By Paul C. McLean
While I was aghast earlier this week that the White House struggled over whether to fly the flag at half-mast or full for the death of John McCain, and relieved that it was still the American flag, I distracted myself from the drama in Washington with other news:
Item: In Europe, there were 5,000 cases of the measles in all of 2016, 24,000 in 2017, and already 41,000 halfway through 2018, including 37 deaths, according to the World Health Organization. Globally, measles remains a leading cause of death among young children even though a safe and cost-effective vaccine is available.
Item: In the bizarre case of a convicted murdered claiming his victim wouldn’t have died had he stayed on life support, the Georgia Supreme Court rejected that argument because the patient “was basically brain dead.” [PDF]
Item: Twenty-five years later, gene therapy finally got a common-sense definition: “the intentional, expected permanent, and specific alteration of the DNA sequence of the cellular genome, for a clinical purpose.”
Bioethicists, policymakers, and clinicians tend not to lump brain death, gene therapy and the anti-vaccine movement together. And why should they? Though fate management is central to each, they are perplexing enough to the public (i.e. me) when considered separately.
By Cansu Canca
A new worry has arisen in relation to machine learning: Will it be the end of science as we know it? The quick answer is, no, it will not. And here is why.
Let’s start by recapping what the problem seems to be. Using machine learning, we are increasingly more able to make better predictions than we can by using the tools of traditional scientific method, so to speak. However, these predictions do not come with causal explanation. In fact, the more complex the algorithms become—as we move deeper into deep neural networks—the better are the predictions and the worse are the explicability. And thus “if prediction is […] the primary goal of science” as some argue, then the pillar of scientific method—understanding of phenomena—becomes superfluous and machine learning seems to be a better tool for science than scientific method.
But is this really the case? This argument makes two assumptions: (1) The primary goal of science is prediction and once a system is able to make accurate predictions, the goal of science is achieved; and (2) machine learning conflicts with and replaces the scientific method. I argue that neither of these assumptions hold. The primary goal of science is more than just prediction—it certainly includes explanation of how things work. And moreover, machine learning in a way makes use of and complements the scientific method, not conflicts with it.
Here is an example to explain what I mean. Prediction through machine learning is used extensively in healthcare. Algorithms are developed to predict hospital readmissions at the time of discharge or to predict when a patient’s condition will take a turn for worse. This is fantastic because these are certainly valuable pieces of information and it has been immensely difficult to make accurate predictions in these areas. In that sense, machine learning methodology indeed surpasses the traditional scientific method in predicting these outcomes. However, this is neither the whole story nor the end of the story. Continue reading
By Stephen Wood
The patient was a very pleasant 45-year-old woman who came into the emergency department with fever, headache and neck pain; all signs and symptoms concerning for meningitis or possibly encephalitis. Both are often an infectious, sometimes inflammatory diseases of either the meninges, the thin membrane that covers the brain, or the brain itself. The diagnosis is considered clinically, based on signs and symptoms as well as some clinical exam, and often confirmed by a lumbar puncture or spinal tap.
I discussed this with the patient and she agreed to the procedure. I had her positioned and had opened the prepackaged kit to get started. The kit is wrapped in plastic, a necessity to keep equipment sterile, especially for a procedure that will involve instrumenting a space that communicates with the central nervous system; the brain and spinal cord.
Off came the plastic, and into the trash. There are also some stickers for labeling the syringes used to inject the anesthetic, but I didn’t need those either, so they also went into the trash. There are extra plastic syringes that you don’t need, as well as a plastic straw to draw up the anesthetic if you choose to use that instead of a needle. Into the trash. There are several more items in the kit that are destined for the trash as well: a small circular piece of foam for sticking used needles into, as well as unused needles. By the end of the procedure, I had become a one-man wrecking ball of plastic waste.
By Nicolas Terry
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The next four episodes were recorded at the 2018 SEALS conference. Four of us got together as a panel to discuss Healthcare in the Era of the Trump Administration. I was joined by:
- Nicole Huberfeld, Professor of Health Law, Ethics & Human Rights at the Boston University School of Public Health and Professor of Law at the School of Law there.
- Zack Buck, Associate Professor of Law and Wilkinson Junior Research Professor at The University of Tennessee, Knoxville.
- Jennifer Bard, Professor of Law in the College of Law at the University of Cincinnati with an appointment as Professor, Department of Internal Medicine at the College of Medicine.
BU is hiring in health law this year, hopefully a lateral with tenure. Anna di Robilant chairs the committee.
Any other law schools hiring in HL this year?
By Ameet Sarpatwari, Michael S. Sinha, and Aaron S. Kesselheim
Each month, members of the Program On Regulation, Therapeutics, And Law (PORTAL) review the peer-reviewed medical literature to identify interesting empirical studies, policy analyses, and editorials on health law and policy issues relevant to current or potential future work in the Division.
By Paul C. McLean
Gene editing is at once promising and perilous. Or, as John Oliver said in a recent episode of his news show, it is ”either going to kill all disease or kill every last one of us.”
The Nuffield Council on Bioethics is not as amusing as John Oliver, and unlike the summer film “Rampage,” its new gene editing report features neither The Rock nor a genetically modified, 30-foot wolf.
But if you want to understand what we may actually be getting ourselves into, England’s de facto national bioethics commission has produced a useful roadmap for educating the public and addressing concerns. It may the summer read you’ve been looking for.
And if there’s a gene splicer for envy, I’m ready to be CRISPR’d.
By Norman L. Cantor
The scourge of Alzheimer’s is daunting. For me, the specter of being mired in progressively degenerative dementia is an intolerably degrading prospect. One avoidance tactic — suicide while still competent — risks a premature demise while still enjoying a tolerable lifestyle.
The question arises whether an alternative tactic — an advance directive declining all life-sustaining intervention once a certain point of debilitation is reached — might be preferable as a device to avert a prolonged, unwanted limbo.
By John Tingle
Two key NHS (National Health Service) organisations have recently produced reports. NHS Resolution has produced its annual report and accounts.The Care Quality Commission (CQC) has produced a report on the experiences of adult in -patients in NHS hospitals.These reports are excellent for real-time trend analysis and important patient safety and clinical negligence trends are identified.
23andMe has partnered with GlaxoSmithKline, creating a flurry of questions around customer consent to how their data is used in research. (Phobo via imran/Flickr)
By Valerie Gutmann Koch
23andMe announced its $300 million partnership with GlaxoSmithKline late last month, a move that will allow the drug behemoth to develop drugs based on “deidentified” DNA and other information collected from the direct-to-consumer (DTC) genetic testing company’s five million customers.
Over the last decade, 23andMe has confronted – and survived – various challenges and existential threats to its existence. However, this announcement, while representing an incredible success for 23andMe’s business, presents potential obstacles for informed consent and the research enterprise.
It may also undermine public trust in the company.
The newest textbook in public health law comes from Scott Burris, Micah Berman, Matthew Penn and Tara Ramanathan Holiday. The New Public Health Law is an effort to equip students in law, public health, social work and other fields in the public health and social policy realms with the tools to fully exploit the potential of law to improve public health. It takes a transdisciplinary approach, breaking down complex legal processes into discrete and understandable stages, using examples from the field.
We asked authors Micah Berman and Scott Burris about the textbook’s new approach to teaching and learning public health law.