Drained Swamps and Quackery: Some Thoughts on Efficacy

“What makes drug development long and expensive is the need to prove, beyond statistical doubt, that your damn drug works”

Michael Gilman, Biotech Entrepreneur

2017 is going to be terrific. Tremendous, even. Things are going to change, big league.

7770160314_61e7536762_kThe new President has promised fantastic reforms to the drug industry. He’s going to get the big players in the pharmaceutical industry around a table and negotiate huge price reductions. Of course, he’s not going to touch their bottom line. If anything, he’s going to improve it. Innovation is being choked by over-regulation and he’s going remove burdensome FDA hurdles. But he has Executive Orders to give and walls to build, so he’s drafting in the very best people to help. We’re still waiting for those people to be officially named. Meanwhile, the media have had a month and a half of fun and speculation. The volume and variety of names being thrown around make it feel like a food fight at a Chinese buffet. One of those names is Peter Thiel.

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Bill of Health Blog Symposium: How Patients Are Creating the Future of Medicine

Bill of Health Blog Symposium: How Patients Are Creating the Future of Medicine

We are pleased to host this symposium featuring commentary from participants in the University of Minnesota’s Consortium on Law and Values in Health, Environment & the Life Sciences event, “How Patients Are Creating Medicine’s Future: From Citizen Science to Precision Medicine.”  Below, Susan M. Wolf tees up the issues.  All posts in the series will be available here.

How Patients Are Creating the Future of Medicine: Roundtable at University of Minnesota

By Susan M. Wolf, JD (Chair, Consortium on Law and Values in Health, Environment & the Life Sciences; McKnight Presidential Professor of Law, Medicine & Public Policy; Faegre Baker Daniels Professor of Law; Professor of Medicine, University of Minnesota)

Citizen science, the use of mobile phones and other wearables in research, patient-created medical inventions, and the major role of participant-patients in the “All of Us” Precision Medicine Initiative are just a few of the indicators that a major shift in biomedical research and innovation is under way. Increasingly, patients, families, and the public are in the driver’s seat, setting research priorities and the terms on which their data and biospecimens can be used. Pioneers such as Sharon Terry at Genetic Alliance and Matthew Might at NGLY1.org have been forging a pathway to genuine partnership linking patients and researchers. But the legal and ethical questions remain daunting. How should this research be overseen? Should the same rules apply as in more conventional, academically driven research? What limits should apply to parental use of unvalidated treatments on children affected by severe, rare disease? And should online patient communities be able to set their own rules for research?

In December 2016, the University of Minnesota’s Consortium on Law and Values in Health, Environment & the Life Sciences convened four thinkers with diverse academic and professional backgrounds to analyze these trends. This event, “How Patients Are Creating Medicine’s Future: From Citizen Science to Precision Medicine” was part of the Consortium’s Deinard Memorial Lecture Series on Law & Medicine, co-sponsored by the University’s Center for Bioethics and Joint Degree Program in Law, Science & Technology, with support from the Deinard family and law firm of Stinson Leonard Street. To see a video of the event, visit http://z.umn.edu/patientledvideo.

The four speakers offered diverse and provocative perspectives, each of which is highlighted in this series.

Citizen-Led Bioethics for the Age of Citizen Science: CRexit, BioEXIT, and Popular Bioethics Uprisings

By Barbara J. Evans, MS, PhD, JD, LLM (Alumnae College Professor of Law; Director, Center on Biotechnology & Law, University of Houston)

This post is part of a series on how patients are creating the future of medicine.  The introduction to the series is available here, and all posts in the series are available here.

The citizen science movement goes beyond merely letting people dabble in science projects. It involves giving regular people a voice in how science should be done. And citizen science calls for a new, citizen-led bioethics.

Twentieth-century bioethics was a top-down affair. Ethics experts and regulators set privacy and ethical standards to protect research subjects, who were portrayed as autonomous but too vulnerable and disorganized to protect themselves. The Common Rule’s informed consent right is basically an exit right: people can walk away from research if they dislike the study objectives or are uncomfortable with the privacy protections experts think are good for them. An exit right is not the same thing as having a voice with which to negotiate the purposes, terms, and conditions of research.

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The Wearables Revolution: Personal Health Information as the Key to Precision Medicine

By Ernesto Ramirez, PhD (Director of Research & Development, Fitabase)

This post is part of a series on how patients are creating the future of medicine.  The introduction to the series is available here, and all posts in the series are available here.

