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The 21st Century Cures Act preserved the FDA’s authority to regulate several categories of software that incorporate artificial intelligence/machine learning (AI/ML) techniques. The agency’s draft guidance on Clinical Decision Support Software proposed an approach for regulating CDS software and shed light on the FDA’s approach to genomic software. This chapter explains why the FDA’s proposed approach to regulating software is unlikely to preempt failure-to-warn suits. It then turns to design-defect suits, focusing on adaptive AI/ML software that continues to redesign itself throughout the product lifecycle. How will common defenses work when the state of the art is in the robotic “mind” of an AI/ML algorithm? We also reflect on broader impacts on patients, clinicians, software developers, and healthcare systems and ask whether the FDA is the “right” regulator to address the unresolved ethical and medical practice concerns that surround this software.
Genetic testing and gene editing are rapidly becoming – indeed, already are – consumer Genetic testing and gene editing are rapidly becoming – indeed, already are – consumer technologies that people can experiment with and apply on their own, potentially without any involvement by traditional payers and research funding agencies, professional scientists and healthcare providers, regulators, and medical product manufacturers. This chapter explores the challenges of regulating direct-to-consumer and do-it-yourself genomic technologies that disrupt the traditional funding, supply arrangements, and roles. It is widely understood that the U.S. Coordinated Framework for biotechnology regulation, even after a 2017 update, is a patchwork of old federal statutes that were never designed for some of the genetic technologies now emerging. This chapter explores four problems that are less well understood: First, consumer genetics poses a fundamental challenge, also seen in the sharing economy exemplified by ride-sharing platforms such as Uber and Lyft. This challenge is one of scale, and the need for regulators to oversee a massive number of small-scale transactions and individual actors. A second challenge is that consumer genetics forces a rethinking of the goals of regulation – specifically, how paternalistic is it appropriate for regulators to be? A third conundrum is whether top-down regulatory approaches can be effective and, if not, how to motivate bottom-up, citizen-led norm-setting and compliance. A final challenge concerns the fact that the human genome itself is, ultimately, software, and many of the consumer products for interpreting and manipulating it also are in the nature of software, yet traditional consumer safety regulators struggle when confronted with the task of regulating software. The chapter concludes that merely expanding the jurisdiction of existing regulatory bodies and granting them new tools and powers will not suffice. A more sweeping redesign of consumer safety regulation will be required.
Archaeologists have pointed to certain architectural or decorative designs as representing “elite styles” that mark status distinctions. We look at one such style—Dogoszhi—that was applied to several pottery wares across the Chaco World of the northern Southwest. Using a large database of ceramics, we test whether this style comprised an elite style or whether it signaled participation in a broader Chaco social network. We compare the distribution of Dogoszhi style to measures of settlement importance, including site size and network centrality, and we investigate whether this style occurs differentially at Chacoan great houses as opposed to small houses, or by subregion. We also compare its spatial distribution to an earlier style, called Black Mesa style, similarly applied to a number of different wares. Our results indicate that both styles were consistently distributed within Chaco communities (whether great houses or small houses) but variably distributed across subareas and most measures of settlement importance. We conclude that Dogoszhi style was used to mark membership in social networks that cross-cut great house communities, a pattern more typical of heterarchical rather than hierarchical social structures. Such variation questions the uniform category of “elites” and points to the ways that representational diversity may be used to interpret different regional histories and alliances.
In the absence of pyuria, positive urine cultures are unlikely to represent infection. Conditional urine reflex culture policies have the potential to limit unnecessary urine culturing. We evaluated the impact of this diagnostic stewardship intervention.
We conducted a retrospective, quasi-experimental (nonrandomized) study, with interrupted time series, from August 2013 to January 2018 to examine rates of urine cultures before versus after the policy intervention. We compared 3 intervention sites to 3 control sites in an aggregated series using segmented negative binomial regression.
The study included 6 acute-care hospitals within the Veterans’ Health Administration across the United States.
Adult patients with at least 1 urinalysis ordered during acute-care admission, excluding pregnant patients or those undergoing urological procedures, were included.
At the intervention sites, urine cultures were performed if a preceding urinalysis met prespecified criteria. No such restrictions occurred at the control sites. The primary outcome was the rate of urine cultures performed per 1,000 patient days. The safety outcome was the rate of gram-negative bloodstream infection per 1,000 patient days.
The study included 224,573 urine cultures from 50,901 admissions in 24,759 unique patients. Among the intervention sites, the overall average number of urine cultures performed did not significantly decrease relative to the preintervention period (5.9% decrease; P = 0.8) but did decrease by 21% relative to control sites (P < .01). We detected no significant difference in the rates of gram-negative bloodstream infection among intervention or control sites (P = .49).
Conditional urine reflex culture policies were associated with a decrease in urine culturing without a change in the incidence of gram-negative bloodstream infection.
Mobile devices with health apps, direct-to-consumer genetic testing, crowd-sourced information, and other data sources have enabled research by new classes of researchers. Independent researchers, citizen scientists, patient-directed researchers, self-experimenters, and others are not covered by federal research regulations because they are not recipients of federal financial assistance or conducting research in anticipation of a submission to the FDA for approval of a new drug or medical device. This article addresses the difficult policy challenge of promoting the welfare and interests of research participants, as well as the public, in the absence of regulatory requirements and without discouraging independent, innovative scientific inquiry. The article recommends a series of measures, including education, consultation, transparency, self-governance, and regulation to strike the appropriate balance.
Regulatory policy for genomic testing may be subject to biases that favor reliance on existing regulatory frameworks even when those frameworks carry unintended legal consequences or may be poorly tailored to the challenges genomic testing presents. This article explores three examples drawn from genetic privacy regulation, oversight of clinical uses of genomic information, and regulation of genomic software. Overreliance on expedient regulatory approaches has a potential to undercut complete and durable solutions.
The individual right of access to one’s own data is a crucial privacy protection long recognized in U.S. federal privacy laws. Mobile health devices and research software used in citizen science often fall outside the HIPAA Privacy Rule, leaving participants without HIPAA’s right of access to one’s own data. Absent state laws requiring access, the law of contract, as reflected in end-user agreements and terms of service, governs individuals’ ability to find out how much data is being stored and how it might be shared with third parties. Efforts to address this problem by establishing norms of individual access to data from mobile health research unfortunately can run afoul of the FDA’s investigational device exemption requirements.
Delivering high quality genomics-informed care to patients requires accurate test results whose clinical implications are understood. While other actors, including state agencies, professional organizations, and clinicians, are involved, this article focuses on the extent to which the federal agencies that play the most prominent roles — the Centers for Medicare and Medicaid Services enforcing CLIA and the FDA — effectively ensure that these elements are met and concludes by suggesting possible ways to improve their oversight of genomic testing.
Transparency is a concept that is becoming increasingly lauded as a solution to a host of problems in the American health care system. Transparency initiatives show great promise, including empowering patients and other stakeholders to make more efficient decisions, improve resource allocation, and better regulate the health care industry. Nevertheless, transparency is not a cure-all for the problems facing the modern health care system. The authors of this volume present a nuanced view of transparency, exploring ways in which transparency has succeeded and ways in which transparency initiatives have room for improvement. Working at the intersection of law, medicine, ethics, and business, the book goes beyond the buzzwords to the heart of transparency's transformative potential, while interrogating its obstacles and downsides. It should be read by anyone looking for a better understanding of transparency in the health care context.