Population Health and an aging world

I first used the above photo in my recent post on "The Silver Tsunami." Then, in a subsequent post on "The Biden Cancer Initiative" I cited an article I ran across at STATnews.

More research on ‘dying healthy’ will also help us live healthier
By GEORGE J. ANNAS and SANDRO GALEA, OCTOBER 3, 2018

Helping people live longer has been a central goal of medicine for decades. The quest to extend life raises an interesting question: Should we keep investing in research aimed at adding even more years to the already impressive gains in the average life expectancy that occurred during the 20th century?

We can only go so far. There’s likely an unalterable biological limit to the human life span, somewhere around 115 years (though there are, of course, occasional outliers). Virtually all humans die before reaching that age, most of them before they turn 90.

This limit should give us pause…

Advances in medical treatment, including cancer treatments, are increasingly unlikely to provide further significant gains in human longevity. An analysis of 71 cancer drugs consecutively approved between 2001 and 2012, for example, suggests that their overall contribution to survival was just 2.1 months; the gains attributable to personalized cancer medicine have, so far, also been minimal.

Lacking evidence that the human life span can be radically increased by new medical technologies, we believe it’s time to shift our country’s investment priorities away from medical research that aims to extend life and instead focus on the same social, cultural, and political factors that successfully prolonged life in the last century.

That means more public investment in education, transportation, and housing. That kind of investment would directly contribute to the prevention of chronic diseases such as diabetes, heart disease, and many cancers, and would do more to improve the quality of life of the population than additional medical research aimed at treating individuals with specific diseases…

One way to preserve quality of life throughout the life span is to compress aging-related illness and disease into as short a time as possible.

Others before us have suggested that the U.S. is now at the point of diminishing returns in high-tech medicine. Unfortunately, calls to redirect resources away from research into extending life and toward quality of life have been ignored in the past, and the same will likely happen now. We believe that is a mistake…

I immediately tangentially thought of "A Good Death."

I looked into the authors of the foregoing STATnews piece, both faculty members of the Boston University School of Public Health.

Sandro Galea, MD is the author of this intriguing book:

Introduction
HEALTH MATTERS. A CONCERN with our health and well-being crosses national, partisan, and ideological divides. Our concern with health has led us to remarkable achievements that have made for a healthier world during the past century. Life expectancy worldwide is higher than it has ever been. In the past century alone, we have increased life expectancy by a mind-boggling 30 years after centuries during which life expectancy was more or less stagnant. We have dramatically reduced death from infectious disease, and large numbers of people worldwide have access to quality medical care when they need it. Yet, our health achievements leave much to be desired. Although life expectancy has increased overall, billions of people continue to die prematurely, and substantial healthy life years are lost worldwide due to disease or disability. Our collective health achievement is marred by tremendous gaps, with global life expectancy ranging from a high of 83 years in Japan to a low of 47 years in Malawi. The United States has worse health metrics than nearly all other high-income countries, even as the country spends far more on health than any other country worldwide. Population health in the United States is characterized by racial/ethnic and socioeconomic gaps, despite decades of study and effort to narrow these disparities. These successes, and failures, are all the remit of public health.

At heart, public health is concerned with the social, economic, cultural, and political conditions that shape the health of populations. The vast majority of health achievement during the past century is attributable to an improvement in these conditions: to better living conditions in cities, improved educational status for women and men, safer water and sanitation, availability of nutrient-rich food, stable housing and shelter, and reduction in violence and injury. Conversely, our shortcomings represent our failure to tackle the social divides—across countries and within countries—that become health divides. This is compounded by our mis-investment of resources in curative care and away from education, physical and social conditions of cities, social justice, and efforts at disease prevention that create the conditions for healthy populations…

1. The Aspirations and Strategies of Public Health 
DURING THE PAST century, public health has been responsible for an extraordinary number of achievements. Going forward, the field stands to make similar contributions to health in this century. Our rapidly changing world continually presents us with new challenges, including chronic diseases, increasing income disparities, the threat of bioterrorism, and climate change. In the face of these concerns, public health is well positioned to lead the way.

Yet, despite its record of achievement, organized public health appears to be on the defensive. High-profile initiatives such as the burgeoning precision medicine agenda and the continuing war on cancer have captured attention at the highest levels of politics, diverting resources into individualized efforts at disease prediction through genomic approaches, at the expense of population-based public health action geared toward the foundational drivers of health [2, 3]. Given that much public health scholarship arises from academic public health institutions that are heavily dependent on federal funding agencies, our national preference for cutting-edge technology and expensive treatment over less eye-catching prevention measures threatens to monopolize the direction of public health scholarship for decades to come. Public health is not alone in this financial uncertainty. We share funding and infrastructure deficiencies with transportation, education, and almost all other endeavors that are reliant on public funding and leadership. Investments in much of this infrastructure have been declining, or barely keeping pace with needs, for decades [4]‌. In this context, every extra dollar spent on medical care comes at a high opportunity cost, at the expense of public health [5].

The difficulties we face do not center on disagreements about the core goals of our field, which have always been, and remain, broad and aspirational. According to the American Public Health Association, “public health promotes and protects the health of people and the communities where they live, learn, work, and play” [6]‌. This statement captures public health’s goal of shaping the conditions that enable healthier populations, with a key emphasis on the prevention of disease…

Galea, Sandro (2017-06-20T23:58:59). Healthier: Fifty Thoughts on the Foundations of Population Health (Kindle Locations 184-258). Oxford University Press. Kindle Edition.

OK. More stuff to have to study up on. I have to confess I don't know much about the nuts and bolts of "public health" as an academic and/or professional domain. I spent my three tenures with the HealthInsight Medicare QIO first as a Nevada acute care hospitalization outcomes analyst (pdf), and then as an EHR implementation and workflow analyst (DOQ-IT, Meaningful Use REC) working the ambulatory primary care space (Family Med, Internal Med, Peds, OB/GYN). In that arena, mention "population health" to the harried docs on the enervating productivity treadmill would just get you eye-rolling, grumpy, dismissive responses -- "If we each provide the best care for our patients, 'population health' will take care of itself."

