Surprise billing ban implementation

Health insurers have limitations on what providers you as the patient can see. Most of us are familiar with network providers and out-of-network providers, and the differential in payments.

Patients are careful to select in patient providers as outpatients, and they have a choice. However when hospitalized and seen by a number of providers the patient loses the option of selecting a provider.

Case in point. A patient is admitted by his PCP (in network), then requires a specialty  provider which is usually selected by the PCP.Most of the time the PCP and specialty provider belong to the same network or have an agreed common MSA, HMO or PPO.  In those instances the correct billing is automatic.  However in  cases where a network provider is not available the patient has no choice. This can happen if a patient needs surgery and the anesthesiologist is not in network, or if a patient requires X-rays, or  a critical care consultation in an intensive care unit.

Hospitals are careful to accept and join networks in which  their physicians are members.

Disputes often arise and a means to adjudicate the billing are important.

A federal judge poked at the government’s defense of a rule that is designed to help third parties resolve payment disputes between healthcare providers and insurers

Federal Judge Jeremy Kernodle heard arguments Tuesday in a case challenging the implementation of a federal law that protects consumers from surprise medical bills.  Congress in its infinite wisdom created this law to protect patients.

The No Surprises Act was a win for consumers who found themselves stuck with hefty medical bills after being caught between provider and payer pricing disputes. Patients were sometimes stuck with the remaining balance of a medical bill from an out-of-network provider with insurers paying only some — or none — of the bill. Patients were sometimes surprised by these bills after going to an in-network facility and unknowingly treated by an out-of-network clinician. 

With patients shielded from surprise bills, it places the burden on payers and providers to resolve payment disputes when an out-of-network claim arises. If they can’t come to an agreement on reimbursement, payers and providers can opt to engage in an independent dispute resolution process and turn to a third-party arbiter. Each side submits a payment amount, leaving it up to the arbiter to pick one.

Patients are usually confused and poorly prepared to chose a plan which can cover most of their health needs

Judge questions surprise billing ban implementation during court hearing | Healthcare Dive

What Happens When Doctors Can't Tell the Truth?

By Katie Herzog (with insertions by this author Gary M. Levin M.D.)

Whole areas of research are off-limits. Top physicians treat patients based on their race. An ideological 'purge' is underway in American medicine

That’s one of the lessons I have learned over the past few years as the institutions that have upheld the liberal order — our publishing houses, our universities, our schools, our non-profits, our tech companies — have embraced a Manichean ideology that divides people by identity and punishes anyone that doesn’t adhere to every aspect of that orthodoxy.  This duality creates bias and inaccuracy in scientific studies.  

I always thought that if you lived through a revolution it would be obvious to everyone. As it turns out, that’s not true. Revolutions can be bloodless, incremental and subtle. And they don’t require a strongman. They just require a sufficient number of well-positioned true believers and cowards, like those sitting in the C-suite of nearly every major institution in American life.

You see C-suite  members rarely know what is going on in the basements of their corporations, tending to observe from 50,000 feet what is happening at sea level. The higher the level, the less granular is the data.  Whether intentional deceitful or accidental the outcome can be misinformation and dangerous.

That’s one of the lessons learned over the past few years as the institutions that have upheld the liberal order — our publishing houses, our universities, our schools, our non-profits, our tech companies — have embraced a Manichean ideology that divides people by identity and punishes anyone that doesn’t adhere to every aspect of that orthodoxy.

This is wrong when it happens at a company Apple or Condé Nast. But there are sectors where the stakes of the ideological takeover are higher. Like K-12 education.The rapid explosion of communication via the internet and the digital age presents certain new challenges.

But if any area is more urgent, it is the world of medicine, where the ability to speak truthfully is quite literally a matter of life and death. Without being able to discuss reality and take intellectual risks, it’s impossible to get to the truth. No truth, no medical progress.

Doctors who are alarmed at what they are witnessing in some of the top medical schools and hospitals in the country. It was clear that this is a story that deserves to be told.  In my time (that dates me) scientific research was a secretive secretive industry. There were fewer journals and it was common policy to be secretive about one's research.  Believe it or not I was told by a senior scientist to not discuss our work for fear it would give advantage to our 'competitors'.

There is significant competition for grants, awards, the number of articles one had published and the Nobel Prize.  It took considerable time to do research, write the results and get it published in a reputable peer reviewed journal.  At times this can consume several years and require resubmission. At times the research scientist will not resubmit his article due to the effort. He/She may decide to submit to a lesser known journal as an alternative.

