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Monday, April 23, 2018

"Fix the EHR?" Of course, but how about fixing the clinical process workflows?

Per my prior post "Fix the EHR!"

As reported in Healthcare IT News:
Can Lean methodology help improve EHR documentation?
Mayo Clinic researchers write in an AHIMA report that the process technique could improve electronic health record efficiency and overall satisfaction by users.

Clinical documentation improvement has been a major focus of many health systems' value-based care initiatives. But getting to more efficient and more accurate charting, especially for providers using older electronic health record systems, is a tall task with no dependable template for success.

But in AHIMA's Perspectives in Health Information Management, four experts from the Mayo Clinic College of Medicine showed how their department – the college's Department of Physical Medicine and Rehabilitation – used Lean processes for a redesign of an inefficient, first-generation EHR documentation system.

The project was a success, at least with respect to a boost in productivity and staff morale…
From the AHIMA paper:
Providing efficient, accurate, and timely patient health information is the overriding aim of an electronic health record (EHR) documentation system. As new technologies evolve and regulatory requirements continue to change, administrators who find limitations in earlier iterations of EHR systems may need to rethink existing systems and processes. Seeking to optimize quality of patient care, the leadership of the Department of Physical Medicine and Rehabilitation at an academic medical center initiated a quality improvement project utilizing Lean methodology to guide redesign of an inefficient, first-generation EHR documentation system. Baseline data were collected using therapist/EHR interaction time studies, therapist productivity measurements, and stakeholders’ surveys. Existing documentation templates, available technology, and regulatory requirements were evaluated. Outcomes included mean reductions in time spent using the EHR from 2.8 hours per day to 1.9 hours per day per therapist, increases in patient care time from 53 percent to 71 percent, and overall improvements in internal and external stakeholders’ satisfaction from 17 percent to 97.4 percent and 43 percent to 80.3 percent, respectively. The implementation of Lean methodology applied to EHR documentation template inefficiencies proved to be an effective way of reducing time spent in the EHR by therapists, improving therapist productivity, and increasing satisfaction of internal and external stakeholders.

Providing well-organized, accurate, and timely patient health information is an important aim of an electronic health record (EHR) documentation system. By the end of 2014, three-fourths of the acute care hospitals in the United States had transitioned away from exclusively paper-based health records to some form of electronic system that provided the ability to capture clinician notes in addition to other basic EHR functionality. A major concern among clinicians is that EHR adoption can interfere with practice productivity. Studies have shown that clinicians spend extra time entering data in the EHR, and it can negatively affect the time spent on patient care. As the numbers of EHR users have grown, some early adopters of EHR products have recognized the inherent process and design limitations and are reevaluating, redesigning, and even replacing earlier versions of health record automation.

Lean methodologies, which have been used for several decades in the industrial sector, are increasingly being applied to healthcare to drive quality improvement in order to reduce or eliminate errors, delays, and redundancy. The leadership of the Department of Physical Medicine and Rehabilitation of an academic medical center identified ongoing EHR limitations following the adoption of a first-generation documentation system designed for inpatient and outpatient physical therapists and occupational therapists (PTs and OTs). Lean methodology was applied utilizing the Define, Measure, Analyze, Improve and Control (DMAIC) framework to modify and enhance the existing patient care documentation system…
Good stuff. PDF copy of the paper here.

See some of my prior riffs on "workflow" here. See also my "Health Care Productivity Treadmill" post. And, my old REC deck on workflow (pdf).

Also, apropos of "Lean" methodology, see some of my coverage of the annual Lean Health Care Summits. See here as well.

Another thought: how about data-mining the EHR security logs for what they might reveal about workflow?

Also of interest:

"Q&A with Stanford Dean Dr. Lloyd Minor on harnessing technology for future physicians"

"...we will be sponsoring a national conference here on June 4 with leaders from the industry, from the EHR sector, as well as from the policy world, to focus on how we could improve the EHR so that it becomes an opportunity to improve the efficiency of practice, rather than a burden."
He addressed clinician burnout during the interview. "Relational Leadership™" anyone?


A THCB post by Don Rucker, MD, current ONC Coordinator:
APIs: A Path to Putting Patients at the Center
Some of the natives ain't buyin' it. A commenter:
Blah blah blah…the one thing you failed to mention is that Apple and Google both do API’s WITHOUT the US government’s heavy hand. They compete for developers. Have you EVER tried to ask Cerner or Epic for access to their API’s, its a total mess, a huge special effort, and just does NOT happen at all for anyone not willing to pay to play. They do NOT want you to use them.

So lets back up…we have tried the Certified EHR and it left us here…dejected, burned out MDs that are using 1990’s technology that does NOTHING to improve the Triple Aim, and obviously failed the Quad Aim.

Its time that ONC and CMS just stop all the certified madness, the hyper-regulatory action and just get out of the way of real competition. The artificial market made by HITECH has nearly destroyed the practice of medicine and further actions by the tone deaf ONC leaders and HIT leaders that can’t seem to understand that why their heavy regulatory action has not brought about positive change… you just need to go away…

So thanks ONC, CMS, but get out of the exam room, get out of the way of MDs and patients. We know what we need, stop trying to regulate and think for us. Let REAL innovation happen, we do NOT need to be babysat for our products. Stop CertEHR, Stop MIPS MACRA and counting attesting for quality points.

Do you understand you have failed Mr Rucker? Stop all the puffery language and “Value Based” talk and how you are gonna help clarify “special effort”. Just stop and let innovation come back in. You have set us back AT LEAST a decade of real progress.
Okeee dokeee, then. Tell us what you really think.


Got a new Twitter Follow. Reciprocated.

NatureVolve was created to act as a platform for scientific researchers to communicate their research to broader audiences, and for creative thinkers to share their ideas.

This is through an online digital magazine, and an online blog. In the future, we have plans for the magazine to be released to the UK in print.

We believe that combining scientific thought with artistic expression can generate effective engagement with  public audiences. We also believe there is a growing need for science and art to rekindle the harmonious relationship that was once seen during the early age of the Enlightenment. We would like to show that artists and scientists can support each other, and engage with the world while working in unison.

By sharing understandable scientific stories with the general public, and inspiring art, we hope that wider audiences can enjoy finding new ways of appreciating the natural world…
Hmmm... "Art of Medicine" stuff?

My terminally ailing Danielle, when she was 5. Below, with comedian Margaret Cho in 2014 at San Francisco Comedy Day in the Park.

Below, April 13th, probably the last photo I will post of Danielle. An increasingly rare "good" day.

We are now 6 weeks into home hospice care. She is fading away. Mostly sleeping in the hospital bed, unable to stand. Increasingly emaciated. Increasingly incoherent. Mostly one-word responses to questions. A distant stare when awake. Her son is here. He got FMLA dispensation from his employer.

Words fail to describe the sadness and stress. See my post "A tale of two sisters."

More to come...

Friday, April 20, 2018

"Happy 4/20 Day"

OK, so, this "420" is a "thing" now.