Personal health data has historically been controlled by the healthcare industry. However, much has changed in the last decade. From wearable devices for tracking physical activity, to services that decode the personal microbiome, there has been an explosion of methods to collect and understand our personal health and health behavior. This explosion has created a new type of data that has the potential to transform our understanding of the deep interactions of health behaviors, exposure, and outcomes — data that is large-scale, longitudinal, real-time, and portable.

New devices, applications, and services are creating large amounts of data by providing methods for collecting information repeatedly over long periods of time. For example, I have tracked over 20 million steps since 2011 using a Fitbit activity tracker. Many of the new tools of personal health data are also connected to the Internet through Bluetooth communication with smartphones and tablets. This connectivity, while commonly used to update databases as devices sync, also provides an opportunity to view data about ourselves in real-time. Lastly, there is an increasing interest in making this data accessible through the use of application programming interfaces (APIs) that allow third parties to access and analyze data as is becomes available. Already we are seeing unique and useful tools being developed to bring consumer personal health data to bear in clinical settings, health research studies, and health improvement tools and services.

The availability of this type of personal health data is having a big impact. The examples provided by the #WeAreNotWaiting and #OpenAPS communities showcase the groundbreaking potential of portable, usable, personal data. It is transforming the quality of life for individuals living with type 1 diabetes. Through access to data from continuous glucose monitors and wireless control of insulin pumps, over 100 individuals have implemented their own version of an artificial pancreas. These pioneering individuals are at the forefront of a revolution using personal health data to take charge of care and customize treatment decisions.

Personal health data will play a major role in the future of precision medicine, healthcare, and health research. Sensors will continue to improve. New data streams will become available. More analytical tools will surface. There will be more support for portable and sharable data. The availability of large-scale, longitudinal, and real-time personal health data will improve not only the ability of individuals to understand their own health, but when pooled, may produce new insights about what works, for what people, under what conditions.

Patient-Driven Medical Innovations: Building a Precision Medicine Supply Chain for All

Kingshuk K. Sinha, PhD (Department Chair and Mosaic Company-Jim Prokopanko Professor of Corporate Responsibility Supply Chain and Operations Department, Carlson School of Management, University of Minnesota)

This post is part of a series on how patients are creating the future of medicine.  The introduction to the series is available here, and all posts in the series are available here.

While the promise and potential of precision medicine are clear, delivering on that promise and making precision medicine accessible to all patients will require clinical adoption and a reliable and responsible supply chain. We already know this is a big problem in pharmacogenomics technology; the science is advancing rapidly, but clinical adoption is lagging. While Big Data can be a powerful tool for health care – whether it be an individual’s whole genome or an online aggregation of information from many patients with a particular disease – building implementation pathways to analyze and use the data to support clinical decision making is crucial. All of the data in the world doesn’t mean much if we can’t ensure that the development of precision medicine is linked with the efficient, safe, and equitable delivery of precision medicine.

Effective implementation means addressing the stark realities of health disparities. Leveraging citizen science to develop and deliver precision medicine has the potential to reduce those disparities. Citizen science complements more traditional investigator-driven scientific research and engages amateur and non-professional scientists, including patients, patients’ families, and communities across socio-economic strata as well as country boundaries.

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ACA Repeal and the End of Heroic Medicine

Last week, I saw Dr Atul Gawande speak at Health Action 2017. Healthcare advocates and activists sat around scribbling notes and clutching at their choice of whole-food, cold-pressed, green and caffeinated morning lifelines. Gawande speaks softly, lyrically and firmly; the perfect bedside manner for healthcare advocates in these early days of the Trump presidency. He calmly announced to the congregation that the age of heroic medicine is over. Fortunately, he continued, that’s a good thing.

Gawande’s remarks echoed a piece he published in the New Yorker. He writes that for thousands of years, humans fought injury, disease and death much like the ant fights the boot. Cures were a heady mixture of quackery, tradition and hope. Survival was largely determined by luck. Medical “emergencies” did not exist; only medical “catastrophes”. However, during the last century, antibiotics and vaccines routed infection, polio and measles. X-rays, MRIs and sophisticated lab tests gave doctors a new depth of understanding. New surgical methods and practices put doctors in a cage match with Death and increasingly, doctors came out with bloody knuckles and a title belt. Gradually, doctors became heroes and miracles became the expectation and the norm. This changed the way we view healthcare. Gawande writes, “it was like discovering that water could put out fire. We built our health-care system, accordingly, to deploy firefighters.”