Benefits of Peer-Reviewed Literature

Peer-review process ensures that the quality of the research and validity of the findings are high.

Information on highly-detailed subject matter and complex analyses  

Easy to search through millions of articles with online databases.

Limitations of Peer-Reviewed Literature

Highly-detailed and complex analyses may be irrelevant for users who are simply searching for descriptive statistics and basic measures of public health

May require a subscription to journals or databases to access articles (can be costly for individuals, although many universities and other organizations provide access to students and faculty)

In 2022, this literature is easily accessed in Pubmed, Medline, or Google Scholar. Previously, non-scientists were not aware of Pubmed or Medline, both of which are hosted by the National Institute of Health and its subsidiary National Library of Medicine.

The categories of literature range from basic sciences (such as chemistry, physics, organic chemistry to clinical articles organized by medical or organ specificity.  There are also review articles which summarize advances in each category. These articles are not about original articles and are written by experts in each category.

Articles published in media such as news sites, new media and social media are often not researched adequately.

The review committee for each journal is the GATEKEEPER. (According to Urban Dictionary, gatekeeping is defined as, "when someone takes it upon themselves to decide who does or does not have access or rights to a community or identity". Essentially, gatekeeping is an ongoing practice that a hierarchy of power within the community and further excludes others.One cannot overemphasize the importance of the editorial advisory board.) (more about this later)

In this age of accelerated knowledge gain, communication and a control mechanisms which were overloaded by the COVID pandemic an atmosphere of anxiety and fear was rampant among the public.  Social media added to the chaos because anyone can publish fake news or misinformation.  Most posts do not include references.  

It is the social media author's responsibility to provide this in their post. A failure to do so is akin to. yelling "FIRE" in a crowded theater.  

Transparency and informed patient consent have become a  foundational part of healthcare.

Some journals publish article on the internet, which are open access.

PLOS Medicine   is a nonprofit, Open Access publisher empowering researchers to accelerate progress in science and medicine by leading a transformation in research communication.

https://www.thefp.com/p/what-happens-when-doctors-cant-speak

California has plenty of anti-COVID drugs, but few prescriptions -

“Why are doctors still so afraid to [prescribe] Paxlovid,” tweeted Dr. Purvi Parikh, an infectious disease expert and clinical assistant professor at New York University Grossman School of Medicine.

Public health sites, newspapers, social media are all espousing the lack of enthusiasm of providers to recommend  drugs which include pills such as Paxlovid

What these sources are not telling you are the possible serious complications which can occur with Paxlovid or Molnupiravir.  It has been shown these molecular agents can cause mutagenesis creating unknown variants which may be cardiotoxic, causing heart dysfunction, and even death.  Public health studies and statistics are misleading as the risk factors are only probabilities, and not absolutes.  There is no predictability of adverse occurrences

Although all these sources emphasize the drugs are free and widely available,  officials say some doctors are not prescribing them as much as they should. Paxlovid and another oral medication known as molnupiravir.

Public health sites argue, “Many of our hospitals across the state are reaching capacity — if they aren’t there already — and one of the ways we can reduce admissions is by treating individuals who have COVID-19,” Dr. Tomás Aragón, the California public health director and health officer, said in a statement. “Unlike previous years, people now have safe and effective treatment options that can prevent serious disease, reduce hospitalization and may also lower the risk of long COVID-19 symptoms.”

Rate of bivalent boosters in population over 65 yrs

Much of the online reporting is duplicated verbatim from the CDC and/or WHO posts.  They basically are parroting (plagiarising information from National sources.

Physicians usually do not accept isolated studies and prefer to source peer reviewed articles from physician scientists in reputable journals, such as the Lancet, New England Journal of Medicine or Infectious Disease Journals. Much of what is published by conventional media are not adequately resourced by authors in a rush to be the first to publish  news worthy information even if it is not correct.

Should Physicians prescribe Paxlovid ?  There is no absolute answer, because it depends upon the severity, the age, presence of other chronic conditions, such as chronic kidney disease and the presence of immunocompromise.   

mRNA vaccines and treatments should not be used lightly or without a careful history and severity of the illness.

Data snapshot: Covid-19 bivalent booster uptake winners and losers among seniors. Comments from Jeremy Faust MD

Consult with your physician, before going to a CVS, RiteAid, of Walmart.

California has plenty of anti-COVID drugs, but few prescriptions - Los Angeles Times

Hope In The Post-Pandemic World. Part III

“Success in creating AI would be the biggest event in human history. Unfortunately, it might also be the last, unless we learn how to avoid the risks.”

