Insights

Both Republicans and Democrats have unveiled their visions for health care ahead of the 2026 midterm elections, with a combined 3 pages of text. The White House released The Great Healthcare Plan for Republicans, while Senate Minority Leader Chuck Schumer (D-NY) took the lead for the Democrats with the Democratic Vision for Health Care. While there were some common mentions, namely improving health care affordability, lowering costs, and holding health insurers accountable, what might be the most revealing is what has been left out of the conversation.

This blog walks through 3 major health policy areas missing from both plans and where we can look beyond these messaging documents for answers to where the parties stand on these health care issues.

The Medicaid Silence

The lack of discussion on Medicaid in either plan is staggering. For a program that covers more than 75 million Americans and is the single largest payer for long-term care, behavioral health, and births in the US, a mention might be warranted. But the Republican plan does not mention Medicaid at all. The Democratic plan fares only slightly better, with vague references to “15 million losing care,” and “750 plus hospitals at risk.” These are claims that Democrats often attribute to changes to Medicaid under the OBBBA due to the implementation of community engagement requirements, changes to state directed payment rates, and limiting provider taxes. However, even though the claims are made, the plan does not reference what actions Democrats would take to strengthen the Medicaid program if they were to flip Congress in November.

For providers that often care for a large share of Medicaid patients, such as safety-net hospitals, managed care plans, and long-term care providers, neither party’s proposal explains what to expect should they be in power. In an industry where information is critical, the silence is deafening.

Workforce: A Value, But No Plan

The health care workforce shortage is arguably one of the most time-sensitive issues facing the health care industry. The Association of American Medical Colleges projects a shortage of 86,000 physicians in the next decade, and the American Association of Colleges of Nursing has shared data which predicts a shortage of 63,720 registered nurses in 2030. Even a fraction of these projections would lead to access challenges due to hospital closures and increasing long wait times for care.

And yet, neither the Republican plan nor the Democratic plan offers input on the many policies suggested to address health care workforce challenges, such as graduate medical education funding, top of license practicing, or improvement of visa programs to allow for more foreign-born nationals to fill the gaps. While the Democratic plan does list “a strong workforce” as a value, a bullet without a mechanism for action does not hold a lot of promise.

The AI Elephant Not in the Room

Artificial intelligence (AI) is the fastest moving area in health care policy, as providers, regulators, and policymakers grapple with how the technology fits into the health care landscape. And yet, neither plan makes any suggestions or offers insight into how each party will approach AI regulation or use in health care settings.

However, now is not the time to be passive. AI is already being used across the federal government, such as for reviewing prior authorizations in Medicare through the Wasteful and Inappropriate Service Reduction (WISeR) Model at the Centers for Medicare and Medicaid Services (CMS) or aiding in approving drug applications at the Food and Drug Administration (FDA). Without a clear path forward for federal action, individual state regulations could create a haphazard regulatory environment for providers, health systems, and pharmaceutical companies to navigate.

Reading Between the Lines

In Washington, you often have to look deeper than the messaging documents that make the headlines. To understand where the parties actually stand on these issues, and not just what they will be campaigning on, looking past the press releases to see what the White House and leaders of health care committees in Congress are working on can fill in the gaps and provide context.

• Medicaid: Republicans have been laser-focused on fraud, which can be seen by recent actions taken by CMS to pause hospice and home health agency enrollment in Medicare and the House Ways and Means hearing on preventing Medicare fraud. In contrast, Democrats have highlighted the impacts of OBBBA Medicaid funding changes in reports and have advocated for their reversal at numerous hearings.
• Health Care Workforce: There are numerous bipartisan bills that have been introduced to address the health care workforce crisis; however, each party has preferred proposals. Republicans often support bills to improve domestic supply of physicians, improving rural training programs, and reducing administrative burden. On the other hand, Democrats have emphasized expanding funding for health care training facilities and expanding immigration pathways as a stopgap.
• AI: The Trump administration has been pro-adoption of AI in health care, including releasing an RFI on Use of AI as Part of Clinical Care, issuing a proposed rule with provisions intended to make it easier for AI to be used as it relates to electronic health information, and implementing the WISeR model. Republicans have generally supported these moves, while Democrats have been much more skeptical. For example, congressional democrats have introduced bicameral legislation to prevent the WISeR Model from going into effect.