There is a bit of news on the underlying topic today, from Ars Technica:
Here are the types of marijuana best for stress and anxiety, according to users
For depression, use may exacerbate symptom severity over time.
BETH MOLE - 4/20/2018

By passively monitoring user-generated data from medical cannabis patients, researchers have glimpsed the types and amounts of marijuana that seem effective for relieving symptoms of stress, anxiety, and depression. The findings could direct more detailed research into the best strains for specific conditions. But the data also hints at a danger of using marijuana to manage depression symptoms in the long term.

The study, published this week in the Journal of Affective Disorders by researchers at Washington State University, is based on data from a medical cannabis app called Strainprint, which lets patients track symptom severity after medical cannabis use. Before that, users enter detailed information about the strain of marijuana used, including selecting specific products from a list of those sold by licensed medical cannabis distributors in Canada. Health Canada has uniquely strict production and quality control guidelines for products sold there. But if a patient is using a product not on the list, they can manually input information about the strain, including cannabinoid content.

The researchers looked at data from nearly 1,400 medical cannabis users, analyzing outcomes from almost 12,000 inhalation sessions. The researchers kept their analysis just to sessions involving inhalation (smoking, vaping, concentrates, dab bubbler, dab portable), to try to control—at least a little—for efficacy and timing of the onset of effects…
Not sure about the quality of the "science" there.

I could damn sure use some stress relief these days.

Below, from a prior post of mine.

Then there are my prior posts about our poignantly ignorant Attorney General Jeff Sessions. But, current news has his boss undermining him yet again:
"Marijuana industry poised for supercharged growth thanks to President Trump"
Whatever works to help get Robert Mueller, Michael Cohen, and Stormy Daniels out of the news.

Also apropos, from the first chapter of my 1998 graduate Thesis on the "drug testing" scam industry.

I guess overall we're making progress, net. But the idiots have hardly gone away.

Anyway, "Happy 4/20 Day."


A bit of long-past-the-statute-of-limitations full disclosure I posted in 2006.

Also, a "cannabis industry writer" I just ran across over at Medium, Los Angeles based Amanda Chicago Lewis.

More to come...

Monday, April 16, 2018

"There is no precision medicine without AI"

A reasonable assertion, I guess. But, need we still be mindful of "AI vs IA" (Artificial Intelligence vs. Intelligence Augmentation)? Or, is the latter essentially morphing increasingly into the former?

Comes a recent paper by the young wizard author of this book I've cited before:

The role of artificial intelligence in precision medicine
Bertalan Mesko
The Medical Futurist Institute; Department of Behavioral Sciences, Semmelweis University, Budapest, Hungary

Accepted 13 September 2017 (pdf link in title)

1. Introduction
The essence of practicing medicine has been obtaining as much data about the patient’s health or disease as possible and making decisions based on that. Physicians have had to rely on their experience, judgement, and problem-solving skills while using rudimentary tools and limited resources.

With the cultural transformation called digital health, disruptive technologies have started to make advanced methods available not only to medical professionals but also to their patients. These technologies such as genomics, biotechnology, wearable sensors, or artificial intelligence (AI) are gradually leading to three major directions. They have been (1) making patients the point-of-care; (2) created a vast amount of data that require advanced analytics; and (3) made the foundation of precision medicine. 

Instead of developing treatments for populations and making the same medical decisions based on a few similar physical characteristics among patients, medicine has shifted toward prevention, personalization, and precision. 

In this shift and cultural transformation, AI is the key technology that can bring this opportunity to everyday practice...
2. The dawn of practicing medicine
In previous centuries, healthcare has focused on working out generalized solutions that can treat the largest number of patients with similar symptoms. If cough syrup was good for the majority of the coughing masses and only a few people had a rash as an allergic reaction to it, there was no question about treating sore throat with cough syrup. Obtaining experience and empirical evidence on a generalized basis was the working method of the medical community since Hippocrates until around the beginning of the twentieth century. 

With the refinement of diagnostic tools, the detection of viruses or bacteria, the development of new pharmaceuticals and medical methods, healthcare has been going through sweep- ing changes since the start of the last century. The experience- based and somewhat ‘trial-and-error’ approach of medicine made place for evidence-based medicine. As a consequence, physicians not only prescribed treatments because their ancestors also used the same methods, but they proved the efficacy of treatments and diagnostic methods in scientific papers and clinical studies…

3. There is no precision medicine without AI
As the National Institutes of Health described it, precision medicine is ‘an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment and lifestyle for each person.’[3] This approach allows doctors and researchers to predict more accurately which treatment and prevention strategies for a particular disease will work in which groups of people. 

It requires significant computing power (supercomputers); algorithms that can learn by themselves at an unprecedented rate (deep learning); and generally, an approach that uses the cognitive capabilities of physicians on a new scale (AI)…

4. AI in clinical practice
A major application of AI in healthcare is collecting, storing, normalizing, and tracing data. The AI research branch of the search giant, Google, launched its DeepMind Health project, which is used to mine the data of medical records in order to provide better and faster health services. In 2016, they launched a cooperative project with the Moorfields Eye Hospital NHS Foundation Trust to improve eye treatment [9]. To investigate how technology could help to analyze eye scans, Moorfields shared a set of one million anonymized eye scans with DeepMind and some related anonymous information about eye condition and disease management…

5. Is precision medicine the end of the human touch?
With advantages will also come ethical considerations and legal issues. Who is to blame if an AI system makes a false decision or prediction? Who will build in safety features? How will the economy respond to the appearance of AI when it starts making certain jobs useless? With driverless cars, there is a global debate about what decisions the algorithms would make in tricky situations. When it comes to health, this becomes a vastly bigger ethical challenge. There are more unanswered questions today than we can deal with and hopefully, with public discussions worldwide, this will clear up as AI is becoming a reality.
AI also has serious limitations in healthcare. Forecasting and prediction are mediated based on precedence in the case of machine learning, but algorithms can be underperforming in novel cases of drug side effects or treatment resistance where there is no prior example to build on. Hence, AI may not replace tacit knowledge that cannot be codified easily…

…Through the cultural transformation called digital health, the hierarchy of traditional medicine is transforming into an equal-level partnership between patients and caregivers. Besides many disruptive technologies, AI has the biggest potential to support this transition by analyzing the vast amounts of data patients and healthcare institutions record in every moment. By taking away the repetitive parts of a physician’s job, it might lead to being able to spend more precious time with their patients, improving the human touch. However, AI can only fulfill its mission if it remains a safe, efficient, and proven aid in treating patients and improving healthcare.
"By taking away the repetitive parts of a physician’s job, it might lead to being able to spend more precious time with their patients, improving the human touch. However, AI can only fulfill its mission if it remains a safe, efficient, and proven aid in treating patients and improving healthcare."

Well, yeah, you can't argue with that closing sentiment. But, for one thing, revisit my prior post "Artificial Intelligence and Ethics." See also my post on remediating "Clinician Burnout."

And, recall, we gotta "Fix the EHRs."