Not that simple, by a long shot. But, then, none of us in the trenches had time for debating abstract macro policy issues.

"Yet, despite its record of achievement, organized public health appears to be on the defensive."

In particular given the priorities of the Trump administration. And then there are the competing economic priorities and chronic misalignments revealed in Rosenthal's excellent book "An American Sickness." 

An Aside: where might "Data Science" fit in to this? And, broadly, the "Upstream"? In that regard, "Your ZIP code matters more than your genetic code."

And, let us not forget the "exposome."

Take a Deep Breath and Say Hi to Your Exposome
Researchers begin to explore the unique cloud of airborne microbes and chemicals that surrounds each of us

In the past few decades, researchers have opened up the extraordinary world of microbes living on and within the human body, linking their influence to everything from rheumatoid arthritis to healthy brain function. Yet we know comparatively little about the rich broth of microbes and chemicals in the air around us, even though we inhale them with every breath.

This struck Stanford University genomics researcher Michael Snyder as a major knowledge gap, as he pursued long-term research that involved using biological markers to understand and predict the development of disease in human test subjects. “The one thing that was missing was their exposure” to microbes and chemicals in the air, Snyder says. “Human health is clearly dependent not just on the genome or the microbiome, but on the environment. And sampling the environment was the big hole.”…

 Add one more discipline to the "Omics." 

ALSO OF INTEREST AT BU-SPH

Roaming around their website led me to this:

Health Law, Ethics & Human Rights Research

The Affordable Care Act
Constitutionality, implementation strategies, Medicaid expansion, role of private health insurance companies, coverage of public health screening, and patient-oriented research.
 
Clinical Bioethics
Analysis of clinical case consultations performed at Boston Medical Center dealing with end-of-life care, reproductive health, patient capacity to participate in decision-making, and resource allocation.

Genetics & Genomics   
Genetic screening and counseling strategies, including fetuses, newborns, children, and adults. Introduction of whole genome screening into the clinical setting. Role of government mandates and informed consent. Genetic privacy, genetic transfer experiments, and regulation of synthetic biology.

Health Promotion
Legal and ethical issues in health promotion programs among employers, health care payers, government, and communities as well as the constitutionality of state and federal laws designed to change health behaviors (e.g., cigarette labeling laws, container size limits for sugary drinks, etc.)

Health & Human Rights
Development of a theory linking health to respect for human rights, including the meaning of the international “right to health.”

Patient Rights & Patient Safety
Defining the legal rights of patients, including the “right to safety” and the role of evidence-based medicine in setting the standard of care.

Medicine & the Holocaust
Study of the role of medicine during the Holocaust, focusing on racial hygiene, eugenics, euthanasia, and genocide. Care of Holocaust survivors, research on perpetrators and bystanders.

Military Medical Ethics
Study of existing military doctrine, application of civilian medical ethics to the military; special emphasis on ethics standards at Guantanamo, including hunger strike protocols, and the concepts of “dual loyalty” and “dual use.”

Reproductive Rights
Constitutionality of new state laws that restrict abortion services.

Research on Human Subjects
Study of the changes needed in federal research regulations and methods to improve subject understanding of research and improve the consent process and its documentation.

Religion & Public Health
The role of religion in public health policy and the First Amendment limits on governmental interference with religion and religious practices.

Emergency Preparedness
An examination of how public health should work with national security agencies, including the relationship between epidemics and bioterrorist attacks.

Medical Privacy
Privacy of medical and genomic records, quality assurance studies, and electronic health records, as well as the access the government has to private health information.

Legal & Ethical Implications of Wellness Programs
An analysis of the reciprocal interactions between corporate wellness programs and the laws governing health insurance and employment.

Forensic Medicine
Forensic evaluations of refugees and asylum seekers, as well as victims of abuse and torture. Setting standards for same.

Wow. Makes me want to move to Boston and apply.

My interest in these areas has been abiding ever since grad school [pdf] in the 1990's ("Ethics and Policy Studies"). apropos, see my prior post on "Information Ethics."

Oh, and I've alluded to this a couple of times:

I reached out to these folks, and gently pointed out that their "Ethical Framework" pdf download document had no definition of "ethics." The email reply I got blew me off -- "we all know what we mean, we're not gonna get bogged down in abstract academic jargon."

Right. In Silicon Valley-speak, just "Don't Be Evil" while you "Fail Fast and Break Stuff" in your Agile Scrums.

Dudes, I'm not talkin' obtuse ivory tower "Dialectical Hermeneutics,"or hypothetical "gotcha" moral dilemma "Trolley Problems," etc, just a common-sense primer of sufficient detail. e.g., from a book I got onto via Science Based Medicine:

Ethical Frameworks and Principles
Ethical considerations of any problem or issue can be divided into two major categories: (a) nonconsequentialist and (b) consequentialist approaches. 1 Nonconsequentialism considers that the action (or even just the motivation behind an action) is the crucial ethical factor. In other words, the action itself is more important than the actual outcome (consequence) of the action. By contrast, consequentialism holds that outcomes (as opposed to actions) should be the crucial determinants of ethical decisions…

Principlism
The inherent subjectivity of ethics presents a problem: even when reflexive and uncritical responses (such as the ‘gut reactions’ of tabloid readers) are excluded, along with religious outlooks, medical ethicists still do not all agree on which ethical principles are best.