Stephen Hawking, British theoretical physicist

Andrew Chang MD completes his synopsis of AI in the Era of Covid 19

The most obvious effects of the pandemic was the huge growth of telemedicine for clinicians.  AI will be much more difficult with many more failures than success, much like the beginning of Space-X and the Falcon rockets.  Nevertheless iterative engineering will ultimately succeed.

We conclude this series on the future of artificial intelligence in healthcare with a discussion on the more distant future of artificial intelligence. In our struggle against this menacing pandemic, we can look at the future with optimism and idealism, and with artificial intelligence as one of our essential resources in our portfolio.

Significant needs and advances for AI in medicine in the coming decades will mandate us to understand the potential, limitations, and perhaps dangers of this resource.

First, means of decreasing the human burden of labeling medical images will be in the form of innovations in artificial intelligence such as few shots learning and generative adversarial networks that can enable more automated interpretation in the future.

Second, there need to be AI systems that can perform real-time AI. For this to occur, AI architectures will need to be even more robust and will need to include AI tools such as anytime algorithms, decision-theoretic meta-reasoning, and reflective architecture. These new AI tools will also need to incorporate the nuances of complexity and chaos theory as biomedical phenomena often have complex rather than complicated elements.

The entire learning portfolio will need to be explored and orchestrated for biomedical work: transfer learning, unsupervised and self-supervised learning, predictive learning, apprenticeship learning, reinforcement learning, and other types of learning to come in the future.

Digital twins at the individual and population levels and federated learning of all health systems at the international scale are now part of healthcare.

Cognitive elements of artificial intelligence such as 1) Joseph Voss’ cognitive architecture (declarative and procedure learning and memory, perception, action selection, etc), 2) Geoff Hinton’s “capsule networks”, or 3) Jeff Hawkins’ “reference frames” described in his book A Thousand Brains: A New Theory of Intelligence, will need to be increasingly a broad motif in artificial intelligence in medicine and healthcare that will incorporate the insights, intuition, and intelligence of our clinicians. The phrase “artificial intelligence in medicine or healthcare” will no longer be used as it was decades before.

The future of artificial intelligence in healthcare and many other topics will be discussed at our in-person AIMed Global Summit, currently being rescheduled to a later date this year to navigate around the pandemic. An exciting final session will be on the future of artificial intelligence in healthcare including its role in digital twins, extended reality, and federated learning. We will see each other in the near future. Find more information here.

Hope for the post-pandemic world (part II) | MI10

AI is shining new light in medicine and most other industries, first the industrial revolution, next the digital revolution, and now machine learning and the metaverse.  The tide is coming in.

There will be exciting developments coupled to artificial intelligence for diagnosis and treatment of medical conditions during the remainder of this decade. For instance, there is exciting work on pushing AI “peripherally” to devices – even at the microprocessor level. This artificial intelligence of things, or AIoT, provides a portfolio of “intelligent” devices for the future of chronic disease management as well as population health strategies. In short, AI in healthcare will be in two directions: a centralized cloud for analytics and concomitantly a peripheral network with AI embedded in many devices and sensors. This will be the AI equivalent of a brain and peripheral nervous system.

In addition, the limitations and nuances of existing electronic medical records in their current state demands a disruptive technology in the future. A promising technology is graph and hypergraph databases coupled with knowledge graphs to create a paradigm shift in how electronic medical records are structured and curated. Federated learning consists of edge devices with local data that can train their own copy of the model from a central server, and only the parameters/weights from these models (but not the data) are sent to the global model. Multimodal AI, such as combining perception and linguistic capabilities of machines, can increase the potential for AI to deal with the complexities of healthcare.

In the area of medical education and clinical training, adding an AI dimension to extended reality can be termed intelligent reality. Along with this virtualization of clinical medicine and healthcare can be AI imbued in the virtual twin concept for both the patient as well as the health system. All of this demand for artificial intelligence will warrant the availability of quantum computing. For AI experts, there will be an increasingly dire need for more talent, especially at the PhD level, to work in healthcare, but an escalating amount of automated machine learning will be accessible.

In addition, AI alone in medicine is not going to make an impact long term unless it is applied “intelligently” with human clinician insight and intuition to render it truly meaningful.  For the clinicians, adoption will need to be accelerated to accommodate the technology that is available. A small cohort of clinicians will need to be champions of AI by learning a minimal amount of knowledge to be able to be conversant with a data scientist. Creative uses of AI in the future can include embedding knowledge into the EHR while gaining continuing medical education credits. The ethical and legal aspects of healthcare AI continue to be widely and publicly discussed and debated.

