Illegal Fentanyl is the scourge of overdoses by opioids

Contrary to media sources prescriptions for opioids (codeine, hydrocodone) is not the main cause of overdoses in the United States.

Illegal sources of fentanyl (DEA). 

Currently, China remains the primary source of fentanyl and fentanyl-related substances trafficked through international mail and express consignment operations environment, as well as the main source for all fentanyl-related substances trafficked into the United States. Seizures of fentanyl sourced from China average less than one kilogram in weight, and often test above 90 percent concentration of pure fentanyl.

This is how Fentanyl is causing so many deaths.  

Fifty times stronger than heroin, one hundred times stronger than morphine, fentanyl is very dangerous, a quantity like 2 grains of salt can be lethal.

A Tavares, Florida police officer has her coworkers to thank for taking decisive, lifesaving action when she overdosed ...from inhaling fentanyl powder accidentally when doing a traffic stop.

 It was a windy day and even though the officer wore protective gloves when handling the plastic containers of fentanyl powder, it is thought that she inhaled some of the fentanyl powder when the wind blew it into the air.  Fortunately her fellow officers had Narcan (a powerful antidote) readily available. Narcan is administered as a nasal spray.

Public health measures such as:

Establishing a leave behind program enables first responders to leave naloxone kits with the family, friends, or bystanders at the scene of a non-fatal overdose. Survivors are at high risk for repeated overdoses, providing naloxone to these individuals and their loved ones is especially important.

VIDEO: Bodycam Shows Officer Overdosing After Fentanyl Exposure, Fellow Officers Saving Her Life With NARCAN: 

A Comparison of Nurse Practitioners, Physician Assistants, and Primary Care Physicians' Patterns of Practice and Quality of Care in Health Centers - PubMed

Who was that person in the white coat that saw me today in the clinic? Should I have called them 'Doctor'??

For the last several decades what we are calling mid-level practitioners. have been present in a variety of settings.  Various titles have been assigned to them dependent upon which route they took to become mid-level practitioners.  Nurse practitioner, physician assistant.  It is not so straight forward to telling you how advanced their training has been.

M.D.s and D.O.s normally have three or four years of undergraduate degrees leading to a bachelor's degree, followed by four years of medical school and then postgraduate training in a general or specialty area.  Over time this training has evolved and become longer.  Mid-level health personnel may have previously been R.N.s or taken a route to become a physician assistant in special programs. Some P.A.s may also become 'specialty PAs' serving as assistants to surgeons as extenders.

It becomes obvious a long white coat is no longer a beacon called 'doctor'.

This phenomenon has become more prominent due to organizations such as the. Veterans Administration Health System, the Department of Defense and some managed care institutions.  The initial impetus was to increase accessibiliy when physicians are in short supply and/or over worked.  A secondary gain has been some cost savings.  

In all instances the mid level practtiner reports to a licensed physician. They do not practice independently.

: Under the Affordable Care Act, the number and capacity of community health centers (HCs) is growing. Although the majority of HC care is provided by primary care physicians (PCMDs), a growing proportion is delivered by nurse practitioners (NPs) and physician assistants (PAs); yet, little is known about how these clinicians' care compares in this setting.  

 Primary analyses included 23,704 patient visits to 1139 practitioners-a sample representing approximately 30 million patient visits to HCs in the United States.

Measures: We examined 9 patient-level outcomes: 3 quality indicators, 4 service utilization measures, and 2 referral pattern measures.

Results: On 7 of the 9 outcomes studied, no statistically significant differences were detected in NP or PA care compared with PCMD care. On the remaining outcomes, visits to NPs were more likely to receive recommended smoking cessation counseling and more health education/counseling services than visits to PCMDs (P≤0.05). Visits to PAs also received more health education/counseling services than visits to PCMDs (P≤0.01; design-based model only).

Conclusions: Across the outcomes studied, results suggest that NP and PA care were largely comparable to PCMD care in HCs.