What This Means for Health Care Leaders

With the plans released and the midterms fast approaching, here are a few takeaways on how best to engage with the health policy landscape and shape your federal engagement strategy.

• Don’t focus only on the plans: while helpful guides, these plans are only campaign tools. Policy decisions are still being made in committee rooms and in agency offices. Tracking and understanding these updates can provide important context.
• Engage with decision makers now: movement is happening in health policy, regardless of campaign promises. Providing input to agencies through comment letters and meetings with lawmakers is more important than ever if you want your perspective represented.
• Watch the year-end vehicles and other legislative packages: These are the most likely avenues for policy to move. Tracking and advocating on legislation can continue to advance your interests.

The Bottom Line

Both health care plans reflect each party’s desire to address health affordability concerns but leave out other key health policy conversations. These messaging exercises help to highlight what they want voters to focus on in the lead up to the November midterms, but if you want to understand what is truly happening in Washington, looking at the actions of the administration and leaders of health care committees in Congress can help to shape federal engagement strategies and give a better sense of what is – or isn’t – coming.

As of March 2026, the Food and Drug Administration (FDA) has authorized over 1,400 AI-enabled devices for market use. To help achieve this, the FDA has worked to adapt a framework originally built for static devices into one capable of governing adaptive, learning software. 

Having advanced framework for marketed AI devices, the FDA is now turning its attention to AI inside live clinical trials. In April 2026, the FDA announced the Real Time Clinical Trial (RTCT) initiative. RTCT will allow real-time clinical trial data to be transmitted directly from hospital sites to the FDA and will use AI to analyze predefined signals on safety, efficacy, dosing, and adverse events to give FDA reviewers earlier insight into how a trial is progressing. The agency has already successfully initiated proof-of-concept trials, announced the pilot program to begin in August, and submitted a Request for Information (RFI) regarding the program’s design and implementation. The FDA has explicitly stated that the pilot is designed only for early-phase (Phase 1 and 2) trials. 

This blog explores what guidance FDA has created for AI-enabled devices, why that framework doesn’t extend to clinical trials, and what needs to happen before RTCT launches. 

The Existing Framework: AI-Enabled Medical Devices 

For decades, the FDA’s authorization of medical devices has followed the same process: a device is reviewed, authorized, and remains unchanged. Any significant modification required submission from the device manufacturer. This system works for static devices, but not for AI, which depends on its ability to change. 

The FDA has taken steps to improve how the agency handles authorization of AI-enabled medical devices, publishing two significant frameworks in 2025. The agency published the Total Product Life Cycle (TPLC) draft guidance which requires manufacturers to document how AI tools are taught, how bias is assessed throughout the building process, and how the tool will be monitored on the market. The FDA also finalized its Predetermined Change Control Plan (PCCP), which allows manufacturers to define anticipated AI modifications and get pre-authorization for those specific changes.  

TPLC and PCCP create a solid regulatory environment for AI in medical devices, which can be anticipated and pre-authorized. The FDA has created a clear pathway for manufacturers and a structured system to monitor the devices. The framework is not complete, TPLC remains a draft, but there is real progress. However, this work was designed on the assumption that a manufacturer can control and anticipate the changes its AI will make. RTCT breaks that assumption entirely. 

The New Frontier: AI in Live Clinical Trials 

Clinical trials occupy a fundamentally different regulatory space than devices. They are governed by the Center for Drug Evaluation and Research (CDER), have different statutory authorities, and have different stakeholders.  

RTCT would change how FDA reviewers access and analyze trial information. Rather than waiting for submitted data packages, reviewers would receive predefined signals, analyzed by AI, as the trial is actively running.  The FDA issued draft guidance in January 2025 on the use of AI to support regulatory decision-making for drugs and biologics. This is the closest analog to what RTCT would do, but it remains a draft more than a year later with no finalization timeline announced. 

The frameworks built for devices do not apply here, as they were created for manufacturers who control their AI systems. RTCT involves AI operating on live trial data to analyze signals that no existing regulatory framework governs. 

Concerns with RTCT 

As the FDA develops the regulatory framework for AI in clinical trials, stakeholders have four critical questions regarding how RTCT will actually function. 