Bertalan's paper is well worth a close read. This stuff is coming, for better and/or worse.


I've run across (via my new issue of Harper's) a breathtakingly marvelous young writer of riveting eloquence and broad perceptivity, Meghan O'Gieblyn: 
There are two kinds of technology critics. On one side are the determinists, who see the history of technology as one of inexorable progress, advancing according to its own Darwinian logic—the wheel, the steam engine, the autonomous car—while humans remain its hapless passengers. It is a fatalistic vision, one even the Luddite can find bewitching. “We do not ride upon the railroad,” Thoreau said, watching the locomotive barrel through his forest retreat. “It rides upon us.” On the opposite side of the tracks lie the social constructivists. They want to know where the train came from, and also, why a train? Why not something else? Constructivists insist that the development of technology is an open process, capable of different outcomes; they are curious about the social and economic forces that shape each invention.
Nowhere is this debate more urgent than on the question of artificial intelligence. Determinists believe all roads lead to the Singularity, a glorious merger between man and machine. Constructivists aren’t so sure: it depends on who’s writing the code. In some sense, the debate about intelligent machines has become a hologram of mortal outcomes—a utopia from one perspective, an apocalypse from another. Conversations about technology are almost always conversations about history. What’s at stake is the trajectory of modernity. Is it marching upward, plunging downward, or bending back on itself? Three new books reckon with this question through the lens of emerging technologies. Taken collectively, they offer a medley of the recurring, and often conflicting, narratives about technology and progress...
I could not recommend Meghan's eclectic writing more enthusiastically.


Erratum, from THCB:

Twitter-Based Medicine: How Social Media is Changing the Public’s View of Medicine

Doctors can be two-faced. This isn’t necessarily a negative attribute. Doctors have distinct personas for our patients and our colleagues. With patients, doctors strive for a compassionate but authoritative role. However, with each other, doctors often reveal a different demeanor: thoughtful and collaborative, but also opinionated and even sometimes petty. These conflicts are often the result of our struggle with evidence-based medicine. The modern practice of evidence-based medicine is more than the scientific studies we read in journals. Medicine doesn’t just change in rational, data-driven increments. Evidence-based medicine is a dialectic, a conversation. Doctors are being continually challenged to reconcile personal experience, professional judgment, and scientific data. Conflict can naturally result.

This struggle has been ongoing since the rise of evidence-based medicine decades ago. There are factions in medicine who are skeptical of clinical trials as the answer to all of medicine’s important questions, while other factions are wary of authority and consensus-driven medicine. These battles have traditionally been confined to the doctor’s lounge, both literal and in the figurative “safe spaces” of academic journals and conferences. But now the doctor’s lounge is going public. Social media is enabling doctors to rapidly communicate with each other. The heated public arguments that often result are in turn raising new questions about the effect of public discourse on the medical profession and the patients we serve.

I think the social media platform that’s doing the most to influence public debate about medicine is Twitter. Twitter, with its character limits, bandwagons, and trolls may seem inhospitable to nuanced medical debate, but the power of Twitter to broadcast physicians’ instinctive and abbreviated thoughts is underappreciated…
Interesting post.

Then there's the biz sided of things. From the NY Times:

Is the doctor in?

In this new medical age of urgent care centers and retail clinics, that’s not a simple question. Nor does it have a simple answer, as primary care doctors become increasingly scarce.

“You call the doctor’s office to book an appointment,” said Matt Feit, a 45-year-old screenwriter in Los Angeles who visited an urgent care center eight times last year. “They’re only open Monday through Friday from these hours to those hours, and, generally, they’re not the hours I’m free or I have to take time off from my job.

“I can go just about anytime to urgent care,” he continued, “and my co-pay is exactly the same as if I went to my primary doctor.”

That’s one reason big players like CVS Health, the drugstore chain, and most recently Walmart, the giant retailer, are eyeing deals with Aetna and Humana, respectively, to use their stores to deliver medical care.

People are flocking to retail clinics and urgent care centers in strip malls or shopping centers, where simple health needs can usually be tended to by health professionals like nurse practitioners or physician assistants much more cheaply than in a doctor’s office. Some 12,000 are already scattered across the country, according to Merchant Medicine, a consulting firm.

On the other side, office visits to primary care doctors declined 18 percent from 2012 to 2016, even as visits to specialists increased, insurance data analyzed by the Health Care Cost Institute shows.

There’s little doubt that the front line of medicine — the traditional family or primary care doctor — has been under siege for years. Long hours and low pay have transformed pediatric or family practices into unattractive options for many aspiring physicians.

And the relationship between patients and doctors has radically changed. Apart from true emergency situations, patients’ expectations now reflect the larger 24/7 insta-culture of wanting everything now…
Lots of moving parts, many of them still moving at cross-purposes. Lots of "disruption."

Announcing the RWJF AI & The Healthcare Consumer Challenge!

…With the advent of advanced and robust AI platforms in marketing, law, and other sectors, we’re observing the vast opportunities for AI solutions in healthcare decision making. As medicine becomes more specialized, talent bottlenecks are developing and leading to increased professional strain on healthcare providers and consumers. To bring clarity and personalization to the healthcare industry, the Robert Wood Johnson Foundation is teaming up with Catalyst @ Health 2.0 to foster change in this space.

The RWJF AI & The Healthcare Consumer Challenge is calling all innovators to create AI enabled tools that support well-informed health decisions. By accelerating image recognition, data analysis, and pattern detection, we can start to remove harmful elements of human error from our systems. With predictive analysis, deep learning, and other AI enabled tools, innovators have the opportunity to help healthcare consumers make more informed and accurate decisions about the best health pathways to explore. With $100,000 in total challenge prizes, the most innovative solutions can bring attention to the benefits of AI in the consumer domain, as well as gain funding to continue tech development. Applicants can submit solutions such as tools to help find the ideal physician, estimate the cost of a health plan, or chatbots that track daily health decisions; it is up to YOU to do your part in solving a multi-billion dollar problem that affects all Americans…

More to come...

Monday, April 9, 2018

"Fix the EHR!"

From THCB:

After a blizzard of hype surrounding the electronic health record (EHR), health professionals are now in full backlash mode against this complex new tool. They are rightly seen as a major cause of professional burnout among physicians and nurses: Clinicians are spending almost half their professional time typing, clicking, and checking boxes on electronic records. They can and must be made into useful, easy-to-use tools that liberate, rather than oppress, clinicians.

Performing several tasks, badly. The EHR is a lot more than merely an electronic version of the patient’s chart. It has also become the control panel for managing the clinical encounter through clinician order entry. Moreover, through billing and regulatory compliance, it has also become a focal point of quality-improvement efforts. While some of these efforts actually have improved quality and patient safety, many others served merely to “buff up the note” to make the clinician look good on “process” measures, and simply maximize billing…
Above, my Photoshop reaction.

I've cited Dr. Wachter multiple times on this blog.

My solution? My next iteration of my Clinic Monkey EHR will be "Blockchain Monkey EHR!"

But, according to "Healthcare Kate," "EHR's are a dying technology."