But the age of heroic medicine is over. Dramatic, emergency interventions are still an important part of the system. However, Gawande insists that the heavy emphasis on flashy, heroic work is misplaced. Much more important is “incremental medicine” and the role of the overworked and underappreciated primary care physician.

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Artificial Intelligence and Medical Liability (Part II)

Recently, I wrote about the rise of artificial intelligence in medical decision-making and its potential impacts on medical malpractice. I posited that, by decreasing the degree of discretion physicians exercise in diagnosis and treatment, medical algorithms could reduce the viability of negligence claims against health care providers.

It’s easy to see why artificial intelligence could impact the ways in which medical malpractice traditionally applies to physician decision-making, but it’s unclear who should be responsible when a patient is hurt by a medical decision made with an algorithm. Should the companies that create these algorithms be liable? They did, after all, produce the product that led to the patient’s injury. While intuitively appealing, traditional means of holding companies liable for their products may not fit the medical algorithm context very well.

Traditional products liability doctrine applies strict liability to most consumer products. If a can of soda explodes and injures someone, the company that produced it is liable, even if it didn’t do anything wrong in the manufacturing or distribution processes. Strict liability works well for most consumer products, but would likely prove too burdensome for medical algorithms. This is because medical algorithms are inherently imperfect. No matter how good the algorithm is — or how much better it is than a human physician — it will occasionally be wrong. Even the best algorithms will give rise to potentially substantial liability some percentage of the time under a strict liability regime.

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Artificial Intelligence, Medical Malpractice, and the End of Defensive Medicine

Artificial intelligence and machine-learning algorithms are the centerpieces of many exciting technologies currently in development. From self-driving Teslas to in-home assistants such as Amazon’s Alexa or Google Home, AI is swiftly becoming the hot new focus of the tech industry. Even those outside Silicon Valley have taken notice — Harvard’s Berkman Klein Center and the MIT Media Lab are collaborating on a $27 million fund to ensure that AI develops in an ethical, socially responsible way. One area in which machine learning and artificial intelligence are poised to make a substantial impact is health care diagnosis and decision-making. As Nicholson Price notes in his piece Black Box Medicine, Medicine “already does and increasingly will use the combination of large-scale high-quality datasets with sophisticated predictive algorithms to identify and use implicit, complex connections between multiple patient characteristics.” These connections will allow doctors to increase the precision and accuracy of their diagnoses and decisions, identifying and treating illnesses better than ever before.

As it improves, the introduction of AI to medical diagnosis and decision-making has the potential to greatly reduce the number of medical errors and misdiagnoses — and allow diagnosis based on physiological relationships we don’t even know exist. As Price notes, “a large, rich dataset and machine learning techniques enable many predictions based on complex connections between patient characteristics and expected treatment results without explicitly identifying or understanding those connections.” However, by shifting pieces of the decision-making process to an algorithm, increased reliance on artificial intelligence and machine learning could complicate potential malpractice claims when doctors pursue improper treatment as the result of an algorithm error. In it’s simplest form, the medical malpractice regime in the United States is a professional tort system that holds physicians liable when the care they provide to patients deviates from accepted standards so much as to constitute negligence or recklessness. The system has evolved around the conception of the physician as the trusted expert, and presumes for the most part that the diagnosing or treating physician is entirely responsible for her decisions — and thus responsible if the care provided is negligent or reckless. Continue reading

New Book – Electronic Health Records and Medical Big Data: Law and Policy

Guest Post by author Sharona Hoffman

hoffman-cover-1-002I am pleased to post that my new book, “Electronic Health Records and Medical Big Data: Law and Policy” was recently published by Cambridge University Press.  The book enables readers gain an in-depth understanding of electronic health record (EHR) systems, medical big data, and the regulations that govern them.  It is useful both as a primer for students and as a resource for knowledgeable professionals.

