AHA Responds to OSTP Request on AI Policies for Health Care – American Hospital Association

Advancing Sustainable Development Goals through Artificial Intelligence in Healthcare: A Policy Framework Analysis

This report analyzes the American Hospital Association’s (AHA) recommendations to the Office of Science and Technology Policy (OSTP) on regulatory reform for Artificial Intelligence (AI). The analysis frames these recommendations within the context of the United Nations Sustainable Development Goals (SDGs), highlighting how strategic AI regulation can advance global targets for health, equality, and innovation. The AHA underscores that AI can significantly reduce the over $1 trillion spent annually on administrative tasks, freeing resources to enhance patient care and system sustainability, directly contributing to SDG 3 (Good Health and Well-being) and SDG 8 (Decent Work and Economic Growth).

Harmonizing Policy Frameworks for Sustainable Innovation (SDG 9, SDG 16)

To foster an environment of responsible innovation in line with SDG 9 (Industry, Innovation, and Infrastructure), it is imperative to synchronize new AI policies with existing regulatory frameworks. This approach avoids redundancy and builds effective, accountable institutions as targeted by SDG 16 (Peace, Justice, and Strong Institutions).

Leveraging Existing Regulatory Structures

The development of AI policy should not occur in isolation but must be integrated with established healthcare regulations to ensure coherence and efficiency. Key existing frameworks include:

• Data Privacy: HIPAA provides foundational standards for protecting health information, a cornerstone for patient trust and safety central to SDG 3.
• Cybersecurity: Voluntary frameworks from the National Institute of Standards and Technology (NIST) and the Department of Health and Human Services (HHS) offer robust standards for securing health infrastructure.
• Premarket Testing: Food and Drug Administration (FDA) regulations for Software as a Medical Device (SaMD) ensure the safety and efficacy of AI tools before deployment.
• Transparency and Anti-discrimination: HHS requirements ensure AI tools are transparent and do not perpetuate biases, supporting SDG 10 (Reduced Inequalities).
• Access to Care: Centers for Medicare & Medicaid Services (CMS) regulations mandate that AI cannot be the sole arbiter in denying services, safeguarding equitable access to care.

Synchronizing policies with these frameworks will prevent inefficiency and support the safe, effective use of AI, contributing to resilient health systems.

Removing Regulatory Barriers to Advance Health and Well-being (SDG 3, SDG 10)

Current regulatory complexities can inhibit the development and deployment of beneficial AI tools, hindering progress toward SDG 3 (Good Health and Well-being). Addressing these barriers is essential for unlocking AI’s potential to improve patient outcomes and reduce systemic costs.

Recommendations for Regulatory Modernization

1. Modernize Privacy and Security Rules: While foundational, certain HIPAA provisions require modification to support modern cybersecurity realities without imposing infeasible requirements on providers. A focus on voluntary, consensus-based standards is recommended over punitive measures, recognizing that cybersecurity risks often originate from third-party vulnerabilities.
2. Establish Federal Preemption for Data Privacy: The current patchwork of state privacy laws creates significant compliance burdens and impedes the data sharing necessary for developing effective AI tools and coordinating care. Strengthening HIPAA preemption would create a unified standard, reducing administrative waste and supporting the goals of SDG 3 and SDG 10 by enabling more robust population health initiatives.
3. Align Substance Use Disorder (SUD) Data Regulations: The requirements of 42 CFR Part 2 create barriers to integrated, whole-person care by siloing SUD data. Aligning these regulations with HIPAA would facilitate better care coordination and allow SUD providers to leverage AI tools, directly advancing targets within SDG 3.

Ensuring Safe and Equitable AI for All (SDG 3, SDG 10)

The deployment of AI in healthcare must prioritize patient safety and equity, core tenets of SDG 3 and SDG 10. A robust policy framework is necessary to balance innovation with public interest, ensuring AI tools are used responsibly and effectively.

Key Policy Recommendations

• Mandate Clinician Oversight: To prevent inappropriate denials of care, particularly by commercial insurers using automated systems, AI tools must not act alone. A trained clinician must be included in the decision-making loop for any denial of services, ensuring that medical necessity, not algorithmic output, is the final determinant. This protects patient access to care, a critical component of SDG 3.
• Enforce Consistent Third-Party Standards: As data breaches increasingly originate from third-party vendors, it is crucial to hold all entities that handle protected health information (PHI), including AI vendors, to the same rigorous privacy and security standards as healthcare providers. This strengthens the entire health data ecosystem.
• Develop Post-Deployment Monitoring Standards: The “black box” nature of some AI models necessitates ongoing evaluation to ensure their validity and integrity post-deployment. Establishing voluntary, stakeholder-developed standards for continuous testing will help identify and mitigate biases or inaccuracies, ensuring AI tools remain safe and effective over time, thereby supporting both SDG 3 and SDG 10.