Current State of the Best AI Healthcare Companies

The Future of Post-Pandemic Healthcare

Hope for the post-pandemic world (part II) | MI10

Hope for the post-pandemic world (part I) | MI10

Hope for the post-pandemic world (part I)

“Historically, pandemics have forced humans to break with the past and imagine their world anew. This one is no different. It is a portal, a gateway between one world and the next. We can choose to walk through it, dragging the carcasses of our prejudice and hatred, our avarice, our data banks and dead ideas, our dead rivers and smoky skies behind us. Or we can walk through lightly, with little luggage, ready to imagine another world. And ready to fight for it.”

Arundhati Roy, author and activist

This pandemic has wreaked havoc in healthcare, but the human spirit yearns for hope with each global catastrophe.

As we turn to a new year, it is a good opportunity to reflect on the current state of artificial intelligence in healthcare as well as future possibilities of artificial intelligence for health and disease. Part I of this series will highlight the current state of artificial intelligence and the following two weeks will be on the near future (this decade) and then future (beyond this decade) aspects of AI in healthcare.

Data science, machine and deep learning, artificial intelligence and a panoply of technological tools have had an impact on medicine and healthcare in several domains, especially in medical imaging and decision support. As the COVID-19 pandemic demonstrated, however, these tools have not been as successful as clinicians had hoped. This observation is probably more about deficiencies in healthcare data, databases, and information technology infrastructure than it is for AI itself. Despite this observation, expectations remain high that AI and its technological tools will deliver in the long term.

An impressive portfolio of technological tools are now available (or coming soon) in the domain of artificial intelligence in medicine. By far the most mature appears to be deep learning in the form of convolutional neural networks (CNN) in medical imaging. The Cambrian explosion of CNN tools have made progress in static imaging, but are now starting to make inroads into moving images such as ultrasound studies, endoscopic imaging, and even echocardiograms.

Both machine and deep learning have also made progress in electronic medical records – in projects on readmission criteria or decision support – but these have not been nearly as productive as medical imaging due to the records being fragmented in location and complex in nature.

In addition, there is promise in the area of drug design or repurposing in treatment for cancer patients and even for COVID-19 patients during the pandemic as a result of machine and deep learning, especially with protein structure determination based on genomic sequencing.

There are other exciting areas for artificial intelligence at present as we head into the future decades. Natural language processing (NLP) capabilities with transformer architectures such as the generative pre-trained transformer 3 (GPT-3) have started to be considered for its deployment in healthcare. This technological tool of NLP continues to advance at an exponential pace.

Unsupervised learning also holds great promise for discovery of new phenotypic expressions of disease subtypes and treatment responses.

Lastly, healthcare is starting to embrace an older AI technology of robotic process automation (RPA) for administrative tasks that can be automated by algorithms rather than completed by humans.

For data scientists, this past decade has been a journey into healthcare with mixed dividends. While the aspiration to help improve patients’ lives and/or create a viable business venture was a driving force for artificial intelligence experts, the nuances of access to healthcare data and inadequacies of databases was a deterrent for some. For clinicians at all levels of education and training as well as practice, there is an escalating need to learn about the basics of AI as it is becoming more evident that those clinicians who understand AI will have a growing advantage over those who do not.

Lastly, the myriad of issues and challenges in ethical, legal, regulatory, and financial domains focused on AI technology usually have a linear trajectory whereas emerging and disruptive AI technologies have mostly an exponential trajectory; the mismatch of these two curves creates both challenges and opportunities.

by Anthony Chang

Hope for the post-pandemic world (part I) | MI10

Precision Medicine, Use of Cell Therapy

Scientists said that without the treatment, which came after chemotherapy and an initial bone marrow transplant failed to clear her cancer, her only next step would have been palliative care

T-cells are a type of white blood cell which move around the body to find and destroy defective cells. Alyssa, who was diagnosed with T-cell acute lymphoblastic leukaemia (T-ALL) in 2021, was given all the conventional treatments including chemotherapy and a bone marrow transplant, but the disease returned.

She then became the first patient enrolled onto a new clinical trial, funded by the Medical Research Council, during which she was given universal CAR (Chimeric Antigen Receptor) T-cells that had been pre-manufactured from a healthy volunteer donor in May this year. The researchers described base-editing as chemically converting letters of the DNA code which carry instructions for a specific protein.

