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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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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lady justice.

Computational Psychiatry for Precision Sentencing in Criminal Law

By Francis X. Shen

A core failing of the criminal justice system is its inability to individualize criminal sentences and tailor probation and parole to meet the unique profile of each offender.

As legal scholar, and now federal judge Stephanos Bibas has observed, “All too often … sentencing guidelines and statutes act as sledgehammers rather than scalpels.”

As a result, dangerous offenders may be released, while offenders who pose little risk to society are left behind bars. And recidivism is common — the U.S. has an astounding recidivism rate of 80% — in part because the current criminal justice system largely fails to address mental health challenges, which are heavily over-represented in the justice system.

Advances in computational psychiatry, such as the deep phenotyping methods explored in this symposium, offer clinicians newfound abilities to practice precision psychiatry. The idea behind precision psychiatry is both simple and elusive: treat individuals as individuals. Yet advancing such a program in practice is “very ambitious” because no two individual brains — and the experiences those brains have had over a lifetime — are the same.

Deep phenotyping offers the criminal justice system the tools to improve public safety, identify low-risk offenders, and modify decision-making to reduce recidivism. Computational psychiatry can lead to what can be described as precision sentencing.

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phone camera

Deep Phenotyping Could Help Solve the Mental Health Care Crisis

By Justin T. Baker

The United States faces a growing mental health crisis and offers insufficient means for individuals to access care.

Digital technologies — the phone in your pocket, the camera-enabled display on your desk, the “smart” watch on your wrist, and the smart speakers in your home — might offer a path forward.

Deploying technology ethically, while understanding the risks of moving too fast (or too slow) with it, could radically extend our limited toolkit for providing access to high-quality care for the many individuals affected by mental health issues for whom the current mental health system is either out of reach or otherwise failing to meet their need.

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Petrie-Flom Center logo.

Call for Applications: Research Fellow for Diagnostic Digital Home Health

Overview

The Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School is hiring a full-time post-doctoral fellow to support its newly launched Diagnostic Digital Home Health initiative. This position will likely be a three year commitment.

This sponsored research project examines the ethical, social, and legal challenges of digital home health products, with a focus on home diagnosis of infectious and chronic conditions. This project will develop scholarship, guidelines, and proposed regulations for the ethical implementation of these products, using focus groups, virtual workshops, and interdisciplinary scholarship, with a focus on considerations of access and equity, social interconnectedness, and patient privacy.

Previous Petrie-Flom Center post-doctoral fellows have used their positions as successful launching pads for tenure-track legal, health policy, and bioethics academic careers. Our most recent post-doctoral fellow has published in leading journals such as JAMA, Science, and the Journal of Law and the Biosciences. She has been interviewed as an expert in biomedical regulation by media outlets such as Forbes and Lancet Digital Health and presented to regulators at the U.S. Department of Health and Human Services.
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Life preserver on boat.

Incidental Findings in Deep Phenotyping Research: Legal and Ethical Considerations

By Amanda Kim, M.D., J.D., Michael Hsu, M.D., Amanda Koire, M.D., Ph.D., Matthew L. Baum, M.D., Ph.D., D.Phil.

What obligations do researchers have to disclose potentially life-altering incidental findings (IFs) as they happen in real time?

Deep phenotyping research in psychiatry integrates an individual’s real-time digital footprint (e.g., texts, GPS, wearable data) with their biomedical data (e.g., genetic, imaging, other biomarkers) to discover clinically relevant patterns, usually with the aid of machine learning. Findings that are incidental to the study’s objectives, but that may be of great importance to participants, will inevitably arise in deep phenotyping research.

The legal and ethical questions these IFs introduce are fraught. Consider three hypothetical cases below of individuals who enroll in a deep phenotyping research study designed to identify factors affecting risk of substance use relapse or overdose:

A 51-year-old woman with alcohol use disorder (AUD) is six months into sobriety. She is intrigued to learn that the study algorithm will track her proximity to some of her known triggers for alcohol relapse (e.g., bars, liquor stores), and asks to be warned with a text message when nearby so she can take an alternative route. Should the researchers share that data?