A Comparison of Nurse Practitioners, Physician Assistants, and Primary Care Physicians' Patterns of Practice and Quality of Care in Health Centers - PubMed

Practice Environment and Workforce Outcomes of Nurse Practitioners in Community Health Centers

A survey of implicit bias training in physician assistant and nurse practitioner postgraduate fellowship/residency programs

The development of a visual dashboard report to assess physician assistant and nurse practitioner financial and clinical productivity

Factors associated with federally qualified health center financial performance

This study. is highly biased as it only surveys in FQHMCs. (Community Health Centers).  The cohort of patients is almost 100% Medicaid, a statewide payer through a variety of managed care programs such as the Inland Empire Health Plan and Molina Care.

Both of these entities are not for profit plans, paid for entirely by state and federal medicare funds.  These plans reimburse providers and hospitals amounts far below the usual and customary fees.  Hospitals and providers are paid barely their cost to provide services.  They could not exist without indirect subsidies by private payers.

The statistical results as to quality of care may be biased since the study is done by the entities themselves, to justify the use of mid level practitioners.

Nearly 90% of those living with long COVID have not returned to full health

The study of 988 participants conducted by APC Microbiome Ireland, an SFI research center based at University College Cork (UCC), in conjunction with Cork University Hospital (CUH) and long COVID Advocacy Ireland, provides greater insight into impact of long COVID on quality of life, mental health and physical health of people in Ireland. The study is published in HRB Open Research.

More than 2 out of 3 participants continue to experience fatigue, post-exertional malaise, palpitations, chest pain, stomach upset/nausea, memory problems, muscle pain or joint pain. The median number of long COVID symptoms reported was 8 for each person, highlighting the substantial burden of this disease. The median reported time since the initial COVID-19 infection was 12 months

Six out of every ten missed workdays

A high proportion of long COVID patients reported that they still have a moderate to severe limitation in their ability to carry out their usual daily activities. Nearly 4 of 10 people were severely limited in their ability to work and 6 of every 10 have missed workdays (at some stage) due to their long COVID symptoms. 16% of respondents were unable to work at the time of the survey due to long COVID and were receiving social welfare supports.

The survey was produced in a researcher-clinician-patient partnership involving Professor Liam O'Mahony, APC Principal Investigator and UCC Professor of Immunology, Dr. Corinna Sadlier, Consultant in Infectious Diseases at CUH, and Ms. Tanja Buwalda, long COVID sufferer and representative of "Long COVID Advocacy Ireland."

This working group included patient engagement to ensure the survey would impact patients in a targeted and meaningful way, and ultimately help inform care pathways in the treatment of long COVID.

SARS-CoV-2 infection not only impacts the lungs

Professor O'Mahony said, "This survey highlights that SARS-CoV-2 infection not only impacts the lungs but can have significant long-term effects on multiple organ systems following clearance of the acute SARS-CoV-2 infection in many Irish people who were otherwise healthy previously. The reasons why some people develop long COVID, and others do not, are still unclear. While many different biological mechanisms have been proposed, we are focusing on the role of the immune system and the microbiome in these complicated disease processes.

Dr. Corinna Sadlier said, "The study demonstrates the significant and wide-ranging impacts long COVID is having not only on physical health, but also on ability to carry out usual daily activities, return to employment and overall quality of life.Fatigue is the single most frequent symptom reported," Professor O'Mahony continued.  

Ref:

 Liam O' Mahony et al, Impact of Long COVID on health and quality of life, HRB Open Research (2022). DOI: 10.12688/hrbopenres.13516.1

Nearly 90% of those living with long COVID have not returned to full health: 

This Couple Died by Suicide After the DEA Shut Down Their Pain Doctor

“There are millions of chronic pain patients suffering just like me," Danny Elliott wrote before ending his life. "Nobody cares."

DEA, FDA, CDC often overstep their missions.  This is all to common a problem.

Many physicians should push back and be aggressive if confronted by their state medical boards, or other regulatory bodies.  Organized medicine must do more to protect patient rights to access treatment. A referral to a pain specialist may not be adequate protection.  One would think an ethical and properly trained pain medicine physician would escape algorithm care.  Then again there are other means to alleviate pain.  Suicide should not be an option.

It was a Tuesday in early November when federal agents from the Drug Enforcement Administration paid a visit to the office of Dr. David Bockoff, a chronic pain specialist in Beverly Hills. It wasn’t a Hollywood-style raid—there were no shots fired or flash-bang grenades deployed—but the agents left behind a slip of paper that, according to those close to the doctor’s patients, had consequences just as deadly as any shootout.   