The edited CAR T-cells can be given to a patient so that they quickly find and destroy T-cells in the body, including cancerous ones, after which the person can have a bone marrow transplant to restore their depleted immune system. Twenty-eight days after being given the treatment, Alyssa was in remission, researchers said, and was able to have a second bone marrow transplant.

Alyssa received the treatment at Great Ormond Street (Image: PA)

She is said to be “doing well at home” as she recovers and continues with follow-up monitoring at GOSH. It is hoped the research, due to be presented for the first time at the American Society of Haematology annual meeting in New Orleans in the US this weekend, could lead to new treatments and “ultimately better futures for sick children”.

Scientists aim to recruit up to 10 patients who have T-cell leukaemia and have exhausted all conventional options for the clinical trial into the new treatment. Medics at GOSH hope that if it is successful it can be offered to children earlier in their treatment when they are less sick and that it can be used for other types of leukaemia in future.

Girl, 13, ‘leukaemia-free’ after world-first use of cell engineering therapy - Wales Online: 

Artificial intelligence and metaverse: future implications for clinical medicine and healthcare | MI10

“How are artificial intelligence and metaverse related?” Or are they?

Metaverse

Metaverse is a convergence of the real and virtual worlds made possible with technologies of extended reality (augmented and virtual types), artificial intelligence, and blockchain. The origin of metaverse is from the 1992 science fiction novel Snow Crash in which the terms “meta” and “universe” are combined.  The metaverse is, in short, an immersive virtual world (VR, AR, and even social media) that can accommodate a person to be a persona in a myriad of networks. Both augmented reality and virtual reality require a binocular headset which allows a 3D stereoscopic image. It also requires considerable computing power  with a dedicated video graphics card.

Artificial intelligence and metaverse

Artificial intelligence in the form of self-supervised learning will most likely play key roles in the portfolio of metaverse architectural elements:

Language

The convening of players in the metaverse will rely heavily on language processing, so artificial intelligence in the form of natural language processing will be extremely useful for this element.

Avatars

The players are represented by avatars, which are essentially 2D and 3D images created by artificial intelligence. As the user experience is a key part of the metaverse, artificial intelligence will be vital to improve the overall experience.

Data

The metaverse is also supported by data of all types in the players. The curation and management of data will be enabled by artificial intelligence in the form of machine and deep learning.

The potential of metaverse use in clinical medicine and healthcare is virtually (excuse the unintended pun) limitless: medical education, clinical training, patient education, and performing procedures.

Artificial intelligence and metaverse: future implications for clinical medicine and healthcare | MI10

Statiscal Methods in Clinical Medicine, or What to Believe ? Bayes’ Theorem

The Bayesian vs Frequentist statistical schools

Bayesian and Frequentist statistics are two major competing philosophies in statistical analysis. In the former, one uses prior knowledge (which can be subjective and is therefore a main source of criticism) to derive future events. In the latter, probabilities are based on observations and therefore ignore the prior information. In other words, the Bayesian advocate updates beliefs based on new data and is content with knowledge evolving over time. The more “objective” Frequentist, on the other hand, considers solely the frequency of occurrence of the outcome of the event. In spite of this fundamental difference, there seems to be a rapprochement between these two statistical schools in the current artificial intelligence milieu.

The Medical Test Paradox

This paradox relates to the observation that an accurate test is not always as predictive of disease as one would think. An example to illustrate this paradox is as follows:

If a person tested positive for COVID-19 in a population that has prevalence of 1% for the infection, and the sensitivity and specificity are 90% and 91% respectively, how many who tested positive actually have the disease?

After all the calculations, it may surprise some that only 1 in 11 who tested positive actually have COVID-19. If the prevalence is much higher at 10%, then the chance of actually having the disease in those who tested positive is much higher (around 50%). Of note, the real world sensitivity of the COVID-19 PCR test is only around 80%, so multiple tests are necessary to increase the positive predictive value.

“By updating our initial beliefs with objective new information, we get a new and improved belief.”

Sharon Bertsch McGrayne in The Theory That Would Not Die

Thomas Bayes, the eponymous Presbyterian minister of the renowned theorem, first introduced his mathematical expression close to 300 year ago. This Bayesian approach is the mathematical formulation of the concept that one can continually update an initial belief about data with new data and evidence. The recent surge in computational power and machine learning with one of its popular methodologies (“naive” Bayes) has perhaps reinvigorated this centuries-old theorem and its theoretical framework of prior and posterior probabilities.Both statistical schools are essential in clinical medicine, so perhaps we should leverage the advantages of both of these methodologies while mitigating the relative weaknesses of either.

 by Anthony Chang M.D.