Accountability: Who Is Responsible When AI Gets It Wrong? 

Under RTCT, AI-analyzed signals will directly inform consequential reviewer decisions, including whether to stop a trial arm, change a dose, or accelerate enrollment. Yet no existing policy assigns responsibility when an AI-generated signal is flawed and a resulting decision causes patient harm. The answer to this question matters for determining who has oversight and the extent to which there is public trust in this initiative.  

Bias: How will RTCT address concerns about bias? 

RTCT will process live data continuously from a small number of academic medical centers, where data may not reflect national diversity. Bias can emerge dynamically in the data as it accumulates in ways a pre-trial assessment cannot detect. There is no existing policy that requires ongoing bias monitoring during a live trial, and there is no infrastructure to mandate or receive such reporting. 

Auditability: Will there be an opportunity for stakeholders to challenge RTCT decisions?  

There is currently no requirement that AI signal outputs be logged in a form that can be reviewed, explained, or challenged after the fact. Without a mandatory audit trail, stakeholders have no mechanism to challenge or reconstruct decisions that shaped a drug’s approval pathway. At the May 15 stakeholder session, FDA officials acknowledged that data cleaning, governance, and quality-control requirements for the signal stream have not yet been finalized. 

Success Metrics: How will the FDA know if RTCT is working? 

A fourth concern emerged directly from the May 15 stakeholder session as the FDA has not yet defined how it will measure whether RTCT actually improves decision-making. Launching a pilot without predefined performance criteria makes it difficult to evaluate whether the program should be expanded or stopped. 

RTCT Comment Period 

The April 28th RTCT announcement included a request for comments on how the initiative should be designed and evaluated. Comments received to date reflect the concerns above with stakeholders urging the FDA to: 

• Require capture of underrepresented populations in AI training data 
• Establish version-traceable lineage so that model changes can be audited 
• Incorporate patient advocate oversight into RTCT governance structures 
• Review site-level operation data to monitor for performance disparities across sites 
• At the May 15 session, stakeholders also requested an extension to the comment period, but the FDA declined to commit to an extension.

What’s Next? 

As the comments demonstrate, actually creating regulations for the RTCT is a difficult process. There is one additional variable that cuts across all of the above: FDA capacity. The agency has lost nearly 15% of its workforce since 2023 and is operating without a confirmed commissioner.  Adding to the uncertainty, Jeremy Walsh, FDA’s first-ever chief AI officer and the official who led the May 15 session, has since resigned from the agency. The RTCT pilot is an ambitious project for an agency that is being asked to do more with considerably less, including the person who architected the program. 

Congress has also taken notice but has not yet acted. The House Energy and Commerce Health Subcommittee held hearings in 2025 examining AI in health care and the Senate HELP Committee flagged FDA modernization as a priority. However, the hearings have not produced legislation, and the administration’s own National Policy Framework for AI, released in March 2026, is only a blueprint for Congress. 

The most consequential near-term legislative vehicle would be one of the FDA user fee reauthorization bills. Congressional authorization for both the Medical Device User Fee Amendments (MDUFA) and the Prescription Drug User Fee Act (PDUFA) expires on September 30, 2027. These programs fund the FDA’s pre-market review operations and are widely considered “must-pass” legislation. Congress has historically used these reauthorization bills to enact broader FDA policy reforms, meaning these could codify AI regulatory authorities for medical devices and clinical trials. Negotiations between the FDA and industry are already underway, meaning stakeholder engagement in that process starts now. 

Conclusion 

The FDA’s progress on AI-enabled medical devices is real and has given the device industry a clearer regulatory path and agency oversight model. The clinical trial space is a different story. RTCT represents one of the most ambitious uses of AI in clinical research and if it works correctly, has the potential to vastly compress drug development timelines. But the risks are real. AI-analyzed signals will directly inform consequential regulatory decisions without finalized standards for accountability, bias monitoring, auditability, or success measurement. The official who built this program has resigned, and no successor has been named. The existing frameworks, TPLC and PCCP, were not designed for this case and the draft guidance closest to it remains unfinalized. Regulatory rules for AI in clinical trials are being written now. Stakeholders who engage in this process will help write those rules and those who wait will inherit them.  

The RTCT public comment period closes May 29, 2026. Comments can be submitted here.