"Relational Leadership™" to the rescue?

Stay tuned. Just getting underway. A lot going on at my house these days. None of it fun.


I'm demonstrably no newcomer to crackin' on EHR technology policy.

See "ICD-10: W6142XA, Struck by turkey, initial encounter."


After reading this week's accruing comments under the THCB "Fix the EHR" post, I feel like it's pointless to yet again point out the direct experience-based assertions I've posted many times. It's not the technology per se, it's the prevailing "productivity treadmill" economic paradigm (including the "shards" of a fragmented system) which leaves clinicians insufficient time to document their work in a timely, necessary, and accurate fashion. Nibbling around the edges, tossing out frustrating, admittedly dubious value "process indicators" (they are not "clinical quality measures") won't move the needle visibly (not that we shouldn't pare them back).

I'd ask these aggrieved blog commenter policy geniuses: "which of the (hundreds to thousands) pt encounter SOAP note elements would you discard?"

Paper is not "better." Paper kills. As does the prevailing socioeconomic / political system as it impacts health care.

Yes, my own broad, multi-EHR in-the-trenches HIT experience is getting a bit dated. But, my world is now "All Epic, All The Time" as my daughter's caregiver and as a patient myself. I continue to be a keen observer of the workflows I see during our clinical interactions.

Yes, clinicians suffer from 'burnout," worn down by impossible demands. But cutting the guts out of EHRs or tweaking the UX at the margins, well, not gonna get us anywhere.


eClinicalWorks CEO Girish Navani: Our next EHR will be like a Bloomberg Terminal
The electronic health record vendor is working on a version that would run on monitors such as Microsoft Surface and feature four distinct panels to help doctors make decisions.

LAS VEGAS – While eClinicalWorks is demonstrating its latest cloud-based EHR and new offerings for inpatient settings at HIMSS18, CEO Girish Navani gave a glimpse of the forthcoming iteration — and the goal is to resemble a Bloomberg Terminal.

The hosted service would make a bold step forward for the EHR vendor that last year settled a $155 million case with the U.S. Department of Justice in a False Claims Act suit.

Much in the way the Bloomberg device delivers information to help bond traders make decisions in near real-time, the next version of eClinicalWorks will provide doctors with four key technologies each on its own screen.
Navani described the setup as such: A physician walks into her office with a big monitor that has a population health panel containing information about the patients the doctor will see that day, a telemedicine tool for virtually connecting with patients, a voice-based virtual assistant for interacting with the software and a machine learning-based panel making evidence-based clinical suggestions…
 OK, then. More data onscreen, fewer mouse clicks? What about quickly actionable data "visibility?"

More to come...

Wednesday, April 4, 2018

"The unsinkable rubber duckies of pseudoscience"

An excellent book I ran across cited at my requisite priority daily stop, Science Based Medicine.

From the preface:
We find ourselves living increasingly in a “post-truth” world, one in which emotions and opinions count for more than well-established findings when it comes to evaluating assertions. In much of contemporary Western culture, such catchphrases as “Don’t confuse me with the facts,” “Everyone is entitled to my opinion,” and “Trust your gut” capture a troubling reality, namely, that many citizens do not— and in some cases, apparently cannot— adequately distinguish what is true from what they wish to be true. This overreliance on the “affect heuristic,” the tendency to gauge the truth value of a proposition based on our emotional reactions to it (Slovic, Finucane, Peters, and MacGregor, 2007), frequently leads us to accept dubious assertions that warm the cockles of our hearts, and to reject well-supported assertions that rub us the wrong way. We are all prone to this error, but one hallmark of an educated person is the capacity to recognize and compensate for it, at least to some degree. 

We also live increasingly in an age in which intuition is prized above logical analysis. Even some prominent science writers (Horgan, 2005) and prominent scientists (Diamond, 2017) have maintained that “common sense” should be accorded more weight in the adjudication of scientific claims than it presently receives. Such endorsements of everyday intuition are surprising, not to mention ahistorical, given overwhelming evidence that commonsense reasoning often contributes to grossly mistaken conclusions (Chabris and Simons, 2011; Kahneman, 2011; Lilienfeld, 2010). As one example, the history of medicine is a much-needed reminder that excessive reliance on gut hunches and untutored behavioral observations can cause scholars and practitioners to embrace ineffective and even harmful interventions (for a horrifying example, see Scull, 2007). Indeed, according to many medical historians, prior to 1890 the lion’s share of widely administered physical interventions were worthless and in some cases iatrogenic (Grove and Meehl, 1996). 
These trends are deeply concerning in today’s age of virtually nonstop data flow via social media, email, cable television, and the like. We live not merely in an information age, but in a misinformation age. In 1859 the author and preacher C. H. Spurgeon famously wrote that “A lie will go round the world while truth is pulling its boots on” (in a curious irony, this quote has itself been widely misattributed to Mark Twain). If Spurgeon’s dictum was true in 1859, it is all the more true in today’s world of instantaneous information transfer across the world. Not surprisingly, the levels of many pseudoscientific beliefs among the general population are high, and may well be increasing…
...The present book is a superbly edited presentation of valuable lessons regarding the application of scientific thinking to the evaluation of potentially pseudoscientific and otherwise questionable claims. In the section to follow, I attempt to distill these lessons into ten user-friendly take-home messages. It may strike some readers as odd to begin a book with a list of lessons, given that such lists usually crop up in a book’s afterword or postscript. But I hope to provide readers with a roadmap of sorts, pointing them to integrative principles to bear in mind while consuming this book’s diverse chapters. In generating these lessons, I have drawn in part on the chapters of this volume, and in part on the extant literature on cognitive biases and scientific thinking.

(1) We are all biased. Yes, that includes you and me. Some evolutionary psychologists maintain that certain biases in thinking are the products of natural selection (Haselton and Buss, 2000). For example, under conditions of uncertainty we are probably evolutionarily predisposed toward certain false positive errors (Shermer, 2011). When walking through a forest, we are generally better off assuming that a moving stick-like object is a dangerous snake rather than a twig being propelled by the wind, even though the latter possibility is considerably more likely. Better safe than sorry. Whether or not these evolutionary psychologists are correct, it seems likely that many cognitive biases are deeply ingrained in the human cognitive apparatus.

(2) We are largely unaware of our biases. Research on bias blind spot (Pronin, Lin, and Ross, 2002) demonstrates that most of us can readily identify cognitive biases in just about everyone except for one person— ourselves. As a consequence of this metabias, we often believe ourselves largely immune to serious errors in thinking that afflict others. We are not merely biased; we tend to be blind to our own biases. As a consequence, we are often overconfident of our beliefs, including our false beliefs.