It was in response to this reality that an approach to ethical analysis known as principlism was developed. Principlism attempts to factor in both nonconsequentialist and consequentialist approaches. The standard version is based on four core principles:

(1) Respect for autonomy (a nonconsequentialist principle—but one that utilitarianism also supports).
(2) Nonmaleficence (‘first, do no harm’—a nonconsequentialist principle).
(3) Beneficence (increase overall utility—a consequentialist principle; it is essentially utilitarianism).
(4) Justice (fairly distribute benefits, risks and costs—a nonconsequentialist principle). 

Principlists apply this approach to an ethical case by examining how each of the four principles (in turn) applies to the issues raised by the case. It is quite common for medical ethics committees to use this method to reach decisions. Principlism can be very useful as a structured ‘checklist’ method to address ethical problems and therefore finds favour amongst laypeople or non-ethically trained professionals, who predominate on ethics committees…

Ernst, Edzard. More Harm than Good?: The Moral Maze of Complementary and Alternative Medicine (Kindle Locations 83-208). Springer International Publishing. Kindle Edition.

That entire chapter is excellent. One need not, however, even go to that much trouble. Any quick Google search will get you tons of relevant, succinct definitional information on the topic of Ethics.

Below, a good, accessible, inexpensive resource:

I still have all of my many grad school texts, but I keep this in my Kindle as a handy refresher.

It was emphasized to us in grad school early on that "Ethics" was not about some lookup cookbook of "right/wrong," but rather a frequently arduous process of rational moral deliberation comprising evidence (including accrued wisdoms), logic, and -- yes -- "values" fused in honest attempts to derive just decisions and policies.

UPDATE: ON HEALTH RESOURCE ALLOCATION

My latest issue of Science Magazine arrived today. This therein is relevant to the discussion in this post:

Cancer prevention: Molecular and epidemiologic consensus

Prevention of any disease can occur at two levels: (i) avoiding or reducing risk factors coupled with increases in protective factors (primary prevention, which is preferable when it can be practiced) and (ii) detection and intervention early in the course of disease evolution (secondary prevention). But despite substantial epidemiologic data showing that a large proportion of cancers and cancer deaths are preventable, decreases in cancer mortality rates in developed countries have lagged far behind decreases in mortality rates from heart disease (1), another major disease amenable to prevention (for example, 18 versus 68% decrease, respectively, between 1969 and 2013 in the United States) (2). We believe that one main factor explaining the relatively modest reduction in mortality is the limited support for cancer prevention research, which receives only 2 to 9% of global cancer research funding (3). As a United Nations (UN) High-Level Meeting begins this week to review efforts to combat noncommunicable diseases, a key question is how to prioritize resources to realize the potential of cancer prevention…

'eh?

CODA

Off-topic erratum: I drove today for the first time since my August 23rd SAVR aortic valve surgery. I start cardiac rehab PT next Tuesday. Doin' OK. Can definitely hear/feel that new valve thumpin'.
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More to come...

"Data Science?"

The latest fad? Last year it was profitably fashionable to add "crypto" and/or "blockchain" to one's resume or startup company name. I've alluded to the phrase "data science" in a number of prior posts, in the context of Health InfoTech. See, e.g., "Health IT: process mining and analytics for healthcare QI." 

(BTW: Blockchain update.)

This (below) is a pretty good illustrative graphic of the subtopical components:

I have direct work experience in a number of these areas, but not "machine learning" nor "large scale distributed computing" (and I have some methodological concerns about the latter, which I will get to). "BPM" is "Business Process Management." We called "process mining" "operations analytics."

The allusion to "databases," one assumes, includes the critical subject of "database architectures." The heterogeneity of widely distributed "big data" (often of materially varying quality pedigree) has to be a concern. In fairness, though, my waning programmer / database architect chops are pretty old-school RDBMS comprising in-house (e.g., local server) "structured data."

By "machine learning," I assume they include "artificial intelligence," "deep learning," and "natural language processing (NLP)."

I'm reading up.

Just getting started with these, stay tuned. Looking for clear, consistent definitions at the outset, for one thing.

From the MIT book:

1. What Is Data Science? 

Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting nonobvious and useful patterns from large data sets. Many of the elements of data science have been developed in related fields such as machine learning and data mining. In fact, the terms data science, machine learning, and data mining are often used interchangeably. The commonality across these disciplines is a focus on improving decision making through the analysis of data. However, although data science borrows from these other fields, it is broader in scope. Machine learning (ML) focuses on the design and evaluation of algorithms for extracting patterns from data. Data mining generally deals with the analysis of structured data and often implies an emphasis on commercial applications. Data science takes all of these considerations into account but also takes up other challenges, such as the capturing, cleaning, and transforming of unstructured social media and web data; the use of big-data technologies to store and process big, unstructured data sets; and questions related to data ethics and regulation...

Kelleher, John D.. Data Science (MIT Press Essential Knowledge series) . The MIT Press. Kindle Edition.

From the "AI Science" book:

What is Data Science?

Data science is multidisciplinary field that relies on scientific methods, statistics and algorithms to extract meaningful insights from data. At its core, data science is all about discovering useful patterns in data that can then be presented as information to tell a story or make informed decisions. It would be noticed that data science depends on techniques from a bunch of other fields such as computer science, mathematics, statistics and business analytics. It is common for data scientists to have skills across this range. Data science can be employed to derive insights from both small and large datasets and it is often a misconception that data science is only suited to so called big data.

Morgan, Peter. Data Science from Scratch with Python: Step-by-Step Guide (Kindle Locations 337-344). AI Sciences LLC. Kindle Edition.

OK. Their Venn diagram:

Another engrossing book that I'm way deep into at the moment, written by the AI eminence Judea Pearl.

This one is a total whack upside the head.

…We live in an era that presumes Big Data to be the solution to all our problems. Courses in “data science” are proliferating in our universities, and jobs for “data scientists” are lucrative in the companies that participate in the “data economy.” But I hope with this book to convince you that data are profoundly dumb. Data can tell you that the people who took a medicine recovered faster than those who did not take it, but they can’t tell you why. Maybe those who took the medicine did so because they could afford it and would have recovered just as fast without it.