The transition from paper medical records to electronic health record (EHR) systems has had a dramatic impact on clinical care.  In addition, EHR systems enable the creation of “medical big data,” that is, very large electronic data resources that can be put to secondary, non-clinical uses, such as medical research, public health initiatives, quality improvement efforts, and other health-related endeavors.  This book provides thorough, interdisciplinary analysis of EHR systems and medical big data, offering a multitude of technical and legal insights. Continue reading

Driven to Abstraction: The Implications of McRO for Diagnostic Patents

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Last month, the Court of Appeals for the Federal Circuit (“CAFC”) handed down their decision on the case of McRO, Inc. v. Bandai Namco Games Am. Inc (Fed. Cir. Sep. 13, 2016) (“McRO”). Commentators have already hailed the decision as providing significant clarity and guidance on subject-matter eligibility for patents under 35 U.S.C. §101 (“§101”) and on pre-emption. It has been lauded by Erich Andersen of Microsoft for providing key guidance for software developers. Others have remarked on the implications for those seeking patents on methods of medical diagnosis. Though not binding on the Supreme Court (and by no means a guarantee of the direction that Court might eventually take), I believe inventors in the medical arena can draw critical guidance on drafting patent claims from McRO. The decision might also signal a shift in attitude in the CAFC, towards a much more welcoming view of diagnostic patents.

In this post, I’ll briefly address the facts and decision in McRO. During that discussion, I believe a discussion of the facts and decision of last year’s CAFC case of Ariosa Diagnostics, Inc. v. Sequenom, Inc. 788 F.3d 1377 (Fed Cir. 2015) (“Sequenom”) will be illustrative. I’ll then briefly compare the two and discuss what the implications might be for biomedical patents moving forward.

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Making Big Data Inclusive

Guest post by Sarah Elizabeth Malanga, Fellow, Regulatory Science Program, James E. Rogers College of Law, University of Arizona, based on her presentation at the Petrie-Flom Center’s 2016 Annual Conference, “Big Data, Health Law, and Bioethics,” held on May 6, 2016, at Harvard Law School.

Cross-posted from the Hastings Center’s Bioethics Forum.

Big Data, which is derived from a multitude of sources including, social media, “wearables,” electronic health records, and health insurances claims, is increasingly being used in health care and it can potentially improve the way medical professionals diagnose and treat illnesses.

But what happens when Big Data only captures a snapshot of the population, rather than an overall picture of the population as a whole? The sources that generate Big Data – the Internet and credit card use, electronic health records, health insurance claims – are not utilized by everyone. Certain demographics may be missing from or underrepresented in Big Data because they do not own smartphones, have access to the Internet, or visit doctors on a regular basis because they lack health insurance. These sectors of the population disproportionately include low-income individuals, minority groups such as blacks and Hispanics, and the elderly. Continue reading

Use of Estimated Data Should Require Informed Consent

Guest post by Donna M. Gitter, Zichlin School of Business, Baruch College, based on Professor Gitter’s presentation at the Petrie-Flom Center’s 2016 Annual Conference, “Big Data, Health Law, and Bioethics,” held May 6, 2016, at Harvard Law School.

Cross-posted from the Hastings Center’s Bioethics Forum.

The Icelandic biotech firm deCODE Genetics has pioneered a means of determining an individual’s susceptibility to various medical conditions with 99 percent accuracy by gathering information about that person’s relatives, including their medical and genealogical records. Of course, inferences have long been made about a person’s health by observing and gathering information about her relatives. What is unique about deCODE’s approach in Iceland is that the company uses the detailed genealogical records available in that country in order to estimate genotypes of close relatives of individuals who volunteered to participate in research, and extrapolates this information in order to make inferences about hundreds of thousands of living and deceased Icelanders who have not consented to participate in deCODE’s studies. DeCODE’s technique is particularly effective in Iceland, a small island nation that, due to its largely consanguineous population and detailed genealogical records, lends itself particularly well to genetic research.

While Iceland’s detailed genealogical records enable the widespread use of estimated data in Iceland, a large enough U.S. database could be used to make similar inferences about individuals here. While the U.S. lacks a national database similar to Iceland’s, private companies such as 23andme and Ancestry.com have created rough gene maps of several million people, and the National Institutes of Health plans to spend millions of dollars in the coming years sequencing full genome data on tens of thousands of people. These databases could allow the development of estimated data on countless U.S. citizens.

DeCODE plans to use its estimated data for an even bolder new study in Iceland. Having imputed the genotypes of close relatives of volunteers whose DNA had been fully catalogued, deCODE intends to collaborate with Iceland’s National Hospital to link these relatives, without their informed consent, to some of their hospital records, such a surgery codes and prescriptions. When the Icelandic Data Protection Authority (DPA) nixed deCODE’s initial plan, deCODE agreed that it will generate for only a brief period a genetic imputation for those who have not consented, and then delete that imputation from the database. The only accessible data would be statistical results, which would not be traceable to individuals.

