cost containment and clinical outcomes.

Analytics-Led Reform

With analytics, data quality, and health system transformation grouped structurally, there’s potential to institutionalize learning loops. Instead of piloting models in silos, reforms can be informed by real-time performance metrics. Current state often means a provider can only participate in one VBC program, even if they could qualify for more types of VBC programs. This will push for how to have overlapping programs or hybrid programs, something both employers and states have been calling for.

AI & Predictive Models

Consolidation under the Digital Transformation Office suggests a commitment to AI tools that forecast patient risk, streamline claims, and optimize reimbursement — a boon for providers navigating complex APM rules.

Risks and Concerns

CMMI’s New Operational Context

The reorganization could politicize CMMI’s historically experimental nature, subjecting innovation pipelines to budget cycles and bureaucratic veto points. CMMI has always operated with CMS oversight, but the question is, will there be new influences and constraints with this reorg?

One-Size-Fits-All Risk

Centralization can create uniform incentives or metrics that overlook regional variability and specialty-specific nuances in VBC performance. This can be incredibly problematic for large segment delineations such as age (can’t use Medicare analyses to dictate or predict Medicaid or Employer, as probably the most well-known example. However, Urban vs Rural, whose markets are vastly different, has proven to be very different with VBC).

Delays Due to Oversight Friction

Integrating analytical, budgetary, and innovative authority may hinder approvals and lead to reduced experimentation.

Physician and Practice Impact

The reorganization will have profound effects on clinical workflows and administrative burdens for physicians and medical practices:

Solo and Small Practices: Already struggling with administrative overhead, these providers may face additional complexity in navigating new reporting structures and compliance requirements.
Burnout Concerns: With each regulatory change, documentation and reporting requirements often increase, potentially exacerbating physician burnout rates, which already hover around 45% nationally.
Practice Transformation Support: Critical question remains whether the new structure will provide adequate technical assistance to help practices transition successfully to new models.

Patient Experience Implications

While administrative reorganizations may seem distant from patient care, the potential impacts include:

Care Coordination: Could improve if data systems are more integrated, allowing providers to better visualize patient needs across different settings.
Access to Care: Rural and underserved populations may experience reduced access if provider networks contract due to administrative pressures.
Out-of-Pocket Costs: Changes in value-based arrangements could either reduce or increase patient financial responsibility depending on implementation details.
Patient Navigation: Fragmentation may initially increase during transition phases, making healthcare system navigation more challenging for patients.

What Happens to Population Health?

Population health management is foundational to VBC but often lacks effectiveness without aligned incentives or interoperable data. The reorg’s centralization of community health initiatives, health disparities teams, and population-based research could go either way:

Opportunity

Enhanced integration with data systems and payment models may help quantify population health ROI — transforming “nice to have” into “must fund.” Pulling data across the spectrum could genuinely unlock significant research potential to identify the best care paths, the most effective and efficient treatment methods, and simplify the requests from providers in VBC, making participation much easier.

Threat

Public health may be overlooked in favor of fiscal performance, particularly if budget teams lead OHPPI governance. This can be incredibly dangerous, not just because it leads to poor care decisions motivated by profit, but also because viewing these types of programs through that lens often results in short-sighted perspectives that incur significantly higher costs overall. It is better to pay Uber to pick up the patient and take them to the PCP than to have them call an ambulance and go to the ER, which results in a difference of thousands of dollars. On a grand scale, that money is massive; yet, those kinds of cuts could happen due to short-sighted decision-making.

Health Equity Considerations

The restructuring presents both opportunities and challenges for addressing systemic healthcare disparities:

Data Visibility: Consolidated data systems could better highlight disparities in care access, quality, and outcomes.
Resource Allocation: Will funding for equity initiatives be maintained when integrated with broader budget considerations?
Community-Based Approaches: The shift toward state-level implementation could either enhance or diminish culturally-appropriate intervention models.
Social Determinants of Health: Changes to community health program structures may impact coordination with social services, which are critically needed by vulnerable populations.

Transition Period Challenges

The implementation timeline presents immediate concerns:

Program Continuity: Current APM participants need clarity on whether existing contracts and benchmarks will remain stable.
Staffing Transitions: Agency reorganizations typically involve staff reassignments that could temporarily reduce operational capacity.
Technical System Integration: Merging disparate data systems takes years, not months, creating potential gaps in program monitoring.
Regulatory Guidance: Providers and payers will need clear implementation guidance during the transition to avoid compliance pitfalls.

Congressional Oversight Implications

The reorganization will likely attract significant congressional attention:

Appropriations Influence: Congressional funding decisions could accelerate or constrain implementation timelines.
Oversight Hearings: Expect intense scrutiny of impacts on constituent healthcare access and costs.
Legislative Adjustments: Congress may introduce legislation to modify aspects of the reorganization based on stakeholder feedback.
Political Dynamics: The reorganization could become a focal point in broader healthcare policy debates.

Strategic Bets: Who Wins, Who Loses

Winners

So, who has the most potential to win with these changes?