(3) Science is a systematic set of safeguards against biases. Despite what most of us learned in high school, there is probably no single “scientific method”— that is, a unitary recipe for conducting science that cuts across all research domains (McComas, 1996). Instead, what we term “science” is almost certainly an exceedingly diverse, but systematic and finely honed, set of tools that humans have developed over the centuries to compensate for our species’ biases (Lilienfeld, 2010). Perhaps foremost among these biases is confirmation bias, the propensity to selectively seek out, selectively interpret, and recall evidence that supports our hypotheses, and to deny, dismiss, and distort evidence that does not (Nickerson, 1998). As social psychologists Carol Tavris and Elliott Aronson (2007) have observed, science is a method of arrogance control; it helps to keep us honest.

(4) Scientific thinking does not come naturally to the human species. As many authors have noted, scientific thinking is unnatural (McCauley, 2011). It needs to be acquired and practiced assiduously. Some authors (e.g., Gilbert, 1991) have even contended that our cognitive apparatus is a believing engine. We believe first, question later (see also Kahneman, 2011). In contrast, some eminent developmental psychologists and science educators have argued that human babies and young children are “natural-born scientists” (e.g.., Gopnik, 2010). True, babies are intellectually curious, seek out patterns, and even perform miniature experiments on the world. But they are not good at sorting out which patterns are real and which are illusory. Moreover, the fashionable view that babies are natural scientists is difficult to reconcile with the fact that science emerged relatively late in human history. According to some scholars, science arose only once in the course of the human species, namely in ancient Greece, not reappearing in full-fledged form until the European enlightenment of the eighteenth century (Wolpert, 1993). Such historical realities are not easily squared with claims that science is part-and-parcel of the human cognitive apparatus.

(5) Scientific thinking is exasperatingly domain-specific. Findings in educational psychology suggest that scientific thinking skills generalize slowly, if at all, across different domains. This point probably helps to explain why it is so difficult to teach scientific thinking as a broad skill that can be applied to most or all fields (Willingham, 2007). This sobering truth probably also helps to explain why even many Nobel Prize winners and otherwise brilliant thinkers can easily fall prey to the seductive sway of pseudoscience. Consider Linus Pauling, the American biochemist and two-time Nobel Prize winner who became convinced that orthomolecular therapy, involving ingestion of massive doses of vitamin C, is an effective treatment for schizophrenia, cancer, and other serious maladies (see Lilienfeld and Lynn, 2016, and Offit, 2017, for other examples). We should remind ourselves that none of us is immune to the temptations of specious claims, particularly when they fall well outside of our domains of expertise.

(6) Pseudoscience and science lie on a spectrum. As I noted earlier, there is almost surely no bright line distinguishing pseudoscience from science. Like many pairs of interrelated concepts, such as hill versus mountain and pond versus lake, pseudoscience and science bleed into each other imperceptibly. My campus at Emory University has a modestly sized body of water that some students refer to as a large pond, others as a small lake. Who’s right? Of course, there’s no clear-cut answer. The pseudoscience-science distinction is probably similar. Still, as I have pointed out, the fact that there is no categorical distinction between pseudoscience and science does not mean that we cannot differentiate clear-cut exemplars of each concept. Just as no one would equate the size of a small pond in a local city park with the size of Lake Michigan, few of us would equate the scientific status of crystal healing with that of quantum mechanics.

(7) Pseudoscience is characterized by a set of fallible, but useful, warning signs. Some contributors to this edited volume appear to accept the view that pseudoscience is a meaningful concept, whereas others appear not to. Following the lead of the philosopher of science Larry Laudan (1983), the latter authors contend that, because the effort to demarcate pseudoscience from science has failed, there is scant substantive coherence to the pseudoscience concept. My own take, for what it is worth, is that pseudoscience is a family-resemblance concept (see also Pigliucci and Boudry, 2013) that is marked by a set of fallible, but nonetheless useful, warning signs. Such warning signs differ somewhat across authors, but often comprise an absence of self-correction, overuse of ad hoc maneuvers to immunize claims from refutation, use of scientific-sounding but vacuous language, extraordinary claims in the absence of compelling evidence, overreliance on anecdotal and testimonial assertions, avoidance of peer review, and the like (Lilienfeld, Lynn, and Lohr, 2014). Despite their superficial differences, these warning signs all reflect a failure to compensate for confirmation bias, an overarching characteristic that sets them apart from mature sciences.

(8) Pseudoscientific claims differ from erroneous claims. Intuitively, we all understand that there is a fundamental difference between fake new and false news. The latter is merely incorrect, and typically results from the media getting things wrong. In contrast, the former is deceptive, often intentionally so. Similarly, many and arguably most assertions in science are surely erroneous, but that does not render them pseudoscientific. Instead, pseudoscientific claims differ from incorrect scientific claims, and in many ways are far more pernicious, because they are deceptive. Because they appear at first blush to be scientific, they can fool us. To most untrained eyes, they appear to be the real thing, but they are not.

(9) Scientific and pseudoscientific thinking are cut from the same basic psychological cloth. In many respects, this is one of the most profound insights imparted by contemporary psychology. Heuristics— mental shortcuts or rules of thumb— are immensely valuable in everyday life; without them, we would be psychologically paralyzed. Furthermore, in most cases, heuristics lead us to approximately correct answers. For example, if three people wearing masks and wielding handguns break into a bank and tell all of us to drop to the floor, we would be well advised to rely on the representativeness heuristic, the principle that like goes with like (Tversky and Kahneman, 1974). By doing so, we would conclude that because these individuals resemble our prototype of bank robbers, they are probably bank robbers. In fact, the invocation of the heuristic in this case and others is not only wise, but usually correct. Still, when misapplied, heuristics can lead to mistaken conclusions. For example, many unsubstantiated complementary and alternative medical remedies draw on the representativeness heuristic as a rationale for their effectiveness (Nisbett, 2015). Many companies market raw brain concentrate in pill form to enhance memory and mood (Gilovich, 1991). The reasoning, apparently, is that because psychological difficulties stem from an inadequately functioning brain, “more brain matter” will somehow help the brain to work better.

(10) Skepticism differs from cynicism. Skepticism has gotten a bad rap in many quarters, largely because it is commonly confused with cynicism. The term “skeptic” derives from the Greek word “skeptikos,” meaning “to consider carefully” (Shermer, 2002). Skepticism requires us to keep an open mind to new claims but to insist on compelling evidence before granting them provisional acceptance. In this respect, skepticism differs from cynicism, which implies a knee-jerk dismissal of implausible claims before we have had the opportunity to investigate them carefully (Beyerstein, 1995). In fairness, some individuals in the “skeptical movement” have at times blurred this crucial distinction by rejecting assertions out of hand. Skeptics need to be on guard against their propensities toward disconfirmation bias, a variant of confirmation bias in which we reflexively reject assertions that challenge our preconceptions (Edwards and Smith, 1996).

If readers keep the foregoing ten lessons in mind while reading this volume, they should be well equipped to navigate their way through its stimulating chapters and their broader implications. These lessons should also remind readers that we are all susceptible to questionable claims, and that science, although hardly a panacea, is ultimately our best bulwark against our own propensities toward irrationality.

Kaufman, Allison B.; Kaufman, James C. (2018-01-26). Pseudoscience: The Conspiracy Against Science (MIT Press) (Kindle Locations xi-313). The MIT Press. Kindle Edition.
Yeah. Not exactly a new concern. Below, a book in my stacks since 1996.