Are the individuals from whom estimated data is gathered entitled to informed consent, given that their data will be used for research, even if the data is putatively unidentifiable? In the U.S., consideration of this question must take into account not only the need for privacy enshrined in the federal law of informed consent, but also the right of autonomy, which empowers individuals to decline to participate in research. Although estimated DNA sequences, unlike directly measured sequences, are not very accurate at the individual level, but rather at the group level, individuals may nevertheless object to research participation for moral, ethical, and other reasons. A competing principle, however, is beneficence, and any impediment to deCODE using its estimated data can represent a lost opportunity for the complex disease genetics community.

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Legal Dimensions of Big Data in the Health and Life Sciences

Please find below my welcome speech at last-weeks mini-symposium on “Legal dimensions of Big Data in the Health and Life Sciences From Intellectual Property Rights and Global Pandemics to Privacy and Ethics at the University of Copenhagen (UCPH).  The event was organized by our Global Genes –Local Concerns project, with support from the UCPH Excellence Programme for Interdisciplinary Research.

The symposium, which was inspired by the wonderful recent  PFC & Berkman Center Big Data conference,  featured enlightening speeches by former PFC fellows Nicholson Price on incentives for the development of black box personalized medicine and Jeff Skopek on privacy issues. In addition we were lucky to have Peter Yu speaking on “Big Data, Intellectual Property and Global Pandemics” and Michael J. Madison on Big Data and Commons Challenges”. The presentations and recordings of the session will soon be made available on our Center’s webpage.

Thanks everybody for your dedication, inspiration, great presentations and an exciting panel discussion.

“Legal Dimensions of Big Data in the Health and Life Sciences – From Intellectual Property Rights and Global Pandemics to Privacy and Ethics”

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TWIHL Special: Wendy Mariner Analyzes the New Wellness Regulations

By Nicolas Terry and Frank Pasquale

twihl 5x5A special TWIHL episode with analysis of the new EEOC regulations under the ADA and GINA on Employer Wellness Plans. Nic is joined by Professor Wendy Mariner. Professor Mariner is the Edward R. Utley Professor of Health Law at Boston University School of Public Health, Professor of Law at Boston University School of Law, Professor at Boston University School of Medicine, and Co-Director of the J.D.-M.P.H. joint degree program, and a member of the faculty of the Center for Health Law, Ethics and Human Rights at BUSPH. Professor Mariner’s research focuses on laws governing health risks, including social and personal responsibility for risk creation, health insurance systems, implementation of the Affordable Care Act, ERISA, health information privacy, and population health policy.

Our discussion concentrated on the ADA regulation and examined how the agency responded to comments (including ours), the concept of voluntariness, the status of EEOC v. Flambeau, Inc., data protection (including issues raised when  employers research the health of their employees), and the policy flaws in the wellness space.The Week in Health Law Podcast from Frank Pasquale and Nicolas Terry is a commuting-length discussion about some of the more thorny issues in Health Law & Policy.

Subscribe at iTunes, listen at Stitcher RadioTunein and Podbean, or search for The Week in Health Law in your favorite podcast app. Show notes and more are at TWIHL.com. If you have comments, an idea for a show or a topic to discuss you can find us on twitter @nicolasterry @FrankPasquale @WeekInHealthLaw

Amicus brief in Sequenom v. Ariosa: Why the U.S. Supreme Court should grant the petition for a writ of certiorari

I am happy to announce that on April 20th the New York attorney Robert M. Schwartz and I have filed an amicus brief at the US Supreme Court with Berkeley-based Andrew J. Dhuey as Counsel of Record. The brief, which was signed by 10 prominent  European and Australian Law Professors as amici curiae, adds a European perspective to the many amicus briefs that have been submitted in support of Sequenom’s petition for certiorari to the United States Supreme Court. Sequenom’s petition in Case No. 15-1182 was filed on March 21, 2016 and seeks review of the Federal Circuit’s controversial decision in Ariosa Diagnostics, Inc. v. Sequenom, Inc., 788 F.3d 1371, reh’g denied, 809 F.3d 1282 (Fed. Cir. 2015). The case concerns the revocation of Sequenom’s patent claims directed to inventive methods of genetic testing by detecting and amplifying paternally inherited fetal cell-free DNA (cffDNA) from maternal blood and plasma. Before the development of this highly beneficial, non-invasive prenatal diagnostic test, patients were placed at higher risk and maternal plasma was routinely discarded as waste. Distinguishing this case from previous Supreme Court decisions and highlighting the mitigating effects of other patentability requirements, we are concerned that the Federal Circuit’s overly rigid approach to claims eligibility decision might jeopardize the development of new therapies in an increasingly important area of modern medicine.