Building Inclusive Infrastructure for AI Adoption (SDG 9, SDG 10, SDG 17)

Widespread and equitable adoption of AI in healthcare depends on addressing foundational organizational and infrastructural factors. This requires a multi-faceted approach aligned with SDG 9 (Industry, Innovation, and Infrastructure), SDG 10 (Reduced Inequalities), and SDG 17 (Partnerships for the Goals).

Addressing Systemic Challenges

1. Align Financial Incentives: Many health systems lack the resources to invest in AI due to inadequate reimbursement. Aligning payment models and incentives to support the adoption of new technologies is critical for enabling providers to leverage AI for improved efficiency and patient care, contributing to the economic sustainability of the health sector.
2. Bridge the Digital Divide: Significant disparities in access to broadband, smartphones, and digital literacy prevent rural and underserved populations from benefiting from digital health innovations. With over 22% of rural Americans lacking broadband access, addressing this digital divide is fundamental to achieving SDG 10. This requires investment in foundational infrastructure and patient education.
3. Foster Cross-Sector Collaboration: Overcoming these infrastructural barriers necessitates partnerships, as envisioned in SDG 17. Collaboration between government agencies (HHS, FCC, Department of Commerce), healthcare providers, and technology companies is essential to develop training and funding opportunities that support equitable access to digital health tools for all communities.

Analysis of Sustainable Development Goals in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

• SDG 3: Good Health and Well-being: The article is fundamentally about the healthcare sector. It discusses improving the quality and efficiency of care delivery, reducing administrative costs to ensure the financial sustainability of hospitals, enhancing patient access to services, ensuring patient safety in the use of AI, and integrating care for substance use disorders.
• SDG 9: Industry, Innovation, and Infrastructure: The article focuses on creating a regulatory framework for a key technological innovation (Artificial Intelligence) within the healthcare industry. It also explicitly addresses the need for infrastructural investment, particularly in broadband and digital technologies, to ensure equitable adoption of AI tools.
• SDG 10: Reduced Inequalities: The article highlights the “digital divide,” where rural and underserved populations have less access to digital health tools due to infrastructural barriers. It also addresses the need to prevent AI tools from introducing or exacerbating discrimination, particularly in decisions about access to care and insurance claim denials.
• SDG 16: Peace, Justice, and Strong Institutions: The core of the article is a recommendation for developing effective, accountable, and transparent policy and regulatory frameworks (“strong institutions”) for AI in healthcare. It discusses data privacy, cybersecurity, and the need for clear, non-redundant regulations that protect fundamental freedoms while enabling innovation.

2. What specific targets under those SDGs can be identified based on the article’s content?

SDG 3: Good Health and Well-being

• Target 3.8: Achieve universal health coverage, including financial risk protection, access to quality essential health-care services and access to safe, effective, quality and affordable essential medicines and vaccines for all. The article connects to this target by discussing how reducing the administrative cost burden (over $1 trillion annually) can improve the financial sustainability of the healthcare system. It notes that financial instability has led some hospitals to “scaled back services or closed outright,” directly impacting access to care.
• Target 3.5: Strengthen the prevention and treatment of substance abuse, including narcotic drug abuse and harmful use of alcohol. The article specifically identifies regulations under “42 CFR Part 2” as a barrier that “prevents the integration of behavioral and physical health care” for patients with substance use disorder (SUD), hindering coordinated, whole-person care and impacting the ability of SUD providers to leverage AI tools.
• Target 3.d: Strengthen the capacity of all countries, in particular developing countries, for early warning, risk reduction and management of national and global health risks. The article’s extensive focus on cybersecurity addresses a major risk to the healthcare system. It highlights that “the number of individuals impacted by health care data breaches increased from 27 million in 2020 to a staggering 259 million in 2024,” emphasizing the need to manage this systemic risk.