Also, sitting right behind that one on the shelf (circa 1991).

One of my favs. I think I gave away my original hardbound edition. Have it paperback now.

Ahhh... what do I know? "I am not a scientist."

apropos of the topic broadly, I know you would enjoy this book:

An "ology" of error. I'd cited it here several years ago. Kathryn Schulz rocks!

Oh, and, one more thing.

See last year's post citing it, "Just the facts..." Also,

Another recommendation


I previously mentioned this book:

From the SBM review,
The Ethics of CAM: More Harm than Good?
A new book examines the ethics of Complementary and Alternative Medicine (CAM). Ernst and Smith demonstrate that CAM is inherently unethical and does more harm than good.

Edzard Ernst is arguably the world’s foremost expert on the claims and the evidence (or lack thereof) for Complementary and Alternative Medicine (CAM). Now he has teamed up with a medical ethicist, Kevin Smith, to co-author a new book, More Harm than Good? The Moral Maze of Complementary and Alternative Medicine. Much has been written on CAM, but this book takes a new approach. It asks if CAM is ethical, and answers with a resounding “No.”...
Goes to scientific thinking, which ethically requires, among other attributes, "competence." From the book:
1. Clinical Competence

To what extent can practitioners and promoters of CAM be relied upon to practice or recommend safe and effective treatments? This is the question that we shall consider in this chapter.

The idea that it is morally required for healthcare professionals to practice safe and effective forms of therapy— in other words, to be competent— is self-evidently correct and incontestable. The ethical reasons for practitioner competence include:

a. To avoid patients being harmed by unsafe therapies;  
b. To avoid patients being harmed through failing to benefit from the most effective therapies available;  
c. To avoid harm to patients through the promotion of a general belief in ‘alternatives’ to proven forms of medicine.
Thus, avoidance of harm is the main ethical rationale underpinning the presumption that competence is an ethical requirement. To prevent harm, there exists a moral imperative on those practicing or recommending any form of healthcare to ensure that their knowledge is thorough and up-to-date. More fundamentally, this knowledge must be scientifically and logically valid. Moreover, it can never be sufficient for healthcare practitioners to merely act in good faith: regardless of how sincerely a false medical belief is held, the agent who acts— however honestly— on such a belief is liable to become the subject of justifiable moral opprobrium. For example, consider a religiously motivated physician who insists in treating his patients by intercessory prayer . This physician is behaving in an ethically reprehensible manner, and the fact that he truly believes in prayer as the best form of therapy does not justify this practice, nor does it excuse him morally.

Regrettably, the reality is that many CAM proponents allow themselves to be deluded as to the efficacy or safety of their chosen therapy, thus putting at risk the health of those who heed their advice or receive their treatment…

1 What Does ‘Competent’ Mean?

Mean? Most CAM practitioners believe themselves to be competent. This raises some important questions: amongst CAM advocates and practitioners, what is competence taken to mean?...

Ernst, Edzard; Kevin Smith. More Harm than Good?: The Moral Maze of Complementary and Alternative Medicine (Kindle Locations 543-562). Springer International Publishing. Kindle Edition.
Prior to this material, the authors provide a very good summary of the principal schools of "ethical" reasoning.
Introduction to Medical Ethics

This introduction is aimed at those readers who are unfamiliar with the principles, frameworks and approaches used in medical ethics. Those already familiar with the basic ethical concepts used in medicine are invited to ignore this section and instead turn directly to Chapter 1.

Medical ethics is a scholarly discipline and like all academic areas contains its own language and theory. A number of formal theoretical frameworks and principles are utilised by medical ethicists in their analyses of ethical problems. However, in this book our ethical points will be based on straightforward argumentation wherever possible. We will refer to formal academic ethical theory only where necessary and always avoid impenetrable or abstruse theory.

However, since ethical frameworks and principles form the substance of professional ethical discourse, it will be useful for the reader to have a broad understanding of these. And, while avoiding undue reliance on formal ethical theory, we will where appropriate utilise theoretical approaches to help analyse specific ethical issues that arise in CAM.

Throughout this book, our ethical considerations of the issues raised by CAM will be based on an ethical approach known as utilitarianism. This ethical framework, which seeks to evaluate the consequences of behaviours and decisions in medicine, is explained in some depth below. Utilitarianism is frequently employed in medical ethics; however, it is not the only approach available or defendable. We think it will be valuable for readers to have some knowledge of the other major ethical approaches that are used in medicine, since this will provide context for the utilitarian approach, and help to show how the other major ethical approaches reach broadly the same basic conclusions about the ethics of CAM as arrived at by utilitarian reasoning.

Thus, we set out below the major approaches used in medical ethics. (It is worth noting that these approaches are also employed in ethics more generally, not only in the domain of medicine.)
[ibid, Kindle Locations 51-66]
Given that my 1998 grad degree is in "Ethics and Policy Studies," I found all of this intrinsically interesting and mostly a quite familiar "refresher course."

All of the foregoing comprise shots below the waterlines of "The unsinkable rubber duckies of pseudoscience." Highly recommended readings.


My own painful experience dealing with medical pseudoscience goes back to the days of my late elder daughter's illness. From my "One in Three" essay:
'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…
Twenty years later, I keep having to fend off the same bullshit while dealing with Danielle's illness.

More to come...

Monday, April 2, 2018

Sleep, health, and IT

As I noted my my prior post, I'm onto yet another intriguing book.

Heard the author interviewed yesterday on NPR's "Hidden Brain" while taking my departing son to the airport.

I have had episodic dysfunctional sleep for more than 15 years (Mr. 'Busy Brain"). Now, as we deal with the end stage of my daughter's Stage IV cancer, the unrelenting daily stress (complicated by my looming surgical aortic stenosis px anxiety) makes it quite difficult to consistently get a good night's sleep.
We now have a President who brags about only getting four hours sleep a night. Check the date/time stamps on his tweets. I'm not sure he even gets four hours. Do you find that comforting? Not me.
This book has gotta go to the top of my burgeoning pile (at least six books in various stages of completion now).

Some excerpts:

Do you think you got enough sleep this past week? Can you recall the last time you woke up without an alarm clock feeling refreshed, not needing caffeine? If the answer to either of these questions is “no,” you are not alone. Two-thirds of adults throughout all developed nations fail to obtain the recommended eight hours of nightly sleep.

I doubt you are surprised by this fact, but you may be surprised by the consequences. Routinely sleeping less than six or seven hours a night demolishes your immune system, more than doubling your risk of cancer. Insufficient sleep is a key lifestyle factor determining whether or not you will develop Alzheimer’s disease. Inadequate sleep—even moderate reductions for just one week—disrupts blood sugar levels so profoundly that you would be classified as pre-diabetic. Short sleeping increases the likelihood of your coronary arteries becoming blocked and brittle, setting you on a path toward cardiovascular disease, stroke, and congestive heart failure. Fitting Charlotte Brontë’s prophetic wisdom that “a ruffled mind makes a restless pillow,” sleep disruption further contributes to all major psychiatric conditions, including depression, anxiety, and suicidality.

