Medicine and the Law

Legislative Session Preview

Heavy on Technology and AI Considerations

BY David Holt, JD

The sheer volume of health care-related filings in 2026 suggests that the era of incrementalism may be ending. Legislators are no longer tinkering at the margins of policy; they are questioning the fundamental architecture of how care is delivered, paid for and audited. For the practicing physician, these bills represent more than just administrative changes, they represent a potential reclaiming of clinical autonomy.

Medicaid Reform and the Retail OP Market (SF1261)

The authors of SF1261 propose a revolutionary shift by creating a retail outpatient medical market for public program enrollees. This bill aims to empower patients with direct funding for onsite payments, effectively removing Managed Care Organizations (MCOs) from the administration of MinnesotaCare and Medical Assistance. Proponents believe this will streamline access and reduce the administrative overhead that often bogs down public programs, creating a frictionless environment for both patients and providers.

By shifting to a retail model, the state would essentially bypass the middleman. Currently, the state pays MCOs a capitated rate, a fixed amount per member per month, to manage the health of enrollees. Under SF1261, the funding would follow the patient more directly to the point of care. This could theoretically allow physicians to be paid at the time of service, mirroring the efficiency of the private cash-pay or direct primary care (DPC) markets, but scaled for the public safety net. For many independent practices, this could be the difference between remaining solvent or being forced into a large hospital system acquisition.

Legislators are no longer tinkering at the margins of policy.

Opponents, such as the Council of Health Plans, warn that the state may be unable to manage the complexities of direct billing and claims administration. They argue that MCOs provide more than just payment processing; they provide population health management, data analytics and narrow-network coordination that keeps costs predictable. Critics of the bill cite concerns regarding increased fraud and the logistical nightmare of replacing a system that has been the standard for decades, despite its known friction points.

Furthermore, there is a technical concern regarding claims leakage and how the state would handle catastrophic costs that exceed a retail budget. The debate ultimately hinges on a fundamental question: is the friction of MCOs a bug or a feature designed to control costs? If it is a feature, removing it might lead to a surge in utilization that the state budget cannot sustain. If it is a bug, removing it could spark a renaissance for independent medical practice in Minnesota.

Prohibiting AI in Prior Authorization (HF2500)

This controversial bill pits business interests against patient care in the rapidly evolving AI world. The authors propose an explicit prohibition on the use of algorithms or artificial intelligence in the review of health insurance prior authorization (PA) requests. Introduced as a direct response to rising frustration among both patients and physicians, this bill addresses high denial rates and treatment delays that have become synonymous with modern utilization management.

There is significant concern that AI systems, if left unregulated, could exacerbate these issues by prioritizing averted expenditure over actual patient health needs. Proponents of the ban argue that current AI systems, often referred to as black boxes because their decision-making logic is opaque, are designed primarily to increase denial rates. In some documented cases nationally, algorithms have been used to deny claims in batches, with reviewing physicians spending less than an average of 1.2 seconds per case. This financial incentive creates a profound conflict of interest that can lead to systematic denials with little to no human oversight.

Algorithmic Malpractice Regulators and medical boards remain wary that allowing an algorithm to make final coverage denials could be legally interpreted as practicing medicine without a license. Because these decisions directly dictate whether a patient receives a specific treatment, they are viewed by many as medical determinations. If a computer makes that call, who is held liable when a denial leads to a catastrophic patient outcome? The legal framework for algorithmic malpractice is nonexistent, leaving physicians in the lurch when they are forced to fight a machine for their patient’s life.

Opponents of the bill point to the potential for AI to streamline what is currently a slow and paper-heavy process. They argue that digitizing prior authorization and using machine learning could make the process significantly faster, potentially reducing the time patients wait for care by days or even weeks. Some insurers suggest that AI can be used for gold-carding or auto-approvals in clear-cut cases, which would actually reduce the administrative burden on physician offices.

Banning AI in Utilization Review (SF1856)

While HF2500 targets the gatekeeping phase of the initial request, SF1856 goes deeper into the ongoing management of care. The authors propose a ban on AI specifically within utilization review (UR) for health insurance. By defining artificial intelligence clearly within the statute, referencing existing federal definitions, the bill aims to ensure that critical coverage decisions remain in the hands of human professionals who are accountable for their medical judgment.