A 26-year-old man with AUD is two years into sobriety. Three weeks into the study, he relapses. He begins arriving to work inebriated and loses his job. After the study is over, he realizes the researchers may have been able to see from his alcohol use surveys, disorganized text messages, GPS tracking, and sensor data that he may have been inebriated at work, and wishes someone had reached out to him before he lost his job. Should they have?

A 35-year-old man with severe opioid use disorder experiences a near-fatal overdose and is discharged from the hospital. Two weeks later, his smartphone GPS is in the same location as his last overdose, and his wearable detects that his respiratory rate has plummeted. Should researchers call EMS? Read More

Pen hovering over words "I agree" with check box next to it.

Unique Challenges to Informed Consent in Deep Phenotyping Research

By Benjamin C. Silverman

Deep phenotyping research procedures pose unique challenges to the informed consent process, particularly because of the passive and boundless nature of the data being collected and how this data collection overlaps with our everyday use of technology.

As detailed elsewhere in this symposium, deep phenotyping in research involves the collection and analysis of multiple streams of behavioral (e.g., location, movement, communications, etc.) and biological (e.g., imaging, clinical assessments, etc.) data with the goal to better characterize, and eventually predict or intervene upon, a number of clinical conditions.

Obtaining voluntary competent informed consent is a critical aspect to conducting ethical deep phenotyping research. We will address here several challenges to obtaining informed consent in deep phenotyping research, and describe some best practices and relevant questions to consider.

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Person typing on computer.

Lessons Learned from Deep Phenotyping Patients with Rare Psychiatric Disorders

By Catherine A Brownstein and Joseph Gonzalez-Heydrich

Given the potential sensitivities associated with describing (i.e., phenotyping) patients with potentially stigmatizing psychiatric diagnoses, it is important to acknowledge and respect the wishes of the various parties involved.

The phenotypic description and depiction of a patient in the literature, although deidentified, may still be of great impact to a family.

By way of example, a novel genetic variant was identified as a likely explanation for the clinical presentation of a patient in a large cohort of individuals with neurodevelopmental and/or psychiatric phenotypes, a finding of great medical interest. The research team elected to further study this candidate and collected samples for functional evaluation of the gene variant and preparation of a case report.

Because the patient had a complicated phenotype, several physicians from various specialties were involved in the patient’s care. The paper draft was circulated amongst the collaborating clinicians and researchers and ultimately shared with the patient’s family by one of their involved caregivers. This is typically not a requirement of such studies, as the informed consent process includes the subjects’ understanding and consent for dissemination of deidentified results in the scientific literature. But as a general practice, families are informed about manuscripts in process, and in this case the family had requested to be kept abreast of ongoing developments.

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doctor holding clipboard.

“Actionability” and the Ethics of Communicating Results to Study Participants

By Patrick Monette

To what end does a physician have a responsibility toward a research participant? Specifically, what data may be considered “actionable” for the physician to disclose to the patient, and when and how might this be done?

In the clinical setting, contemporary medical ethics address a physician’s “fiduciary responsibility.” That is, there is a well-established professional expectation that the physician will place the patient’s interests above their own and advocate for their welfare. This post focuses on an alternative dyad, that of physician and research participant, to explore how the field has broached the topic of actionability in the setting of clinical research. Read More

Telemedicine or telehealth virtual visit / video visit between doctor and patient on laptop computer and mobile phone device.

The Petrie-Flom Center Launches New Project: Diagnosing in the Home

Diagnosing in the Home will seek to examine the ethical, social, and legal challenges of digital home health products, with a focus on home diagnosis of infectious and chronic conditions.

January 27, 2021 – The Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School today announced a new research initiative, Diagnosing in the Home: The Ethical, Legal, and Regulatory Challenges and Opportunities of Digital Home Health. This three-year project will seek to promote the translation of diagnostic medical services into home health care through regulatory and ethical frameworks. This initiative is generously supported by a grant from the Gordon and Betty Moore Foundation.

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