Perhaps you have also noticed a desire to eat more when you’re tired? This is no coincidence. Too little sleep swells concentrations of a hormone that makes you feel hungry while suppressing a companion hormone that otherwise signals food satisfaction. Despite being full, you still want to eat more. It’s a proven recipe for weight gain in sleep-deficient adults and children alike. Worse, should you attempt to diet but don’t get enough sleep while doing so, it is futile, since most of the weight you lose will come from lean body mass, not fat.

Add the above health consequences up, and a proven link becomes easier to accept: the shorter your sleep, the shorter your life span. The old maxim “I’ll sleep when I’m dead” is therefore unfortunate. Adopt this mind-set, and you will be dead sooner and the quality of that (shorter) life will be worse. The elastic band of sleep deprivation can stretch only so far before it snaps…

Scientists such as myself have even started lobbying doctors to start “prescribing” sleep. As medical advice goes, it’s perhaps the most painless and enjoyable to follow. Do not, however, mistake this as a plea to doctors to start prescribing more sleeping pills—quite the opposite, in fact, considering the alarming evidence surrounding the deleterious health consequences of these drugs…

Astonishing, but until very recently, this was reality: doctors and scientists could not give you a consistent or complete answer as to why we sleep. Consider that we have known the functions of the three other basic drives in life—to eat, to drink, and to reproduce—for many tens if not hundreds of years now. Yet the fourth main biological drive, common across the entire animal kingdom—the drive to sleep—has continued to elude science for millennia.

Addressing the question of why we sleep from an evolutionary perspective only compounds the mystery. No matter what vantage point you take, sleep would appear to be the most foolish of biological phenomena. When you are asleep, you cannot gather food. You cannot socialize. You cannot find a mate and reproduce. You cannot nurture or protect your offspring. Worse still, sleep leaves you vulnerable to predation. Sleep is surely one of the most puzzling of all human behaviors.

On any one of these grounds—never mind all of them in combination—there ought to have been a strong evolutionary pressure to prevent the emergence of sleep or anything remotely like it…

Walker, Matthew (2017-10-02T23:58:59). Why We Sleep: Unlocking the Power of Sleep and Dreams (Kindle Locations 69-122). Scribner. Kindle Edition.
A great read thus far. Only just getting underway.

Matthew Walker on the morning news:


What about sleep-deprived clinicians?

If you are about to receive medical treatment at a hospital, you’d be well advised to ask the doctor: “How much sleep have you had in the past twenty-four hours?” The doctor’s response will determine, to a statistically provable degree, whether the treatment you receive will result in a serious medical error, or even death. All of us know that nurses and doctors work long, consecutive hours, and none more so than doctors during their resident training years. Few people, however, know why. Why did we ever force doctors to learn their profession in this exhausting, sleepless way? The answer originates with the esteemed physician William Stewart Halsted, MD, who was also a helpless drug addict.

Halsted founded the surgical training program at Johns Hopkins Hospital in Baltimore, Maryland, in May 1889. As chief of the Department of Surgery, his influence was considerable, and his beliefs about how young doctors must apply themselves to medicine, formidable. There was to be a six-year residency, quite literally. The term “residency” came from Halsted’s belief that doctors must live in the hospital for much of their training, allowing them to be truly committed in their learning of surgical skills and medical knowledge. Fledgling residents had to suffer long, consecutive work shifts, day and night. To Halsted, sleep was a dispensable luxury that detracted from the ability to work and learn. Halsted’s mentality was difficult to argue with, since he himself practiced what he preached, being renowned for a seemingly superhuman ability to stay awake for apparently days on end without any fatigue.

But Halsted had a dirty secret that only came to light years after his death, and helped explain both the maniacal structure of his residency program and his ability to forgo sleep. Halsted was a cocaine addict. It was a sad and apparently accidental habit, one that started years before his arrival at Johns Hopkins.

Early in his career, Halsted was conducting research on the nerve-blocking abilities of drugs that could be used as anesthetics to dull pain in surgical procedures. One of those drugs was cocaine, which prevents electrical impulse waves from shooting down the length of the nerves in the body, including those that transmit pain. Addicts of the drug know this all too well, as their nose, and often their entire face, will become numb after snorting several lines of the substance, almost like having been injected with too much anesthetic by an overly enthusiastic dentist…

Halsted inserted his cocaine-infused wakefulness into the heart of Johns Hopkins’s surgical program, imposing a similarly unrealistic mentality of sleeplessness upon his residents for the duration of their training. The exhausting residency program, which persists in one form or another throughout all US medical schools to this day, has left countless patients hurt or dead in its wake—and likely residents, too. That may sound like an unfair charge to level considering the wonderful, lifesaving work our committed and caring young doctors and medical staff perform, but it is a provable one.
[Walker, op cit pp. 316 - 318]
Wow. I still vividly recall the zombie-shuffling senior Resident assigned to Sissy's case in 1996 at L.A. County / USC Hospital, as he endured 30+ hour continuous shifts. That vestigial "Iron Man" MedEd syndrome still prevails to a great extent in clinical residency.


There will likely be relevant triangulation with two other books I've cited before.

"Evolutionary mismatch" stuff.


No shortage of apps out there these days.

Click to enlarge for full-size image

How much of this is "for entertainment purposes only" remains a concern. I hope to find some good vetting in Dr. Walker's book.

Googling "smartphone sleep apps" readily turns up a good bit of stuff. e.g.,
Overview of smartphone applications for sleep analysis


To review and assess the current selection of sleep analysis smartphone applications (apps) available for download.

The iOS and Google Play mobile app store were searched for sleep analysis apps targeted for consumer use. Alarm clock, sleep-aid, snoring and sleep-talking recorder, fitness tracker apps, and apps geared towards health professionals were excluded. App information and features were obtained from in-store descriptions, and the app developer website.

A total of 51 unique sleep apps in both iOS and Google Play stores were included. The apps were rated 3.8/5 in both stores, and had an average price of $1.12 in the iOS store and $0.58 in the Google Play store. >65% of sleep apps report on sleep structure, including duration, time awake, and time in light/deep sleep, while reporting of REM was limited. The availability of extra features was variable, ranging from 4% to 73% of apps.

There are a variety of sleep analysis apps with a range of functionality. The apps with the most reviews from the each store are featured. Many apps provide data on sleep structure; however the algorithms are not validated by scientific literature or studies. Since patients may inquire about their sleep habits from these apps, it is necessary for physicians to be aware of the most common apps and the features offered and their limitations in order to properly counsel patients.
Interesting. Have to wonder about the study design utility there.

In general, I can just hear the docs griping about "yet more patient-generated data" expected to be reviewed and considered.


