#healthcare data infrastructure

[vivekguptahal]

A Data-Driven Approach to Healthcare - Brain Injury and Disease Research

Cloud adoption & data pipeline automation in healthcare

Traditionally, healthcare advancements have progressed slowly due to siloed research and delayed results. However, with cloud application modernization, all that is changing for good. A unique collaboration between life sciences organizations and digital solution providers is offering an unprecedented level of insight into managing conditions and achieving optimal patient outcomes. Cloud modernization is expanding healthcare organizations’ ability to use data pipeline automation to effectively diagnose patients.

A prime example of cloud adoption is a nonprofit research organization dedicated to biomedical research and technology. The organization has been instrumental in facilitating advances in brain injury and disease research through its launch of the first cloud-based and interactive platform that supports information and idea exchange to further progress in neuroscience research. It uses big data to promote computational innovation discovery in brain diseases.

Co-created by Hitachi and other partners, this platform is a trusted portal where clinical researchers, physicians, and organizations can collaborate on research and the validation of emerging therapeutics.

The context of merging human and artificial intelligence for analyzing health data

Medical research data is becoming siloed, diverse, and complex. To break this complexity, a robust IT infrastructure with the capacity to aggregate data across multiple studies is required along with harnessing patients’ data to improve the healthcare system.

The organization needed an interactive and scalable platform that would be capable of integrating diverse cohorts and investigators and equipped with a high computing speed that is essential in machine learning and artificial intelligence applications.

These new capabilities would empower users to gain a comprehensive understanding of signature patterns within existing and emerging large-scale datasets and to foster collaboration to promote the efficient use of the research community’s collective knowledge of brain injuries and diseases.

With time, the organization recognized that meeting these challenges would require the expertise of specialists in data pipeline automation and healthcare data solutions to meet the steep requirements of the healthcare industry. Having heard of Hitachi, the organization turned to us for our Cloud Managed Services.

Leveraging healthcare data analytics solutions to build more sophisticated infrastructure

The organization wanted to collaborate with Hitachi to upgrade the user interface and augment the platform’s experience for researchers and the virtual analytical environment to ensure secure data management.

Hitachi was able to deliver an integrated solution that encompassed each component of the build-out. This streamlined project management made the process more efficient and data-driven healthcare innovation helped to further modernize, streamline, and simplify the health diagnostic system for the research organization.

Infrastructure that enables innovation

Cloud modernization was central to helping the organization maximize value in its transformation journey and boost the lives of people. While the organization began with a vision, advances in cloud-based data management, storage, and security brought that to fruition. The interactive platform now allows the organization to leverage best practices to tap into the potency of data pipeline automation and utilization.

Hitachi’s commitment to social innovation 

For Hitachi, this project has particular resonance because it is aligned with its commitment to social innovation. To have played a role in accelerating this process and in bringing life-changing drugs and therapies to patients more quickly is always rewarding.

Discover how Hitachi is unlocking value for society with Social Innovation and Digital Transformation in Healthcare :

[epicstoriestime]

The Stargate Project: A Leap Toward AI’s Future

A transformative leap in AI, pushing the boundaries of science, healthcare, and global progress with a $500 billion investment. In January 2025, the Stargate Project was unveiled as a transformative initiative aimed at securing the United States’ leadership in the rapidly advancing field of artificial intelligence (AI). This groundbreaking venture, with a projected investment of up to $500…

[diptisinghblog]

Strategic Approaches to Healthcare Management for PGDM Graduates

[jcmarchi]

Derek Streat, CEO and Founder of DexCare – Interview Series

New Post has been published on https://thedigitalinsider.com/derek-streat-ceo-and-founder-of-dexcare-interview-series/

Derek Streat, CEO and Founder of DexCare �� Interview Series

Derek Streat, CEO and Founder of DexCare, is an experienced entrepreneur with a track record of founding and leading six venture-backed companies, four of which have achieved successful acquisitions. His ventures have included scaling businesses to over $100 million in revenue and establishing non-profits that benefit more than half of all children with kidney transplants. Streat focuses on solving large-scale, impactful problems by leveraging innovative data solutions to bring transparency and efficiency to markets, reducing costs and delivering societal benefits.