Bayes’ Theorem and its statistical inference | MI10

Elon Musk's Neuralink could begin human testing in six months |

Readers are cautioned this article is facetious and intended only for humorous purposes.  It reflects upon current trends in research, informed consent, and the need for diversity in clinical studies and machine learning. It also reflects upon the use of social media as a marketing tool, using common phraseology on blogs, and social media websites.

Get on the waiting list today.  This offer may expire, there are only 10 positions 

available,  Hispanic 1, People of color 3 Caucasian 4, Asian 2 That makes 10. The optional category may be added later (Native American, Native Australian, Other Indigenous people ie, Brazilian, Mexican.  These must be included for accuracy and a nonbiased study.

Elon Musk is making promises (he likely can't keep) again.

The billionaire, who claimed Tesla's Cybertruck would begin production this year (spoiler alert: it didn’t) and who also proclaimed he’d make his own smartphone if he had to (spoiler alert: he probably won’t), has now made perhaps his loftiest business claim yet. Neuralink, Musk's biotech company that specializes in making brain chips to restore functionality to disabled bodies, will reportedly begin testing on human subjects soon.

As reported by Bloomberg, Musk made the statement in a nearly three-hour-long Neuralink recruitment event on Wednesday, the entirety of which can be viewed on YouTube. During the event, Musk intimated that human trials could begin in the next six months pending approval from the U.S. Food and Drug Administration for the device, which is roughly the size of a small stack of coins and would be implanted into the brain by a surgery-performing robot. 

Once implanted, the device would purportedly allow the brain to wirelessly interface with a computer, though Musk said the company is also working on devices to restore vision to the blind and movement to those with paralysis.

Musk even said he’d get one implanted in himself eventually.

Be sure you take an Advil prior to enrolling.

Elon Musk's Neuralink could begin human testing in six months | Mashable

CHD Files Motion to Prevent California From Punishing Doctors for COVID ‘Misinformation’ Until Lawsuit Is Settled •

Mission

The mission of the Medical Board of California is to protect health care consumers through the proper licensing and regulation of physicians and surgeons and certain allied health care professionals and through the vigorous, objective enforcement of the Medical Practice Act, and to promote access to quality medical care through the Board's licensing and regulatory functions

Regulatory bodies need regulation themselves.  There is no means to calibrate and/or suppress some knee jerk regulations that are obsolete, premature, or just outright ill  conceived.

Take telehealth for instance. Prior to 2020 the use of telehealth was suppressed by Medicare and payors because they posited it would drive up the cost of healthcare and also lead to a decrease in quality of care.  This decision was a subjective decision and without merit as there were no pilot studies to disprove their theory.  One year later telehealth was in full swing due to the overwhelming COVID 19 pandemic. Telehealth became the first line of defense by reducing exposure and transmissibility of COVID19, It's rapid acceptance was not so much about an objective decision, but by government edict, Medicare and Private health plans following suit. Medical boards had to back pedal quickly to prevent the healthcare system from self destructing 

Two years later, after the Pandemic peaked telehealth was in use,  accepted by the majority of physicians and patients.  

In a parallel world Medical Boards attempted to regulate free speach by censoring physicians posts and others about vaccinations. treatments and side effects of the virus and the vaccines. Some physicians were threatened and had their medical licenses suspended without due process.  The medical landscape, research and studies were fluid with recommendations changing monthly and at times weekly,

California Assembly Bill 2098 (AB 2098), signed into law on Sept. 30, subjects the state’s doctors to discipline — including the suspension of their medical licenses — for sharing “misinformation” or “disinformation” about COVID-19 with their patients.

According to the motion:

“AB 2098 prohibits physicians from conveying information and advice to their patients about COVID-19, which the State of California believes to be inconsistent with the prevailing opinions of the U.S. public health authorities and the majority of the medical community.

“However, if the pandemic has taught the world anything, it teaches that the views and edicts of the U.S. public health and medical authorities have changed, sometimes quickly, dramatically, and often inconsistently.”

The law is set to take effect Jan. 1, 2023. A hearing on the motion is scheduled for Jan. 17, 2023.

Clearly misinformation and information can rapidly be interchanged.

The dust has not yet settled. Vaccines are changing as fast as the virus is mutating.