As most Bill of Health readers know, the US Supreme Court has in a recent series of cases (i.e. the combined effect of Bilski, Prometheus, Myriad and Alice) barred the patent eligibility for many genetic inventions as “products and processes of nature”. In Sequenom the CAFC interpreted these to mean – in essence- that “laws of nature” had to be entirely eliminated from the test of patent eligibility under §101 of the Patent laws. Should this interpretation be institutionalized it will contravene the tests for exclusions and exceptions under the EPC, arguably contradict longstanding US treaty policy and disrupt international patent harmonization. More importantly, we fear that the broader impact of such an restrictive interpretation may have grave consequences for a sustainable global drug delivery system, which should involve both public and private actors.

Although we believe that patents will remain the backbone of the industry, we acknowledge in our brief that  there are certain areas of biomedical innovations, such as antibiotics and orphan drugs, where the patent system does not work particularly well. We further recognize that both in Europe and in the US concerns have been raised about overly pre-emptive patents scope, but these are addressed at different levels. In contrast to Europe, the CAFC has interpreted the uncodified exception as part of a “threshold test” for patent-eligibility applied before other patentability requirements can be assessed. A strict and coherent application of these requirements, however, would invalidate overly-broad patent claims (including some of Sequenom’s arguably too broad and badly drafted claims), while also permitting, well-defined, narrower claims on diagnostic technology. In our view, the current approach conflates the patent eligibility test with issues that can be more sensibly addressed within a strict and coherent assessment of novelty, non-obviousness and sufficient disclosure criteria or at the post-grant level. We believe that, the Federal Circuit’s threshold test has not sufficiently considered the manner in which today’s statutory requirements have developed in both the U.S. and Europe to address policy rationales for patentability exceptions. To entirely transplant those issues into the patent eligibility assessment would categorically close the patentability door on many well-defined and beneficial inventions that deserve patent protection. In absence of sufficient public involvement and appropriate alternative incentives we risk that the wells driving technological progress run dry and that companies engage in business strategies, such as increased reliance on trade secrecy, that are not necessarily beneficial for our innovation system.

Accordingly, we urge the Supreme Court to clarify a patent eligibility test in line with its longstanding jurisprudence and in harmony with international and European law.

If the CAFC’s restrictive interpretation should prevail, however, I believe that it will be crucial to swiftly optimize the framework for PPPs and alternative innovation incentives, such as prizes and regulatory exclusivities. This would have to be done on an international level to allow for greater flexibilities and encompass further technological areas, such as biomedical diagnostics. Regarding regulatory exclusivities, Article 39 of the TRIPS agreement should provide sufficient leeway for such changes. The pros and cons of the different alternative approaches would of course have to be carefully considered.

The Amici curiae have no stake in the parties or in the outcome of the case. A full list of the Amici is appended at the end of the brief.

 

CPC+: Opportunities and Challenges for Primary Care Transformation

In recent days there has been a lot of action around CMS’ Comprehensive Primary Care Initiative (CPCI). First, the next phase of the program was announced, expanding the program in size and scope. Several days later, an evaluation of the first two years of the initiative was published in the New England Journal of Medicine.

The original CPCI demonstration began in October 2012 and included 502 practices in seven regions (states or smaller areas within states). The regions were determined largely by payer interest, as commercial and state health insurance plans are essential partners in this multi-payer model. The CPCI involves risk-stratified care management fees for participating practices and the possibility of sharing in net savings to Medicare (if any). In turn, the practices must invest in practice redesign around: access and continuity, chronic disease management, risk-stratified care management, patient and caregiver engagement, and care coordination across a patient’s providers, e.g., managing care transitions and ensuring close communication and collaboration.

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Minnesota: Leading The Way In Patient Safety

By John Tingle

The UK Government and the Department of Health are taking patient safety very seriously and, since the publication of ‘An organisation with a memory’ in 2000, the UK has like the USA been a world leader in the field of patient safety policies, practices and developments.