Over and over again, in science and in business, we see situations where mere data aren’t enough. Most big-data enthusiasts, while somewhat aware of these limitations, continue the chase after data-centric intelligence, as if we were still in the Prohibition era.

As I mentioned earlier, things have changed dramatically in the past three decades. Nowadays, thanks to carefully crafted causal models, contemporary scientists can address problems that would have once been considered unsolvable or even beyond the pale of scientific inquiry. For example, only a hundred years ago, the question of whether cigarette smoking causes a health hazard would have been considered unscientific. The mere mention of the words “cause” or “effect” would create a storm of objections in any reputable statistical journal.

Even two decades ago, asking a statistician a question like “Was it the aspirin that stopped my headache?” would have been like asking if he believed in voodoo. To quote an esteemed colleague of mine, it would be “more of a cocktail conversation topic than a scientific inquiry.” But today, epidemiologists, social scientists, computer scientists, and at least some enlightened economists and statisticians pose such questions routinely and answer them with mathematical precision. To me, this change is nothing short of a revolution. I dare to call it the Causal Revolution, a scientific shakeup that embraces rather than denies our innate cognitive gift of understanding cause and effect.

Pearl, Judea. The Book of Why: The New Science of Cause and Effect (pp. 6-7). Basic Books. Kindle Edition.

"If I could sum up the message of this book in one pithy phrase, it would be that you are smarter than your data. Data do not understand causes and effects; humans do." [pg. 21]

So much for the liturgy of "Data-Driven."

Among numerous other virtues, The Book of Why provides the best explication of Bayesian Networks I've ever read. I'm already long up to speed on applications of Bayes Theorem ("base rates matter"), but Pearl's Bayesian Networks stuff is off the hook, and foundational to his compelling argument.

UPDATE

Michael Lewis' new book is out. I read it all immediately.

…in the space of a few years, the interest in data analysis went from curiosity to fad. The fetish for data overran everything from political campaigns to the management of baseball teams. Inside LinkedIn, DJ presided over an explosion of job titles that described similar tasks: analyst, business analyst, data analyst, research sci. The people in human resources complained to him that the company had too many data-related job titles. The company was about to go public, and they wanted to clean up the organization chart. To that end DJ sat down with his counterpart at Facebook, who was dealing with the same problem. What could they call all these data people? “Data scientist,” his Facebook friend suggested. “We weren’t trying to create a new field or anything, just trying to get HR off our backs,” said DJ. He replaced the job titles for some openings with “data scientist.” To his surprise, the number of applicants for the jobs skyrocketed. “Data scientists” were what people wanted to be.

Lewis, Michael. The Fifth Risk (pp. 157-158). W. W. Norton & Company. Kindle Edition.

A compelling, albeit by turns depressing and infuriating read. Highly recommended.
___

"DATA SCIENCE," STANFORD IS ON IT

sdsi.stanford.edu

I saw a presentation about this stuff given by Stanford's Carlos Bustamante last December during the Health 2.0 Technology for Precision Health conference.

From the SDSI website:

Science of Data Science

Science is experiencing simultaneous challenges and opportunities at an unprecedented rate:

• From new sources of data, especially in large quantity and unconventional structure, often from “non-scientific” sources, such as social media;
• From new algorithmic techniques potentially expanding greatly the ability to reason from data but whose interpretation, validity and fairness can not be established by our current statistical and computational techniques;
• From the crucial need for scientifically valid advice on questions of the greatest importance to the future of society, of life and of the earth itself---advice that must be effectively communicated to society.

In all of these, data science is clearly central. Recent computational, statistical and other research has been of great value. Much more needs to be done, however, and with a sense of urgency.

Validity of algorithmic inferences:
Algorithmic techniques to infer patterns and structure have had exceptional success recently in many areas of practical value. They can also be important, even revolutionary, for science in many areas. Data as divergent as social media interactions on one hand and satellite or drone images on the other may provide vital results through such algorithms.

However, the scientific validity of the results can not be assumed. Conventional concepts such as random sampling of the intended population are rarely relevant. A deeper understanding of the data sources and the computations applied will be essential.

Fairness of algorithmic decisions:
Beyond the scientific validity of inferences, the use of algorithmic results to recommend practical actions raises important questions of fairness and equitable treatment. Data science needs to search for valid notions of fairness, to ensure that the results of analysis and the data-based algorithms using them are fair to all demographic and other cohorts.

Privacy and the public interest:
Huge quantities of data exist for individuals, through social media, other internet activities and databases of medical, governmental, employment and commercial records. Computational and statistical techniques are needed that satisfy both the right to privacy and society’s need to deal with important questions. Progress has been made with new approaches such as differential privacy and distributed inference on private data. Much more needs to be done given the increasing attraction of mining such data sources, with the potential risks to individual rights.

Causality:
Some of the richest sources of extensive data for scientific study are observational (“non-randomized”) data bases made available by the explosion of technology (the internet and digital records in medicine, government and business). Naive application of inferential techniques to infer causal mechanisms will be seriously misleading on such data, potentially with disastrously mistaken conclusions. Research in new statistical and computational techniques to adjust for such data sources is needed.

The reproducibility crisis:
Repeated and often highly visible incidents have highlighted failures to reproduce “scientific” conclusions; for example, frequent editorials in prestigious journals such as Science and Nature have documented and apologized for many failures to reproduce published results.

Issues of scientific and academic culture are undoubtedly part of the problem. However, the radical changes in sources of data and algorithms applied mean that the practice of data analysis has changed enormously. Data science needs to find new inferential paradigms that allow data exploration prior to the formulation of hypotheses.

SDSI on Data Science in the health care space:

Data Science for Human Health
It is clear that data science will be a driving force in transitioning the world’s healthcare systems from reactive “sick-based” care to proactive, preventive care.