The central theme here is the protection of the nuanced, personalized approach to medicine that automated systems struggle to replicate. Physicians report that unregulated AI frequently overrides clinical evidence and good medical judgment in favor of rigid data points. In a recent survey, over 90% of doctors noted that these automated guidelines had a negative impact on clinical outcomes for their patients. The nuance of a patient’s co-morbidities or social determinants of health is often lost on an algorithm that is programmed to look for the average case.

The legal framework for algorithmic malpractice is nonexistent.

The Bias in the Machine The bill also seeks to prevent the use of predictive technologies that may introduce systemic bias. For example, if an algorithm is trained on historical data that show lower utilization or poorer outcomes in certain zip codes, it might inadvertently learn to deny care more frequently to patients from those areas, codifying existing health care disparities into a digital standard of care. By mandating human-centric review, SF1856 attempts to keep the art of medicine alive in a world increasingly dominated by data science.

Opponents caution that a total ban might be a blunt instrument that stifles innovation. They suggest that instead of a ban, the state should focus on human-in-the-loop requirements —guardrails that require human sign-off for any denial while still allowing AI to assist in gathering data or flagging administrative errors. They argue that AI is excellent at spotting a missing lab result or an incorrectly coded procedure, which could save human reviewers hours of manual labor.

The Patient-Centered Care Bill (SF 1059)

The authors of the Patient-Centered Care Bill propose a complete overhaul of how MinnesotaCare and Medical Assistance are administered. Building on the themes of SF1261, this legislation seeks to return the focus to the patient-physician relationship by removing the intermediary MCO layer entirely.

Under the current system, the carve-out of various services to different managers has led to a fragmented experience for patients. A patient might have one entity managing their physical health, another for their mental health, and a third for their pharmacy benefits. This siloed approach often results in dropped balls, where a mental health provider is unaware of a physical health change because they are operating under different administrative umbrellas. This bill proposes a unified, state-administered system that prioritizes continuity of care over the management style of private insurers.

Opponents argue that these organizations provide necessary coordination of care and cost-containment measures that the state is not equipped to handle internally. They point to the 1990s as a time of runaway costs and uncoordinated services. Proponents, however, argue that the 2026 version of the state government has significantly better data tools and digital infrastructure than it did 30 years ago, making a state-run fee-for-service or value-based model more viable than ever.

General Prior Authorization Reform (Chapter 127)

While new bills are being debated, it is important to note that Minnesota already passed broader legislation effective this year to reform prior authorization. Chapter 127 was designed to limit the use of PA for certain high-stakes services, such as:

• Outpatient mental health services.
• Initial cancer treatments and oncology medications.
• Post-stabilization emergency care.
• Medication-assisted treatment (MAT) for substance use disorders.

The current session will likely debate how these existing laws interact with the new proposals to ban AI. There is a risk of legislative clutter, where overlapping laws create confusion for providers and insurers alike. Opponents of further reform argue that the 2026 changes should be allowed to mature — essentially giving the ink time to dry — before adding more layers of regulation.

Advocates for children with complex medical conditions argue, however, that even with Chapter 127 in place, insurers are finding workarounds to delay expensive therapies. For these families, the move to ban AI isn’t just a policy preference; it’s a desperate attempt to force a human being to look at their child’s chart and see more than a line item on a spreadsheet.

Conclusions and Considerations

Beyond the clinical implications, these bills represent what could be a massive shift in the Minnesota health care economy. If MCOs are removed from the public sector, billions of dollars in state contracts will be reshuffled. This could lead to a more competitive market for providers but might also lead to initial volatility in reimbursement rates as the state builds out its own payment infrastructure.

Physicians must also consider the AI arms race. If Minnesota bans insurance AI, but the rest of the country adopts it to lower administrative costs, does Minnesota become an island of high-touch, high-cost care? Or does it become a sanctuary for physicians who are burnt out by algorithmic medicine? There is a potential for Minnesota to attract top-tier medical talent looking for an environment where clinical autonomy is legally protected. Conversely, there is the risk that national insurers might raise premiums in the state to offset the higher costs of manual human labor.

Furthermore, we must consider the impact on medical education. If the next generation of physicians is trained in a state where AI is banned from the insurance process, will they be prepared to work in other states where AI is the primary interface? These are the long-term, existential questions that the 2026 session aims to answer.

David Holt, JD, is a health care attorney at Holt Law, a firm specializing in health care law.