Home innovation technology concept illustration.

Call for Abstracts — 2022 Petrie-Flom Center Annual Conference: Diagnosing in the Home

Contribute to the 2022 Petrie-Flom Center Annual Conference and subsequent book project!

Through October 14, 2021, the Petrie-Flom Center is accepting abstracts for its annual conference. The 2022 annual conference will focus on ethical, legal, and regulatory challenges and opportunities around at home digital health technology.

This conference will engage with the vision for a 21st century health care system that embraces the potential of at home digital products to support diagnoses, improve care, encourage caregivers, maximize pandemic resilience, and allow individuals to stay within the home when preferable. The goals of this conference and subsequent book project are to consider the ethical, sociological, regulatory, and legal challenges and opportunities presented by the implementation of digital products that support clinical diagnosis and/or treatment in patients’ homes over the next decade.

Interested in submitting an abstract, but want to know more about what we’re looking for? Read through the following frequently asked questions.

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Close up of a computer screen displaying code

Top Health Considerations in the European Commission’s ‘Harmonised Rules on Artificial Intelligence’

By Rachele Hendricks-Sturrup

On April 21, 2021, the European Commission released a “first-ever” legal framework on artificial intelligence (AI) in an attempt to address societal risks associated with AI implementation.

The EU has now effectively set a global stage for AI regulation, being the first nation of member states to create a legal framework with specific intent to address or mitigate potentially harmful effects of broad AI implementation.

Within the proposed framework, the Commission touched on a variety of considerations and  “high-risk” AI system scenarios. The Commission defined high-risk AI systems as those that pose significant (material or immaterial) risks to the health and safety or fundamental rights of persons.

This post outlines four key considerations in the proposal with regard to health: 1) prioritizing emergency health care; 2) law enforcement profiling as a social determinant of health; 3) immigrant health risk screening; and 4) AI regulatory sandboxes and a health data space to support AI product commercialization and public health innovation.

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Fake Vaccine Cards and the Challenges of Decentralized Health Data

By Carmel Shachar and Chloe Reichel

Soon the U.S. will have vaccinated all adults who are not vaccine hesitant. Our next key challenges will be reopening workplaces, restaurants, schools, and other public areas, as well as encouraging vaccine uptake among those who are hesitant or resistant to the vaccine.

Vaccine passports or certifications could be a tool used to address both of those challenges.

But our approach to health care data management may undermine this next stage of the pandemic response.

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empty hospital bed

Regulatory Gap in Health Tech: Resource Allocation Algorithms

By Jenna Becker

Hospitals use artificial intelligence and machine learning (AI/ML) not only in clinical decision-making, but also to allocate scarce resources.

These resource allocation algorithms have received less regulatory attention than clinical decision-making algorithms, but nevertheless pose similar concerns, particularly with respect to their potential for bias.

Without regulatory oversight, the risks associated with resource allocation algorithms are significant. Health systems must take particular care when implementing these solutions.

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Senior citizen woman in wheelchair in a nursing home.

Telehealth and the Future of Long-Term Care

Join us on Wednesday, April 7 for further discussion of these issues during our virtual event, “Triumphs & Tensions of the Telehealth Boom.

By Tara Sklar

The COVID-19 pandemic accelerated the trend away from providing health care and long-term care in institutional settings in ways not previously imagined; the result of a reckoning with the massacre that disproportionately killed hundreds of thousands of older adults living in nursing homes or similar congregate facilities, along with the staff who cared for them.

Beyond the immediate staffing and infection control issues at hand, this juncture leads to a larger question, in the U.S. and abroad: how can we best care for an older population in the decades — and not just years — ahead?

The major advances and shortfalls that have surfaced during the pandemic around telehealth and its related technologies in digital home health care are essential to this discussion.

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Doctor Holding Cell Phone. Cell phones and other kinds of mobile devices and communications technologies are of increasing importance in the delivery of health care. Photographer Daniel Sone.

Viewing Telehealth Policymaking Through the Lens of Disability

Join us on Wednesday, April 7 for further discussion of these issues during our virtual event, “Triumphs & Tensions of the Telehealth Boom.

By Laura C. Hoffman

As a means for delivering health care, telehealth will only be as successful as it is accessible to our most vulnerable populations.

Although the utilization of telehealth has the great potential to increase access to health care while simultaneously reducing barriers to access for individuals, people with disabilities face multiple barriers to telehealth. The COVID-19 pandemic has further highlighted these challenges.

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Apple watch and fit bit.

Beyond HIPAA: A Proposed Self-Policing Framework for Digital Health Products

By Vrushab Gowda

As digital health products proliferate, app developers, hardware manufacturers, and other entities that fall outside Health Insurance Portability and Accountability Act (HIPAA) regulation are collecting vast amounts of biometric information. This burgeoning market has spurred patient privacy and data stewardship concerns.

To this end, two policy nonprofits – the Center for Democracy and Technology (CDT) and the eHealth Initiative (eHI) – earlier this month jointly published a document detailing self-regulatory guidelines for industry. The following piece traces the development of the “Proposed Consumer Privacy Framework for Health Data,” provides an overview of its provisions, and offers critical analysis.

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Code on computer.

Building Trust Through Transparency? FDA Regulation of AI/ML-Based Software

By Jenna Becker

To generate trust in artificial intelligence and machine learning (AI/ML)-based software used in health care, the U.S. Food and Drug Administration (FDA) intends to regulate this technology with an eye toward user transparency. 

But will transparency in health care AI actually build trust among users? Or will algorithm explanations go ignored? I argue that individual algorithm explanations will likely do little to build trust among health care AI users.

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AI concept art.

A Closer Look at FDA’s Newly Released AI/ML Action Plan

By Vrushab Gowda

The U.S. Food and Drug Administration (FDA or “the Agency”) recently issued its long awaited AI/ML (Artificial Intelligence/Machine Learning) Action Plan.

Announced amid the closing days of Stephen Hahn’s term as Commissioner, it takes steps toward establishing a dedicated regulatory strategy for AI products intended as software as a medical device (SaMD), versus those embedded within physical hardware. The FDA has already approved a number of such products for clinical use; however, AI algorithms’ self-learning capabilities expose the limitations of traditional regulatory pathways.

The Action Plan further outlines the first major objectives of the Digital Health Center of Excellence (DHCoE), which was established to much fanfare but whose early moves have remained somewhat unclear. This document presents a policy roadmap for its years ahead.

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