First, and most importantly, data science has the power to empower the consumer, giving them more control over their own care. People can make better, more informed decisions if their care providers are able to make better, more data-based recommendations. Imagine your care provider could access your genetic information in a proactive healthcare system, measure your genetic risk for disease—not just as an individual but also as a member of a larger population—and then help you manage that risk throughout your life course.

This is the kind of personalized, patient-focused medicine that current reactive healthcare systems cannot facilitate, because they are designed to wait until things go wrong with the human body before addressing the problem, and every individual is deemed responsible for managing his/her own health and risk. In a data-based proactive healthcare system, public education could inform people of what it means to have different levels of risk. Since we all carry some level of risk (some more than others for specific diseases), individuals could be informed of their individual and collective health risks early on, enhancing control over their own health at every stage of their lifespan.

Second, data science enables more cost-effective drug discovery, helping us do the right thing for the right person. Rather than have someone trying and failing ten different drugs at great expense to the individual and the acute-based care system (not to mention worsening quality of life for the patient), data science can help us choose the right one on the first try. Although that drug in isolation is more expensive for the system, it would have been even more expensive if we didn’t have data science because that person would have had ten different things tried and failed. Additionally, data science allows us to bring things to market more quickly, because we’re not beholden to the hypothesis-driven routine.

Third, data science technologies are capable of improving patient outcomes and conditions with variable outcomes. They can capture data inputs, weed out subtypes, and distill best practices when combating disease, such as brain or other neurological cancers.

Lastly, data science technology can also reconfigure the costs associated with delivery of care by utilizing continuous data capture, analytics, and new key insights in order to inform physicians and clinicians when things have gone wrong in the human body before patients feel unwell. That understanding could then be integrated into a new model of care, which would enable early intervention, thus preventing that individual from having to go to the hospital. Recent Stanford research has begun to explore the possibilities of monitoring cardiomyopathy patients at home and monitoring children in the ER and ICU: we believe these studies are leading us toward a future of proactive, consumer-based care.

We recognize fully that technological advancement and unprecedented growth in biomedical data have created great opportunities, but they have also introduced great challenges for protecting the privacy and security of patient and other research data. We must work with stakeholders and experts in the private sector and federal agencies, such as the NIH, to promote and practice robust and proactive information-security procedures to ensure appropriate stewardship of patient and research-participant data while at the same time enabling scientific and medical advances.

Highly recommend you read all of their topical domain info.

"Ethics and Data Science?" Yeah, I'm gonna get there too. For one thing, I gotta get around to evaluating this (below).

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More to come...

The Biden Cancer Initiative

"The Biden Cancer Initiative is a response to the lack of a cohesive, comprehensive and timely approach to cancer prevention, detection, diagnosis, research, and care."

One hopes this effort will get significant, sustained, and effective traction.

BidenCancer.org
@BidenCancer

#BidenCancerSummit

Last Friday Cheryl and I attended the local Biden Cancer Summit, which was held at John Muir Hospital in Concord (where I'd had my SAVR px heart surgery 28 days prior). Local congressman (and cancer survivor) Mark DeSaulnier hosted the event, which was comprised of a panel of clinical and medical business experts, and a panel of cancer survivors, with Q&A sessions following each panel discussion.

The CEO of the Muir Health System, Cal Knight, spoke. I subsequently introduced myself to him, and gave the hospital high praise for my treatment.

Given our long and painful history as family cancer caregivers and my own 2015 experience as a cancer patient, we found it all very interesting, if not exactly news to us. Nicely done.

Joe Biden:

I need to give some thought on how best to support this effort going forward, as I heal up fully.

All lofty, laudable principles. A number of them, however, (1, 2, 4 & 5 in particular), go to chronically contentious "multi-stakeholder" policy issue areas (e.g., "data transparency / interoperability," proprietary intellectual property vs. "open source," a more just and broadly effective health care payment system, etc). I find no detail on the website at this point addressing any of these areas in any substance (beyond, arguably, tangentially, inferentially these links). There's much drill-down work to be done (say, e.g., seven BCI "White Papers" for starters) if this undertaking is to bear fruit.

apropos, see also the NIH/NCI "Cancer Moonshot."

UPDATE

Again, from a BCI website link:

BIDEN CANCER INITIATIVE ANNOUNCES 57 NEW COMMITMENTS TO DOUBLE THE RATE OF PROGRESS
The Biden Cancer Initiative announced 57 new commitments from the public and private sectors in response to Vice President Joe and Dr. Jill Biden’s call to find solutions that will double the rate of progress against the [sic?] cancer. These innovative programs and partnerships focus on data sharing, patient support, education, and empowerment, research, clinical trials, access to care, disparities, and prevention and early detection...

OK. "...double the rate of progress." Do we have a current baseline aggregate operational definition of the current "rate of progress?" (Or, more plausibly, stratified rates of progress? Changes in Prevalence? Incidence? Mortality rates? Median survival times? Remission rates? etc.)
___

OCTOBER 3RD UPDATE

Some cautionary thoughts, via STATnews:

More research on ‘dying healthy’ will also help us live healthier
By GEORGE J. ANNAS and SANDRO GALEA, OCTOBER 3, 2018

…Advances in medical treatment, including cancer treatments, are increasingly unlikely to provide further significant gains in human longevity. An analysis of 71 cancer drugs consecutively approved between 2001 and 2012, for example, suggests that their overall contribution to survival was just 2.1 months; the gains attributable to personalized cancer medicine have, so far, also been minimal.

Lacking evidence that the human life span can be radically increased by new medical technologies, we believe it’s time to shift our country’s investment priorities away from medical research that aims to extend life and instead focus on the same social, cultural, and political factors that successfully prolonged life in the last century.

