Artificial intelligence (AI) is transforming healthcare systems, promising efficiency and cost savings. But for attorneys handling cases involving denied treatments or delayed care, AI is also introducing new complexities.
Prior authorization (PA), a process designed to control healthcare costs, can already delay critical care. The integration of AI in PA can exacerbate these challenges.
In this article, we’ll explore what PA is, how AI is being used to reshape it, and the risks and opportunities this technology presents for both healthcare and legal cases.
What is Prior Authorization?
Prior authorization (PA) is a cost-control process requiring healthcare providers to get insurance approval before delivering certain medical services. While designed to manage costs, it can also be a barrier to timely, patient-centered care.
The American Medical Association (AMA) reports that over 93% of physicians experience significant delays in medically necessary care due to PA, with serious adverse events, including hospitalizations, permanent harm, or even death, occurring at an alarming rate.
For attorneys, these delays and denials can become critical evidence in cases involving insurance disputes and personal injury matters.
While integrating AI into PA systems has the potential to streamline tasks for healthcare professionals, it can present some concerns due to the lack of regulatory oversight. The challenge is striking the right balance between AI working for healthcare workers and not against patients.
Pros of AI in Prior Authorization
AI use in healthcare has increased exponentially over the past few decades. Tasks such as diagnostics, safety and risk alerts, remote monitoring, and patient communication have seen growing benefits.
AI allows healthcare providers to identify patterns and anomalies that may not have been obvious to humans, allowing physicians to tailor treatments based on unique patient data, medical history, and genetics.
When properly supervised and regulated, AI can revolutionize the PA process by saving time, reducing costs, and improving consistency in decision-making.
Pros of using AI in PA include:
- Streamlined processes: AI can dramatically reduce the time healthcare providers spend on manual tasks such as inputting, verifying, and approving PAs.
- Cost efficiency: By automating steps traditionally requiring human input, such as nurse screenings and medical director reviews, AI can significantly decrease administrative costs. Traditional PA reviews can cost hundreds of dollars per claim, while AI tools can process claims faster and at a fraction of the cost, allowing insurers to assess more cases promptly.
- Consistency: AI enhances consistency in decision-making, reducing variability across cases and ensuring patients receive equitable treatment decisions.
The challenge is to keep AI working for healthcare providers instead of creating more work for them.
Challenges and Risks of AI in Prior Authorization
Despite its potential, AI in PA comes with limitations and risks that must be addressed to prevent harm to patients and providers.
Risks and limitations of using AI in PA include:
- Data dependency: AI is only as reliable as the data it processes. The errors, inaccuracies, and biases input by users can lead to flawed decisions and perpetuate inconsistencies.
- Overriding physicians: Some AI systems have overridden physicians’ determinations, resulting in denied access to medically necessary treatments. Federal lawsuits across 30 states have highlighted error rates as high as 90% in certain AI tools, contributing to poor clinical outcomes.
- Cost-driven decisions: AI’s efficiency may inadvertently prioritize cost-effectiveness over patient care, leading to delays or denials of more expensive but necessary treatments.
- Coverage gaps: One of the most alarming concerns is reports that some predictive AI algorithms pinpoint when they can cut off payments, leaving some patients suddenly without necessary coverage for ongoing treatment.
Balancing AI Innovation with Patient-Centered Care
Regulatory gaps in AI-driven PA processes create potential problems that highlight the need for better oversight. While new transparency rules have been implemented, regulations on how PA decisions are made and proper supervision have yet to be established.
Legislation has been filed in 30 states to address various PA issues. Among other provisions, these laws would:
- Set limits on response times for authorization requests.
- Require licensed physicians in the same specialty as the patient’s condition to make final decisions.
- Prohibit retroactive denials of previously authorized treatments and procedures.
- Validate authorizations for the duration of care for chronic conditions.
- Require the public release of PA data.
- Require new health plans to honor PAs for a minimum of 90 days.
The Role of Regulation in AI Accountability
To ensure AI-powered PA enhances healthcare rather than undermines it, robust regulations are essential. Insurers should be required to publish data on their AI-driven PA processes, fostering accountability and transparency. Equitable practices must also be prioritized by rigorously validating AI tools to reduce delays and improve patient outcomes.
As legal professionals, staying informed about these evolving technologies empowers you to advocate effectively for your clients and anticipate opposing counsel’s strategies. The primary objective of integrating AI into healthcare should always be to enhance the effectiveness of care while centering the patient’s needs.
Further Navigating AI’s Impact on Healthcare
In part two of this article, we’ll explore real-world examples of AI’s growing role in healthcare, the risks of algorithmic bias, and the implications for the patient-physician relationship.
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Sources:
- 2023 AMA prior authorization physician survey | American Medical Association
- AI And Health Insurance Prior Authorization: Regulators Need To Step Up Oversight | HealthAffairs
- Should AI be used in health care? Risks, regulations, ethics and benefits of AI in medicine | American Medical Association
- UNITED STATES DISTRICT COURT DISTRICT OF MINNESOTA CLASS ACTION COMPLAINT
- Denied by AI: How Medicare Advantage plans use AI to cut off care for seniors in need | STAT
- Medicare and Medicaid Programs; Patient Protection and Affordable Care Act; Advancing Interoperability and Improving Prior Authorization Processes for Medicare Advantage Organizations, Medicaid Managed Care Plans, State Medicaid Agencies, Children’s Health Insurance Program (CHIP) Agencies and CHIP Managed Care Entities, Issuers of Qualified Health Plans on the Federally-Facilitated Exchanges, Merit-Based Incentive Payment System (MIPS) Eligible Clinicians, and Eligible Hospitals and Critical Access Hospitals in the Medicare Promoting Interoperability Program | Federal Register
- Bills in 30 states show momentum to fix prior authorization | American Medical Association
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