In the UK we have a very sophisticated patient NHS (National Health Service) patient safety infrastructure and system along with a NHS Adverse incident reporting system, the NRLS (National Reporting and Learning System). Despite having such a ‘Rolls Royce’, well-established patient safety infrastructure and system, terrible patient safety incidents such as that which happened in Mid Staffordshire a few years ago seem to plague the NHS. Patients died because of poor care and, according to the report, “[t]he Inquiry identifies a story of terrible and unnecessary suffering of hundreds of people who were failed by a system which ignored the warning signs of poor care and put corporate self-interest and cost control ahead of patients and their safety.”Our patient system missed the terrible care failings identified in this inquiry report. We are working hard on improving the system and my posts will provide regular updates on what is happening in the UK, Europe and beyond in patient safety.

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Should healthcare systems implement routine recontacting services in clinical practice? Some legal and logistical considerations

By Daniele Carrieri, Angus Clarke, Anneke Lucassen, Susan Kelly

Advances in genetic and genomic medicine are resulting in better diagnosis and treatment of some health conditions, and the question of whether former patients should be recontacted is therefore timely. Recontacting patients to inform them of new information or new testing, that could be relevant to their health or that of their biological relatives is made more pressing by the increasing use of whole genome approaches in healthcare, where variants previously of unknown significance (VUSs) may now have known disease effects.  However, there is currently no consensus about whether or not healthcare professionals have a duty or responsibility to recontact former patients in light of this new information. There is also very little empirical evidence in this area. In a recent article published in Genetics in Medicine, we present the results of a survey of recontacting practices of clinical genetics services across the United Kingdom (UK). As far as we know, this is the first study that specifically explores current recontacting practices in clinical genetic services.

One of the questions of the survey asked was whether clinical genetics services should implement routine recontacting systems. The majority of genetic services were undecided for several reasons.  The main arguments given in favor of implementing such systems revolved around patient choice and the idea of keeping patients up to date.  The main arguments against pointed to the logistical difficulties of implementing recontacting systems and the possible legal implications of doing so, if that were seen as establishing a new standard of care without the additional resources required for this to be a sustainable activity. Continue reading

UDI Adoption: A Necessary Step Towards Better Care for Patients with Implanted Devices

By Dalia Deak

In the United States, though many millions of individuals live with implanted devices, it may shock you to know that it is easier to recall tainted dog food than it is to recall a faulty pacemaker. This is due in large part to the lag of the medical device world behind most other industries in the implementation of a standardized system that can uniquely identify and track medical devices as they move through the supply chain to a patient. Such an identification system has existed for most products since stores implemented the UPC and Congress mandated that drugs be labeled with the National Drug Code, both of which were introduced in the early 1970s.

To remedy this lag, Congress, in FDAAA of 2007, tasked the FDA with the creation of a unique device identification (UDI) system. In 2013, FDA published a Final Rule regarding manufacturer labeling of UDIs, to be rolled out by class in the coming years. While the establishment of such a system would certainly constitute an important step forward, another number on a label will do little to enhance patient safety on its own. Rather, the value of UDIs is in the uptake of the identifier at each point in a medical device’s life—from manufacturer to distributor to provider to patient to payer (see this report I co-authored on this very issue). Continue reading

Big Data, Genetics, and Re-Identification

by Zachary Shapiro

While all scientific research produces data, genomic analysis is somewhat unique in that it inherently produces vast quantities of data. Every human genome contains roughly 20,000-25,000 genes, so that even the most routine genomic sequencing or mapping will generate enormous amounts of data. Furthermore, next-generation sequencing techniques are being pioneered to allow researchers to quickly sequence genomes. These advances have resulted in both a dramatic reduction in the time needed to sequence a given genome, while also triggering a substantial reduction in cost. Along with novel methods of sequencing genomes, there have been improvements in storing and sharing genomic data, particularly using computer and internet based databases, giving rise to Big Data in the field of genetics.

While big data has proven useful for genomic research, there is a possibility that the aggregation of so much data could give rise to new ethical concerns. One concern is that promises of privacy made to individual participants might be undermined, if there exists a possibility of subject re-identification.

Re-identification of individual participants, from de-identified data contained in genetic databases, can occur when researchers apply unique algorithms that are able to cross-reference numerous data sets with the available genetic information. This can enable diligent researchers to re-identify specific individuals, even from data sets that are thought to be anonymized. Such re-identification represents a genuine threat to the privacy of the individual, as a researcher could learn about genetic risk factors for diseases, or other sensitive health and personal information, from combing through an individual’s genetic information.

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