That means more public investment in education, transportation, and housing. That kind of investment would directly contribute to the prevention of chronic diseases such as diabetes, heart disease, and many cancers, and would do more to improve the quality of life of the population than additional medical research aimed at treating individuals with specific diseases.

Don’t get us wrong. We aren’t suggesting that we should eliminate funding for medical research to try to prevent, or even cure, diseases. Instead, we are suggesting that public funding should emphasize research on improving and sustaining quality of life rather than focusing on increasing length of life. This means giving greater priority to diseases that affect decades of people’s lives, such as arthritis, autism, macular degeneration, and Alzheimer’s disease over end-of-life diseases like extreme dementia and many cancers…

My early 90's healthcare QI Mentor, IHC's Brent James (MD, M.Stat) cautioned us "let's don't kid ourselves that we're going to QI our way out of the larger social conundrum: every patient for whom you provide the very best care and outcome today will eventually return as a much older and sicker patient."

And, now, as I've noted recently, to the myriad largely "non-clinical" socioeconomic "upstream" factors to be taken into account, we have to add in "exposomics" to the vast "Omics" disciplines.

Tangentially, does "dying healthy" have anything to do with "A Good Death?"

SPEAKING OF "RESEARCH"

Stay tuned. Forefront cancer research will surely be fraught with multiple difficulties.

Click to enlarge

"Given the billions of dollars the world invests in science each year, it's surprising how few researchers study science itself. But their number is growing rapidly, driven in part by the realization that science isn't always the rigorous, objective search for knowledge it is supposed to be. Editors of medical journals, embarrassed by the quality of the papers they were publishing, began to turn the lens of science on their own profession decades ago, creating a new field now called “journalology.” More recently, psychologists have taken the lead, plagued by existential doubts after many results proved irreproducible. Other fields are following suit, and metaresearch, or research on research, is now blossoming as a scientific field of its own.

For some, studying how the sausage is made is a fascinating intellectual pursuit in itself. But other metaresearchers are driven by a desire to clean up science's act…"

Tangentially, I cannot help but be reminded of something I wrote more than 20 years ago during my late elder daughter's cancer illness:

'Arrogant, narrow-minded, greedy, and indifferent?'
Is science the enemy? To the extremist "alternative healing" advocate, the answer is a resounding 'yes'! A disturbing refrain common to much of the radical "alternative" camp is that medical science is "just another belief system," one beholden to the economic and political powers of establishment institutions that dole out the research grants and control careers, one that actively suppresses simpler healing truths in the pursuit of profit, one committed to the belittlement and ostracism of any discerning practitioner willing to venture "outside the box" of orthodox medical and scientific paradigms.
 
One e-mail correspondent, a participant in the internet newsgroup alt.support.cancer, vented splenetic at length recently regarding U.S. authorities' alleged hounding, arrest, and imprisonment of alternative healers. He railed that law enforcement, at the behest of the AMA/FDA Conspiracy (a.k.a. the "corrupt AMA/FDA/NCI/ACS cartel"), had made the practice of alternative medicine illegal in the U.S. Moreover, he considered the fact that medical science can only claim "cures" for approximately 10% of the roughly 10,000 classified human diseases an a priori indictment of the mainstream profession.

I know: this is akin to the U.N. Black Helicopters/One-World-Government Conspiracy stuff of the not-too-tightly-wrapped. Still, I couldn't resist-- pointing out in (no doubt futile) reply that no one came with guns drawn and cuffs at the ready the night at Brotman Rehab when "Healing Angelite Crystals" practitioners-- devotees of India's Sai Baba-- came from Topanga Canyon to hover for hours in ceremony over Sissy (to the curious and wary befuddlement of the night shift nurses); neither did Security nor the medical staff at Brotman confiscate the goopy-looking herbal tonic we brought in, an elixir prescribed for Sissy by a Chinese herbal pharmacist doing business quite openly in Chinatown near downtown L.A.; nor would SWAT teams pounce on the backyard in the Valley where we took part in evening-long Lakota Souix "healing sweat lodge" ceremonies conducted by the venerable Wallace Black Elk; and finally, Wyndie, one of Sissy's highly skilled and effective physical therapists at Brotman did not have her certification revoked for counseling my daughter on the Hindu principles of the Chakras and efficacy of aromatherapy.

Moreover, I had to respond, the fact that we can only cure 10% of known diseases implies nothing regarding the quality of mainstream medical research and practice, unless the alternatives industry can provide hard, "case-mix adjusted," scientifically valid data showing their methods to effect consistently and significantly better outcomes-- which they cannot (a dearth of peer-reviewed studies being a central characteristic of "alternative" practice). Additionally, I asked, can anyone even cite historical curative percentages from 30, 50, or perhaps 100 years ago? Indeed, even such statistics would prove problematic-- "shooting at a moving target," as it were-- in that more subtle and clinically unresponsive maladies continue to be discovered and classified while the easier to treat are dealt with more readily. And, classificatory observation is easy compared to the work and resources required to effect cures; we should expect that identification will outpace remedy. Finally, 50 years ago death certificates listing demise from "natural causes" would today likely have identifiable diseases recorded as the cause of death.

Purveyors of medical quackery should fear the hot breath and hard heel of competent authority, but I see no evidence of suppression of alternative therapy methods that are not certifiably fraudulent. All manner of "unproven" substances are sold quite openly at retail, both in the health food stores and in the national chain outlets; all that need accompany the product is the legal boilerplate disclaimer acknowledging an absence of FDA blessing, along with the inoculating phrase 'dietary supplement.'

In fairness, as I've noted before, "I am not a scientist."
___

"More recently, psychologists have taken the lead, plagued by existential doubts after many results proved irreproducible."

apropos, I just finished this excellent book by esteemed psychologist James Alcock.