DexCare is a care orchestration platform that optimizes healthcare delivery and workforce capacity while enhancing patient convenience. It integrates with existing systems to unify data, forecast demand, allocate resources, and guide patients to the most appropriate care, delivering actionable insights and streamlined operations.

DexCare was born out of your personal journey with healthcare, specifically in helping your child access critical care. How did this experience shape your vision for DexCare, and how does it continue to influence the company’s mission today?

Fifteen years ago, my three-year-old child needed a lifesaving kidney transplant. It was an arduous journey filled with sleepless nights as my wife and I struggled to navigate a fragmented healthcare system. We watched as our little one moved between specialists, surgeries, and intensive care, ultimately receiving a transplant. Through it all, I realized just how fortunate I was to have unfettered access to care. For many Americans, that’s not the case.

Over 37% of Americans live in healthcare deserts. My own experience, combined with years of working closely with healthcare systems, revealed a clear need to bridge the access gap for everyone. In fact, not every patient needs to see a physician – they need the right care, in the right place, at the right time. And that insight led me to found DexCare, a platform designed to orchestrate where and how care is delivered. By reducing provider burnout, creating capacity, and expanding access, we aim to serve more patients effectively. Incubated at Providence, DexCare spun out in 2021 and now proudly partners with leading health systems across the country, including Texas Health Resources, Tampa General, and Piedmont Healthcare.

You’ve successfully founded several healthcare-focused companies. What specific challenges did you encounter in founding DexCare, and how did your prior ventures prepare you for launching this care orchestration platform?

From idea to prototype, to raising capital and scaling, every startup faces familiar hurdles. In healthcare, these challenges are amplified by talent wars, long sales cycles, cautious capital markets, and an ever-shifting regulatory landscape. Success demands a careful balancing act. Having founded and exited multiple companies, I’ve been in the trenches and gained firsthand insight into what it takes to build resilient teams and products capable of thriving under pressure. These lessons became essential when launching DexCare and crafting a strategy to succeed amid the complexities of healthcare.

My foray into healthcare began with Medify, an intelligence company that used NLP technology to create structured data from the vast, global repository of medical literature. The platform made a real difference for patients with rare diseases, bringing together small, scattered populations into larger groups with meaningful insights. At its peak, one in ten doctors across the U.S. relied on our knowledge base to find treatments and therapies that could make a difference for their patients. Eventually, Medify became part of Alliance Health, a leading health network.

After Medify, I began tackling a different set of challenges, focusing on how technology could directly influence clinical practice through C-SATS.

An AI-powered platform, C-SATS leveraged robotics and machine learning to evaluate surgical performance, providing surgeons with actionable insights to improve their skills and patient outcomes. This work with AI—long before today’s hype— opened my eyes to the uncharted complexities of integrating advanced technology into a high-stakes environment like healthcare. While the platform sidestepped privacy concerns by using anonymized surgical footage, it surfaced deeper issues, as surgeons were apprehensive about being credentialed based on technology, as it had direct implications for their careers and livelihoods. This experience taught me that introducing innovation in healthcare requires more than technical expertise—it demands building trust with stakeholders and proactively addressing the unintended consequences that can emerge when technology intersects with human lives.

Throughout my career, I’ve focused on dismantling systemic barriers—scarce resources, disconnected data, and inequitable access—by leveraging technology rooted in practicality, not hype. When building DexCare, I prioritized data intelligence as the cornerstone of our AI applications. And this focus ensures clean, reliable, and unified data that powers how care is orchestrated, routed, and delivered. By exposing capacity imbalances—identifying overburdened providers and underutilized resources—we’re reimagining healthcare to optimize operations and to deliver better outcomes for patients.

DexCare was incubated within the Providence Health system. Could you talk about the advantages of developing a startup from within a large healthcare organization, and how that shaped DexCare’s growth?