One practice known to convert a healthy new habit into a permanent way of life is exposure to your own data. Research in cardiovascular disease is a good example. If patients are given tools that can be used at home to track their improving physiological health in response to an exercise plan—such as blood pressure monitors during exercise programs, scales that log body mass index during dieting efforts, or spirometry devices that register respiratory lung capacity during attempted smoking cessation—compliance rates with rehabilitation programs increase. Follow up with those same individuals after a year or even five, and more of them have maintained their positive change in lifestyle and behavior as a consequence. When it comes to the quantified self, it’s the old adage of “seeing is believing” that ensures longer-term adherence to healthy habits.

With wearables that accurately track our slumber fast emerging, we can apply this same approach to sleep. Harnessing smartphones as a central hub to gather an individual’s health data from various sources—physical activity (such as number of steps or minutes and intensity of exercise), light exposure, temperature, heart rate, body weight, food intake, work productivity, or mood—we show each individual how their own sleep is a direct predictor of their own physical and mental health. It’s likely that, if you wore such a device, you would find out that on the nights you slept more you ate less food the next day, and of a healthy kind; felt brighter, happier, and more positive; had better relationship interactions; and accomplished more in less time at work. Moreover, you would discover that during months of the year when you were averaging more sleep, you were sick less; your weight, blood pressure, and medication use were all lower; and your relationship or marriage satisfaction, as well as sex life, were better.

Reinforced day after day, month after month, and ultimately year after year, this nudge could change many people’s sleep neglect for the better. I’m not so naïve to think it would be a radical change, but if this increased your sleep amount by just fifteen to twenty minutes each night, the science indicates that it would make a significant difference across the life span and save trillions of dollars within the global economy at the population level, to name but two benefits. It could be one of the most powerful factors in a future vision that shifts from a model of sick care (treatment), which is what we do now, to health care (prevention)—the latter aiming to stave off a need for the former. Prevention is far more efficient than treatment, and costs far less in the long run.

Going even further, what if we moved from a stance of analytics (i.e., here is your past and/or current sleep and here is your past and/or current body weight) to that of forward-looking predictalytics? To explain the term, let me go back to the smoking example. There are efforts to create predictalytics apps that start with you taking a picture of your own face with the camera of your smartphone. The app then asks you how many cigarettes you smoke on average a day. Based on scientific data that understand how smoking quantity impacts outward health features such as bags under your eyes, wrinkles, psoriasis, thinning hair, and yellowed teeth, the app predictively modifies your face on the assumption of your continued smoking, and does so at different future time points: one year, two years, five years, ten years.

The very same approach could be adopted for sleep, but at many different levels: outward appearance as well as inward brain and body health. For example, we could show individuals their increasing risk (albeit non-deterministic) of conditions such as Alzheimer’s disease or certain cancers if they continue sleeping too little. Men could see projections on how much their testicles will shrink or their testosterone level will drop should their sleep neglect continue. Similar risk predictions could be made for gains in body weight, diabetes, or immune impairment and infection.

Another example involves offering individuals a prediction of when they should or should not get their flu shot based on sleep amount in the week prior. You will recall from chapter 8 that getting four to six hours of sleep a night in the week before your flu shot means that you will produce less than half of the normal antibody response required, while seven or more hours of sleep consistently returns a powerful and comprehensive immunization response. The goal would be to unite health-care providers and hospitals with real-time updates on an individual’s sleep, week to week. Through notifications, the software will identify the optimal time for when an individual should get their flu shot to maximize vaccination success.

Not only will this markedly improve an individual’s immunity but also that of the community, through developing more effective “herd immune benefits.” Few people realize that the annual financial cost of the flu in the US is around $100 billion ($10 billion direct and $90 billion in lost work productivity). Even if this software solution decreases flu infection rates by just a small percentage, it will save hundreds of millions of dollars by way of improved immunization efficiency by reducing the cost burden on hospital services, both the inpatient and outpatient service utilization…
[Walker, op cit, pp. 329-331]


Surfing about and ran across some other topical research.

Our laboratories focus on two neurobiological problems: the mechanisms and functions of sleep, and the neural substrates of consciousness. Both problems have considerable medical implications, especially for psychiatric disorders such as depression and schizophrenia.

Research Overview
Mechanisms and functions of sleep

Sleep is a pervasive and universal behavior: it occupies a third of our life, and is present in every animal species that has been studied. It is also a fundamental behavior: even partial deprivation of sleep has serious consequences on cognition, mood, and health. All available evidence indicates that the brain needs sleep to function properly, but why this is the case remains unclear.

Our work has been informed by the conviction that the key to sleep is to be found at the intersection between the cellular and the systems level. This is why our laboratories use a combination of different approaches (from fly genetics to computer simulations) to try to understand the purpose of sleep.

The molecular/genetic approach to studying sleep includes genome-wide expression profiling in flies and rodents, with the aim to identify those genes whose expression changes in the brain in sleep relative to spontaneous wakefulness and sleep deprivation. This approach also exploits the power of Drosophila genetics. Fruit flies sleep and need sleep in much the same way that we and other mammals do. This finding has opened the way to the genetic dissection of sleep using mutant screening to identify flies that need little sleep and/or are resistant to the effects of sleep deprivation.

The efforts of many years have converged on a new hypothesis about the functions of sleep—the synaptic homeostasis hypothesis, which claims that that sleep maintains synaptic homeostasis. In essence, sleep is the price we have to pay for plasticity, and its function would be the homeostatic regulation of the total synaptic weight impinging on neurons (Tononi and Cirelli, 2003, 2006).

Neural substrates of consciousness
Understanding how brain activity gives rise to conscious experience has important implications for neuroscience, psychology, and psychiatry. Dr. Tononi has worked on this problem since the beginning of his scientific career (it was the topic of his MD dissertation) and he and his laboratory have approached consciousness in several complementary ways.

Consciousness poses two main problems. The first is understanding the conditions that determine to what extent a system has conscious experience. For instance, why do certain parts of the brain, such as the thalamocortical system, contribute directly to consciousness, and other parts, such as the cerebellum, do not? And why are we conscious during wakefulness and much less so during dreamless sleep? The second problem is understanding the conditions that determine what kind of consciousness a system has. For example, why do specific parts of the brain contribute specific qualities to our conscious experience, such as vision and audition?

To understand what consciousness is at the fundamental level, how it can be measured in a principled manner, and how and why certain parts of the brain are capable of generating it, a theoretical approach is required. The information integration theory of consciousness constitutes such an approach (Tononi, 2004)…

A bit outside the scope of my interest here. Interesting nonetheless. If you wish to ramble further afield on this riff, see this post by John Horgan.


Dr. Walker's website (independent of UC Berkeley):

Lots of cool stuff there.


Lordy. I'm never gonna get caught up on my reading.

A post on this book now up at Science Based Medicine caught my eye.
Conclusion: lots of good stuff
This book is a tour-de-force, a compendium of vital information about science, especially as it pertains to current topics in the media, and about the forces that conspire against science. We all need to know about these things. We ignore them at our peril. The book is an excellent antidote to fake news and a handy reference. It’s not easy going, but it’s well worth the effort.

More to come...