As reviewed at Science Based Medicine:

How We Believe
James Alcock’s new book about belief is a masterpiece that explains how our minds work, how we form beliefs, and why they are so powerful. It amounts to a course in psychology and an owner’s manual for the brain.
Harriet Hall on June 26, 2018

In James Alcock’s classic 1995 article “The Belief Engine“, he said, “Our brains and nervous systems constitute a belief-generating machine, a system that evolved to assure not truth, logic, and reason, but survival.” Now he has expanded that thesis into a book, Belief: What It Means to Believe and Why Our Convictions Are So Compelling. It’s much more than a book about belief. In the Foreword, Ray Hyman says it would be an ideal textbook for a course that provides an integrated overview of all the areas of psychology. He says every psychologist and psychology student should read it. It is an outstanding achievement of scholarship; its 640 pages include over 70 pages of references. It covers everything from the latest findings in neuroscience to a catalog of many of the questionable beliefs people hold, and why they hold them…

The neuropsychology of cognition (and our chronic risks of irrationality), basically. A must-read, IMO. Add another tome to my stash going to my abiding interest in the salient aspects of the cognitive attributes (and liabilities) of "expertise" (e.g., "how doctors think").

UPDATE

Got onto this via a STATnews article, "There's so much health noise..."

"I’m not a cynic. I think we need to keep an open mind and look for potential benefits wherever they may be found. But in this era of twisted facts, we all could use a nudge to keep applying critical thinking skills."

Read Alcock's compelling book "Belief." I've long and deeply studied "critical thinking," both as an undergrad and in grad school, and even thereafter got to teach it as an adjunct, but Alcock's work adds a much larger dimension. Were I teaching today, "Belief" would be a required text.

See also

Joe Schwarcz PhD - Director

I've just finished watching the Netflix "Detox" episode of Timothy Caulfield's documentary. A must-see.

BACK TO SCIENCE, AND BIDEN PRINCIPLE #6, "FIND NEW SOLUTIONS, DISSEMINATE"

Biden Summit discussions were replete with allusions to the imperative of "early detection." As reported in (firewalled) Science Magazine:

"CancerSEEK, and ye shall find?"

Most cancers are detected when they cause symptoms that lead to medical evaluation. Unfortunately, in too many cases this results in diagnosis of cancers that are locally invasive or already metastatic and hence no longer curable with surgical resection or radiation treatment. Medical therapies, which might be curative in the setting of minimal tumor burden, typically provide more limited benefit in more advanced cancers, given the emergence of drug resistance (1). On page 926 of this issue, Cohen et al. (2) describe a strategy for early cancer detection, CancerSEEK, aimed at screening for multiple different cancers within the general population. This study challenges current assumptions in the field of blood-based biomarkers and sets the stage for the next generation of cancer screening initiatives.

Given the potential curative advantage of earlier diagnosis and treatment, why have so many cancer screening approaches failed? In the past, efforts at screening healthy populations for cancer have relied on tests that were insufficiently specific. For example, most men with rising serum prostate-specific antigen (PSA) do not have prostate cancer but instead have benign prostatic enlargement. However, where accurate tests exist, there have been dramatic improvements in cancer outcomes (3). For example, advanced cervical cancer has virtually disappeared in countries where Pap screening is the standard of care; although less reliable, mammography and screening colonoscopy are recommended for early detection of breast and colon cancers in individuals above ages 40 to 45 and 50, respectively, and screening heavy smokers by use of low-dose chest computed tomography (CT) scans reduces deaths from lung cancer (4). However, these tests are imperfect, and cost-effectiveness for broad deployment remains a challenge, particularly because a multitude of false-positive test results may lead to extensive diagnostic evaluations and unnecessary medical interventions. Unfortunately, for the majority of cancers no effective early screening tests are available.

It is in this setting that emerging molecular analyses of blood specimens, so-called “liquid biopsies,” are poised to revolutionize cancer screening (5). Circulating cell-free DNA (cfDNA) in the blood consists of small fragments of DNA that are approximately 150 nucleotides in length. cfDNA is primarily derived from normal tissues, but a small fraction may be derived from tumor cells in individuals who have cancer. This circulating tumor DNA (ctDNA) may be identified by the presence of characteristic mutations in cancer genes or by variations in chromosome copy numbers (6). Recent studies have established the reliability of ctDNA genotyping for monitoring treatment response and identifying drug resistance mechanisms in patients with advanced cancer (7, 8). However, the much lower amount of ctDNA in the plasma of patients who have a localized tumor poses a challenge for early cancer screening, as does the absence of knowledge about which mutation to look for. Furthermore, some background mutations detectable in the blood may arise from nonmalignant proliferation of blood cells in older individuals, a phenomenon called clonal hematopoiesis of indeterminate potential (CHIP) (9). Importantly, cancer gene mutations alone are insufficient to identify the tissue of origin for a given cancer signal in the blood because similar mutations are present in multiple different cancers. Thus, a tissue-agnostic blood-based screening test has limited clinical utility, unless accompanied by insight into which organ should be investigated for follow-up…

There are a number of important caveats. The predictive value of any diagnostic test relies on the prevalence of the disease within the tested population. For instance, in testing apparently healthy individuals within the general population, the prevalence of all eight cancers can be conservatively estimated as 1% of people over age 64 (11). Hence, in this setting even a test that is 99% sensitive and 99% specific will yield a positive predictive value (PPV) of only 50% (half of all test positives will be a false-positive result). Similarly, a positive CancerSEEK test result would be predicted to have a PPV of 40 to 45% for a person having any of the eight different cancers (2). Although the model was not designed to screen for individual cancer types, breaking down the aggregate PPV into its individual component cancers would result in further reduction in PPV, particularly for rare cancers. Because PPVs improve with higher disease prevalence, application of any cancer screening test to subpopulations with increased genetic or environmental risk factors (for example, carriers of familial breast cancer susceptibility mutations, heavy smokers at risk for lung cancer, or patients with liver cirrhosis predisposed to hepatocellular carcinoma) would of course increase the likelihood of true-positive results.