Large health plans: With the shift towards privatization and states, they are likely to attract more business, and they technically have the infrastructure and/or capital to support it. That said, even with infrastructure, regulatory compliance and implementation typically take years, not months. So they might be winning in the long run, if the changes are expected faster than they can adapt, this could put even large health plans on their back foot.
Tech-first providers: VBC is analytics-heavy for discovering ways to succeed; those already embracing this approach can quickly find success.
BDAAS and PAAS Vendors: Healthcare now has strong government support to standardize data ingestion. This support will enhance data accuracy and automation for VBC contracts. With agencies shifting their focus to the states, a significant market opportunity is emerging.
AI-Enhanced Analytics Organizations: Many companies claim to have AI capabilities, but few truly do. In healthcare, training on solid and clean datasets is essential, and a narrow focus is insufficient due to the sector’s diversity. Those who implement AI thoughtfully and avoid rushing to market will excel. Additionally, states lack the budgets to handle all new responsibilities, creating opportunities to provide value to clients in need.
Research and development: Integrating all this data will enhance research capabilities. It is likely that some of it will be made public, similar to Medicare claims data. Much can be achieved with this data that could benefit public health and reduce costs.

Losers

And who has the most chance to struggle with this new design?

Small providers and single-focused non-profits: Reducing funding and shifting resources to states that do not already have funding in place, coupled with what will likely be an expensive and time-consuming need for technology, will complicate the management of these changes. Additionally, cuts to tax incentives will affect insured patients.
Rural hospitals: In 2024, 46% of rural hospitals operated at a loss. With the proposal, funding is being cut, and responsibility is shifting to states that lack the capacity for transition. In 17 states where rural hospitals make up 50% of all hospitals, particularly in the 7 states where they account for 70%, this presents a significant challenge. Additionally, reduced tax incentives will impact insured patients.
Small health plans: Many smaller health plans lack both the technology and the capital to swiftly address technological demands and compete for state-transferred opportunities.
Community-based Organizations: In addition to experiencing significant funding cuts, these organizations are likely to face an increased demand for their services as other government agencies and programs are shut down. This can cause these organizations to be pushed to their limits, especially if funding must now come from various sources, each with their own agendas and requests for them to fulfill.
The American public’s privacy: Merging data across all of HHS is challenging. However, it also consolidates a lot of people’s incredibly personal medical information. This raises the stakes not just for security in general to protect the data, but also for access control within HHS or any other agencies that might have access (DOGE, for example). Given the President’s directive to do this across all agencies, not just HHS, I am unsure that the vast majority of people could truly understand the volume of personal data the government has across what have been siloed agencies per the 1974 Privacy Act, which has prevented a comprehensive picture of each and every one of us. That’s about to change.

Bureaucracy as Innovation Engine?

To be clear, this represents a consolidation of bureaucratic power at the federal level and states in the document (“a renewed emphasis on federalism”). The question isn’t just whether this reorganization will be effective — it’s whether the federal government can structure itself to learn at scale. If the consolidation results in faster feedback loops, smarter payment experiments, and clearer performance metrics, this could signify the true institutionalization of value-based care.

When centralization causes stagnation, the U.S. health system could reinforce the very issues that Value-Based Care (VBC) aims to address. Additionally, as Medicare and Medicaid become more privatized, innovation may shift toward large health plans. This situation has rendered the commercial insurance market less appealing to many providers since each plan has its own demands and nuances, complicating effective management.

Final Thoughts

I have many thoughts about the document, but I want to focus solely on value-based care and data, as these are two of my biggest passions. Without a doubt, the biggest beneficiaries are large health plans and big data vendors. Large health plans already possess a robust analytics structure and teams, and the consolidation aligns with the administration’s preference to transition more members to Medicare Advantage.

This leaked document likely had many CEOs and venture capitalists in tech sitting up, considering the amount of effort and money involved not only in the consolidation but also in the standardization of data across all of HHS. Those working to build healthcare data platforms just received a new whale to bid on, along with many states and potentially health plans who won’t have the time to build internally, particularly if the government aims to gather all the data from health plans managing patients on its behalf. I am really excited to see what happens with both patient matching and provider matching algorithms, which are set to become increasingly popular products as well.

Regardless of who you are, we can all agree that these are significant and incredibly ambitious changes. Most of this isn’t surprising; many of these were mentioned on the campaign trail and/or in Project 2025. What is surprising is the implementation of so many changes all at once, though it shouldn’t have been, considering the last few months.

Regarding my dual focus, the impact on value-based care isn’t clear. I tried to highlight the potential outcomes based on the budget, but without formal statements regarding VBC, we lack an understanding of the intent behind those budgeting decisions related to it. For that, we just have to wait and see.

As for the data, I am very intrigued. This is a mixed bag for me. I love data; I want to see it consolidated and used for good. The possibilities are MASSIVE. However, I have been working in this industry for over 20 years and have witnessed some really shady situations. HIPAA exists for a reason; before it, they could share your data willy-nilly without informing you. In 2006, my state published the social security numbers of 1.2 million residents. That was just Social Security numbers, done in ignorance of the implications. What happens when people have nefarious intent? This is why data merging is both a winner and a loser, because in all honesty, I just don’t know. I guess it comes down to whether you trust the people involved. While the DOGE team is discussing merging the data across various agencies, the challenges in merging healthcare data extend well beyond their team alone, let alone across all the agencies. AI could be employed to handle some of the work, that is clear. However, that capability does not seem to exist yet in the market, and training the AI to perform correctly will require time. (Whoever does this well — well being the key word, especially if they have a PAAS model so others can build their products on it, will make billions, given that the entire healthcare industry, not just in the US, needs this ability.) We don’t know who will win the bids to do all this work yet, so whether this has a true chance of working is still up in the air.

Please share your thoughts and let me know if you agree or disagree with my interpretation of the document. I would love to know your thoughts.