On Nov. 1, the DEA suspended Bockoff’s ability to prescribe controlled substances, including powerful opioids such as fentanyl. While illicit fentanyl smuggled across the border by Mexican cartels has fueled a record surge in overdoses in recent years, doctors still use the pharmaceutical version during surgeries and for soothing the most severe types of pain. But amid efforts to shut down so-called “pill mills” and other illegal operations, advocates for pain patients say the DEA has gone too far, overcorrecting to the point that people with legitimate needs are blocked from obtaining the medication they need to live without suffering. 

Starting around 2016, a backlash to prescribing opioids began to spread across the U.S. healthcare system, sparked in part by guidance from the Centers for Disease Control and Prevention (CDC) that prompted scrutiny of patients on doses equivalent to over 90 milligrams of morphine per day. The National Committee for Quality Assurance, which develops quality metrics for the healthcare industry, has implemented its own 90 milligram threshold, and patients over that baseline count as receiving “poor care,” regardless of their dose history. In practice that means doctors have strong incentives to reduce the dosage, even for someone like Elliott, who had been taking the same prescription for years, and even if it’s not necessarily in the best interests of the patient. Since 2018, the CDC has developed an initiative called the Opioid Rapid Response Program, which is supposed to assist when doctors lose the ability to prescribe pain medication. Stephanie Rubel, a health scientist in CDC’s Injury Center who leads the program, said when the DEA visited Bockoff’s office, “a healthcare professional was onsite in case any patients arrived for their appointments.”

One of Bockoff’s patients who relied on fentanyl was Danny Elliott, a 61-year-old native of Warner Robins, Georgia.

This Couple Died by Suicide After the DEA Shut Down Their Pain Doctor

The Vaccine Confidence Project

Throughout the world confidence in the Covid vaccine varies

State of Vaccine Confidence in the EU (2022)

State of Vaccine Confidence in the EU (2022) by Country

              Download pdf

Vaccine confidence among the public and healthcare professionals is high across most populations, with some exceptions and caveats. Between 2018 and 2020, there was a large increase in public perception towards vaccines across the EU, particularly towards the seasonal influenza vaccine. Many of these 2020 gains have since been reversed. Perceptions towards the importance, safety, and effectiveness of vaccines have declined across the EU between 2020 and 2022. Across the EU, the view that vaccines are safe remains higher than 2018 levels. Yet, EU-wide changes in public perceptions towards the importance and safety of vaccines shows that strong vaccine-dependence and variability in vaccine confidence exist between countries and within sociodemographic characteristics. 

An evaluation into the differences in public confidence between over 65-year-olds and 18-34-year-olds reveals key insights into an increasing ‘vaccine confidence gap’, which needs to be addressed. The difference in vaccine confidence between 65-year-olds and 18-34-year-olds appears to be widening over time across many EU member states, with 18-34-year-olds becoming less confident between 2018 and 2022.

Vaccine confidence among healthcare professionals remains high in 2022 Above 90% of HCPs surveyed in all EU member states agree that vaccines are important. 

Above 90% of HCPs surveyed in all EU member states agree that vaccines are safe, except for France, Greece, and Austria. 

Healthcare professionals across the EU are highly likely to recommend the MMR, seasonal 

influenza, and COVID-19 vaccines to patients, though likelihood to recommend the HPV vaccine shows high variability between countries.

HCPs likelihood to recommend seasonal influenza and COVID-19 vaccines to pregnant women are generally lower than their likelihood to recommend these vaccines to other patients 

Variability in vaccine confidence exists between countries, among vaccination types, and within sociodemographic characteristics.

The age “gap” in confidence is widening between younger and older age groups   

Between 2018 and 2022, there is increasing polarisation between older and younger age groups in terms of perceptions of vaccines with over 65s becoming more confident and 18-34- year-olds growing less confident.

The seasonal influenza vaccine is the only vaccination where an inverse of this trend can be seen, where the gap between older and younger age groups is narrowing.

Research Feed — The Vaccine Confidence Project

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