A well-documented challenge in early cancer detection studies is that patient populations at increased risk for cancer may also have precancerous or inflammatory conditions resulting in baseline elevation of serum protein biomarkers, a confounding factor that is not well recapitulated in the healthy control population used to build the CancerSEEK test…

Undoubtedly, effective screening for early invasive cancers represents the best hope for reducing cancer mortality and morbidity. The conceptual advances and the practical feasibility of the CancerSEEK assay constitute an important milestone toward the application of early cancer detection. Most importantly, the ongoing development of cost-effective and accurate blood-based cancer screening strategies is poised to revolutionize clinical cancer care, bringing with it new emphasis on genetic and environmental risk stratification so as to tailor application of screening tests; minimally invasive imaging, biopsy, and molecular characterization of early tumors that are discovered and might be either indolent or invasive; and deployment of increasingly effective therapeutic options to stages of cancer for which they have curative potential. The vision of effective earlier cancer detection and intervention warrants validation in appropriate populations through large-scale clinical trials that are likely to radically change the way we diagnose and treat cancer.

Promising. Yet fraught with difficulty (pay particular attention to the "important caveats" paragraph).

Nonetheless, a priority research area in my view (in part, personally, because both of my late daughters presented at Stage IV).

ERRATUM

ProPublica Patient Safety Community

Ran across this Facebook group (and joined) while searching out information about medical costs and pseudoscience / quack goods and services. Some of my prior blog riffs on patient safety issues are linked here.

OCTOBER 1ST BREAKING NEWS

Nobel Prize in medicine awarded to two cancer researchers for immune system breakthrough

CODA

On deck, "Data Science." Yet another fad?

Stay tuned. "Coding Boot Camps," anyone? More here.
_____________

More to come...

A literal "shitstorm." What of the public health upshot?

Climate Change Comes Home To Roost In North Carolina
Breached swine lagoons. Overflowing coal waste ponds. Sewage in the streets. The hellish aftermath of climate-fueled Hurricane Florence.

FAYETTEVILLE, N.C. — Florence’s rain came down in sheets ― unrelenting, and for days on end.

The water inundated homes, many still boarded up from Hurricane Matthew two years earlier. It swallowed farm operations, killing millions of chickens and turkeys and overflowing open pits full of hog feces. It flooded coal ash ponds, sending the toxic byproduct of burning coal into area waterways. The smell of human waste tainted neighborhoods; in the small town of Benson, 300,000 gallons of raw sewage spilled into the streets.

On Friday, Charlotte-based Duke Energy reported that a dam containing a lake at one of its power plants in Wilmington had been breached by floodwaters, potentially spilling coal ash from a nearby dump into the Cape Fear River…

Ugh.

One immediate question of concern: what proportion of residents in the affected areas have their medical histories contained in EHRs? And, of those, what sub-proportion are housed in remote cloud-based systems largely immune from storm damage (as opposed to local in-house client-server installs in the-now flooded docs' clinics)? In the aftermath of Katrina, untold thousands of medical records were lost forever. One hopes things have materially improved since then.

I'm not finding much recent news about it. Here's one item:

LESSONS FROM FLORENCE: SET UP ADVANCE HIE CONNECTIONS
With proper disaster prep, Health Information Exchanges play key role in transmitting patient data.

Natural disasters, like Hurricane Florence, present challenges to health systems and providers not only in areas directly impacted, but also to those in neighboring regions who treat patients displaced by the catastrophe. One of the greatest issues: access to patient records.

Health Information Exchanges (HIEs), play a critical role in making these records available. But there's a catch. Electronic connections must be set up in advance by HIEs in the impacted areas and in locations where patients may migrate. And, health systems and providers on both sides of the disaster must participate in an HIE and be connected to a data-sharing network for the data transfer to occur.

Because HIEs are a relatively new resource, a closer look behind the scenes of the nation's most recent widescale natural disasters demonstrates the value these organizations offer and provides lessons as health systems prepare for the future…

That's from the only news article I've thus far found on the topic.

THE LARGER, LONGER-TERM THREAT

Ugh. Raw sewage, dead livestock, fish, pets, etc, overflowing pig farms' excrement ponds, breached power plant coal ash lagoons, massive amounts of household and automotive chemicals -- note the chemical sheens evident in most post-hurricane flooding overhead photos...

Hurricane Florence Is a Public Health Emergency, Too
With its hog manure pits, coal waste ponds, and toxic Superfund sites, North Carolina is among the worst places a major cyclone could hit.
 
...“You don’t want hog waste flowing freely for the same reasons you wouldn’t want sewage flowing freely into the river and the house,” Gisler said. Feces is a breeding ground for bacterial pathogens like salmonella and giardia, and exposure via drinking water could cause experience a number of gastrointestinal problems. Exposure via open wounds or other mucous membranes could cause E. coli.

North Carolina has seen this before. During Hurricane Floyd in 1999, the manure lagoons from dozens of hog farms spilled “over thousands of acres of private and public lands and into the watersheds of four rivers that feed the second-largest estuary system in the nation,” according to the environmental news site Coastal Review. The storm’s extreme rainfall also killed more than 20,000 hogs, whose drowned bodies’ were scattered across the coastal landscape. The state legislature passed a moratorium on new manure lagoons after Floyd, but critics say little has been done to reduce the number of them across the state...

The continuing chronic lack of comprehensive, seamless digital health record "interoperability" (my irasible "Interoperabbable") will yet again result in significant friction hampering aggregate longitudinal public health assessments -- of this, and prior natural disasters.

ERRATUM

I am now one full month out of my open heart SAVR px surgery. So far, so good, overall.

SEPT 29TH UPDATE

Largely off the press radar by now.
_____________ AnthropoceneDenial

More to come...