SDG 9: Industry, Innovation, and Infrastructure

• Target 9.1: Develop quality, reliable, sustainable and resilient infrastructure, including regional and transborder infrastructure, to support economic development and human well-being, with a focus on affordable and equitable access for all. The article directly addresses this by pointing out infrastructural barriers to AI adoption, such as the lack of broadband. It states that this lack of infrastructure contributes to the “digital divide,” limiting access to digital services in rural and underserved areas.
• Target 9.5: Enhance scientific research, upgrade the technological capabilities of industrial sectors in all countries, in particular developing countries, including, by 2030, encouraging innovation and substantially increasing the number of research and development workers per 1 million people and public and private research and development spending. The entire letter is a response to creating a policy framework that can “accelerate innovation” in AI. It advocates for a balance that allows “flexibility to enable innovation while ensuring patient safety” to maximize the potential of AI to transform care.
• Target 9.c: Significantly increase access to information and communications technology and strive to provide universal and affordable access to the Internet in least developed countries by 2020. This target is directly referenced when the article cites the Federal Communications Commission (FCC) report that “over 22% of Americans in rural areas lacked access to appropriate broadband,” which hinders the expansion of digital health and AI tools.

SDG 10: Reduced Inequalities

• Target 10.2: By 2030, empower and promote the social, economic and political inclusion of all, irrespective of age, sex, disability, race, colour, ethnicity, origin, religion, economic or other status. The article’s discussion of the “digital divide” relates to inequality based on location, where rural populations are excluded from the benefits of digital health due to a lack of infrastructure.
• Target 10.3: Ensure equal opportunity and reduce inequalities of outcome, including by eliminating discriminatory laws, policies and practices and promoting appropriate legislation, policies and action in this regard. This is addressed in the article’s call to prevent bias in AI. It references the “HHS Office for Civil Rights (OCR) Anti-Bias and Discrimination regulations” which prohibit AI tools that discriminate. It also raises concerns that commercial insurers’ use of AI has “exacerbated inappropriate denials,” potentially creating unequal outcomes in access to care.

SDG 16: Peace, Justice, and Strong Institutions

• Target 16.6: Develop effective, accountable and transparent institutions at all levels. The article is a direct contribution to the development of an effective and accountable regulatory framework for AI. It calls for synchronizing existing policies to avoid redundancy, removing regulatory barriers, and establishing clear standards to ensure the safe and effective use of AI, all of which are hallmarks of strong institutional governance.
• Target 16.10: Ensure public access to information and protect fundamental freedoms, in accordance with national legislation and international agreements. The focus on data privacy and security directly relates to protecting the fundamental freedom of privacy. The article discusses the importance of HIPAA, the need for consistent privacy standards for third-party vendors, and the dangers of data breaches, advocating for policies that safeguard personal health information.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

Yes, the article mentions several specific data points and metrics that can serve as indicators to measure progress:

1. Percentage of healthcare spending on administrative tasks: The article states, “More than a quarter of all health care spending goes to administrative tasks — totaling more than $1 trillion annually.” A reduction in this percentage would indicate progress towards a more efficient and sustainable healthcare system (Target 3.8).
2. Financial viability of hospitals: The article notes that “nearly 40% [of hospitals] operating with negative margins.” An improvement in this figure would indicate a more stable health system capable of providing consistent access to care (Target 3.8).
3. Number of individuals affected by healthcare data breaches: The article cites a dramatic increase from “27 million in 2020 to a staggering 259 million in 2024.” Tracking this number would serve as a key indicator of cybersecurity effectiveness and risk management in the health sector (Target 3.d).
4. Broadband accessibility gap: The article references an FCC report that “over 22% of Americans in rural areas lacked access to appropriate broadband… compared to 1.5% of urban areas.” This disparity is a direct indicator of the infrastructural inequality and the “digital divide” (Targets 9.1, 9.c, and 10.2).
5. Access to enabling technologies among vulnerable populations: The statistic that “over 26% of Medicare beneficiaries reported not having computer or smartphone access at home” serves as an indicator of the digital divide and barriers to adopting digital health tools (Targets 9.1 and 10.2).
6. Rate of inappropriate insurance denials: The article mentions a survey where “62% of doctors think that payer use of AI is increasing denials for medically necessary care.” This perception, along with data on claim denial and appeal rates, can be used as an indicator to measure whether AI is being used in a non-discriminatory way that ensures equal opportunity for care (Target 10.3).

4. Create a table with three columns titled ‘SDGs, Targets and Indicators” to present the findings from analyzing the article.

Source: aha.org