The President,  CDC, and  NIH rendered conflicting opinions on masking, vaccinations, distancing as well as risk factors for vaccinations. Several authorities on infectious diseases became celebrities overnite on some television news productions  Anthony Fauci, MD (a well known and previously respected physician scientist) rolled his eyes up when President Trump made some outlandish statements about hydroxychloroquine tablets to prevent or treat Covid 19.

CHD Files Motion to Prevent California From Punishing Doctors for COVID ‘Misinformation’ Until Lawsuit Is Settled • Children's Health Defense

Amazon’s Creep Into Health Care Has Some Experts Spooked

Amazon recently said it is losing billions of dollars on Alexa and Echo.  Amazon seems to have lost it's way since Mr. Bezos has been building rockets....that too seems to have bogged down.

The story about Echo is they planned to monetize it by having users purchase items from the Amazon Warehouse.  They saw it as a loss leader.  Amazon claims they sell the echo devices at cost. Meanwhile, the cost of server operations, networks, and personnel is a considerable sum.  90% of users don't use it except to find out the weather, date, or their horoscope.  The first couple of times I used it was fascinating. Now we know more about machine learning and natural language processing it does not seem so magical anymore.  Perhaps setting your thermostat, turning the lights on and off as well as opening up the garage door will entertain us for a while more.  Amazon, much to its profit incentive also licenses its AI to other device manufacturers such as Sonos using the Program Materials License Agreement.

Favorite Alexa gadgets, from speakers to smart clocks.

The networking seems almost endless.  However, ordering and paying for products from a fancy chatbot seems to turn people off.

Amazon bought and operates Pillpak. Amazon bought PillPack for a reported $1 billion in cash.

Amazon also parlayed it into Amazon Pharmacy, purchasing Pillpak from Parker who co-founded PillPack in 2013 along with Chief Product Officer Elliot Cohen. Parker's family operated a mom-and-pop pharmacy, and, while studying to become a pharmacist, he and Cohen developed the idea for a startup that would make it easier for people to buy prescription drugs online and manage their medications. 

The Amazon logo has drifted into televisions, health care, rocket ships, and now is planning an entry into telehealth.  AWS must have empty drives in their cloud space and wants to fill them up with telehealth.   Anyone for an AMAZON EHR?

Using the tech giant’s new telehealth service will mean trusting it with your private data. And for good reason.

This time, it’s aiming for the low-hanging fruit: telehealth, which exploded in popularity during the pandemic. On November 15, Amazon announced the launch of its own telehealth platform, called Amazon Clinic. The service, to roll out in 32 US states, will connect users to health providers to help treat over 20 common conditions, including allergies, acne, and dandruff.  The problem is they are too late for the party. There is already a multitude of successful telehealth companies with an installed base of users. Hospitals and health providers are slow to adopt new companies that have no track record.

The concept is simple: The patient will select their condition, fill out a questionnaire, and Amazon will connect them with a doctor to get a treatment plan. The scheme does not accept insurance; the cost of seeing a doctor will be around that of the average copay for a doctor’s visit, the announcement says: “At Amazon, we want to make it dramatically easier for people to get and stay healthy.”

It’s also seemingly another move by the tech giant to know every last detail about your life—even down to whether you’re suffering from erectile dysfunction (one of the conditions that Amazon Clinic will cover). Yet given that Amazon doesn’t have the squeakiest track record when it comes to protecting data, handing the company the keys to people’s intimate health information raises red flags for privacy experts.

If this feels familiar, it’s because we’ve been here before. The launch of this new service comes hot on the heels of Amazon’s takeover of One Medical, a US company described as a “Netflix-for-healthcare subscription” with around 800,000 members. The acquisition proved controversial due to concerns about patient data privacy mostly centered on the simple fact that Amazon would have access to the data. (When news of the $3.9 billion deal broke in July, it prompted protests outside One Medical’s headquarters in San Francisco.) 

Amazon Care, a telehealth service Amazon piloted among its employees and then rolled out to other customers, shows how things can go wrong. Its shutdown was announced a few months ago, with the senior vice president in charge of the program, Neil Lindsay, writing in an internal memo Amazon shared with WIRED: “Although our enrolled members have loved many aspects of Amazon Care, it is not a complete enough offering for the large enterprise customers we have been targeting and wasn’t going to work long-term.”  

But it was plagued by other problems, too. A Washington Post investigation alleged that moving at top speed and efficiency sometimes conflicted with best practices in medicine: For example, nurses were asked to process patient blood samples in their personal cars, the paper reported, and to store and dispose of medical supplies at home, which they protested. (Amazon told the Post that they could not find records of complaints about these matters.)  

“Amazon Care followed common practices for in-home care and knows them to be safe and appropriate,” Smith told WIRED. “For example, Amazon Care clinicians were always equipped with Stericycle medical waste return equipment to properly and securely return or dispose of supplies.” 

For Sharon, a big concern is how reliant we risk becoming on big companies as mediators of fundamental public needs. “This is a dangerous situation—that we would become dependent on a handful of private actors for the distribution of very basic goods, like health, or education, or public services,” she says. For instance, as these companies increasingly fund and perform their own research, it’s possible they could influence how the research agenda is set. That could be a problem if tech founders’ penchant for wanting to live forever results in a focus on funding longevity research over, say, cancer treatments.

At the very least, Amazon Clinic will be bound by HIPAA, the Health Insurance Portability and Accountability Act, which means individual patient records will be protected as soon as a person begins a process with a health care provider. But all the information you provide prior to this—for instance while searching for a doctor—falls outside of the purview of HIPAA, and is technically open for Amazon to gobble up,

Covid is no longer mainly a pandemic of the unvaccinated. Here’s why. - The Washington Post

It’s no longer a pandemic of the unvaccinated

White House Covid-19 Response Coordinator Ashish Jha speaks alongside Anthony Fauci, Director of the National Institute of Allergy and Infectious Diseases, during a press briefing at the White House on Tuesday. (AP Photo/Patrick Semansky)

For the first time, a majority of Americans dying from the coronavirus received at least the primary series of the vaccine.

Fifty-eight percent of coronavirus deaths in August were people who were vaccinated or boosted, according to an analysis conducted for The Health 202 by Cynthia Cox, vice president at the Kaiser Family Foundation.

It’s a continuation of a troubling trend that has emerged over the past year. As vaccination rates have increased and new variants appeared, the share of deaths of people who were vaccinated has been steadily rising. In September 2021, vaccinated people made up just 23 percent of coronavirus fatalities. In January and February this year, it was up to 42 percent, per our colleagues Fenit Nirappil and Dan Keating.

“We can no longer say this is a pandemic of the unvaccinated,” Cox told The Health 202.

Being unvaccinated is still a major risk factor for dying from covid-19. But efficacy wanes over time, and an analysis out last week from the Centers for Disease Control and Prevention highlights the need to get regular booster shots to keep one’s risk of death from the coronavirus low, especially for the elderly.

Anthony Fauci, the nation’s preeminent infectious-disease expert, used his last White House briefing yesterday ahead of his December retirement to urge Americans to get the recently authorized omicron-specific boosters.

“The final message I give you from this podium is that please, for your own safety, for that of your family, get your updated covid-19 shot as soon as you’re eligible,” he said.

White House press secretary Karine Jean-Pierre:

Ratio shift

Cox, like many experts, says she’s not surprised by the ratio shift. There are a few reasons:

At this point in the pandemic, a large majority of Americans have received at least their primary series of coronavirus vaccines, so it makes sense that vaccinated people are making up a greater share of fatalities.

• Individuals at greatest risk of dying from a coronavirus infection, such as the elderly, are also more likely to have received the shots.
• Vaccines lose potency against the virus over time and variants arise that are better able to resist the vaccines, so continued boosters are needed to continue to prevent illness and death.

The BA.5 omicron subvariant became dominant in July and consistently accounted for the majority of new coronavirus infections across the United States until earlier this month. The highly transmissible strain fueled a surge of new infections, reinfections and hospitalizations throughout the summer.

Boosters

It’s still true that vaccinated groups are at a lower risk of dying from a covid-19 infection than the unvaccinated when the data is adjusted for age. An analysis released by the CDC last week underscores the protection that additional booster shots offer against severe illness and death as immunity wanes. 

Let’s take a look at deaths in August, when the highly contagious BA.5 variant reached its peak:

• That month, unvaccinated people aged 6 months and older died at about six times the rate of those who had received their primary series of shots.
• People with one booster dose were even better protected. Unvaccinated people over the age of 5 had about 8 times the risk of dying from a coronavirus infection than those who received a booster shot.
• Among individuals who were eligible to receive additional booster shots, the gap is even more striking. Unvaccinated people 50 and up had 12 times the risk of dying from covid-19 than adults the same age with two or more booster doses.

David French, senior editor for the Dispatch:

Covid is no longer mainly a pandemic of the unvaccinated. Here’s why. - The Washington Post