DexCare was born within Providence to solve a key challenge in healthcare: balancing supply and demand by leveraging existing marketing, IT, and operational infrastructure. Being built inside a health system gave us an intimate understanding of the dual challenges facing healthcare today. For organizations, it’s the constant struggle to meet growing care demands with limited resources. And for patients, it’s the frustration of finding care when and where it’s needed. This perspective uniquely positions us to empower health systems with critical infrastructure for more effective digital discovery and access, while simultaneously optimizing system capacity. And our incubation within Providence allowed us to refine the platform before scaling to health systems nationwide.

AI in healthcare has been heralded as revolutionary, but it has also faced significant hurdles. How have you seen AI evolve in healthcare over the years, and where do you think it has fallen short of its potential?

The rise of AI in healthcare has sparked both excitement and caution. While AI is becoming more mainstream, significant hurdles remain before it can transform the industry. A recent survey revealed that 96% of healthcare CIOs see AI adoption as a competitive advantage, yet integration challenges—like system interoperability and workflow alignment—often stand in the way. And without seamless integration into the daily process, clinicians, physicians, and administrators are unlikely to embrace these tools.

The crowded landscape of over 14,000 AI-focused companies adds to the complexity, making it difficult for health systems to separate hype from solutions that deliver real value. Choosing the right technology partner requires more than evaluating features—it demands solutions that integrate smoothly, enhance existing workflows, and address real-world challenges.

But the core issue isn’t just finding the next tool—it’s unlocking the potential within healthcare’s existing data. Sustainable systems depend on harmonizing data across care records, workflows, and third-party platforms. Only then can we tackle real priorities, like freeing clinicians to focus on people over paperwork and closing critical care gaps. And this is precisely where DexCare fits in.

DexCare uses AI to optimize healthcare delivery by predicting and distributing care resources. Can you walk us through how the platform’s AI works and how it has impacted care delivery at scale?

DexCare’s care orchestration platform harnesses advanced data intelligence by consolidating key inputs—scheduling, modalities, utilization, locations, and costs—to determine where, when, and how care should be accessed. Our AI not only ingests and organizes massive data sets but also dynamically aligns care delivery with patient needs. For instance, the platform categorizes content—whether it’s an article on seasonal flu, preventive care, or specialized services—and matches it to the most appropriate pathways to care, all while understanding complex taxonomies and synonyms. The result? By linking relevant content to the most suitable venues of care, the platform ensures patients are guided seamlessly to the services they need, enhancing both access and outcomes.

The results speak for themselves. DexCare enables 40% more patients to receive care using the same clinical resources, drives a 24% increase in new patient acquisition, and saves over 34,000 hours of physician time. By eliminating unnecessary steps and presenting clear, actionable choices from the start, we’re transforming patient access and operational efficiency at scale—delivering measurable improvements for patients and providers.

AI has the power to automate tasks and streamline processes, but it can also create fear around job displacement in healthcare. How do you see AI impacting the healthcare workforce, and what strategies can mitigate these concerns?

Addressing fears of job displacement in healthcare begins with clarity. AI isn’t here to replace the human touch in care delivery—it’s here to complement it. Technology, including AI, augments the capabilities of healthcare professionals, but it’s not a silver bullet for addressing the growing gap between increasing patient needs and a shrinking physician workforce.

Platforms like DexCare demonstrate how AI can be a critical tool in extending the capacity of limited healthcare resources. By intelligently balancing workforce demands, controlling costs, and optimizing capacity, AI helps health systems operate more efficiently. This not only ensures patients receive the care they need but also alleviates burdens on providers, reducing burnout and creating a more sustainable healthcare environment. It’s about building smarter, more resilient systems.

What are some of the unintended consequences you’ve observed in the implementation of AI in healthcare, particularly in terms of accountability for AI-driven mistakes? How does DexCare address these ethical challenges?

When I was at C-SATS, we used robotics and machine learning to train surgeons and to improve patient outcomes. While innovative, this approach raised important questions about privacy, consent, surgeon autonomy, and the ethical use of data. These challenges highlighted a crucial truth: implementing AI in healthcare requires rigorous, standardized policies to ensure the safe and ethical use of the technology.

In healthcare, there is no margin for error—lives are at stake. This makes it imperative to establish clear guidelines and frameworks that can serve as a ‘North Star’ to navigate uncharted legal and ethical questions. And accountability and transparency must be at the heart of AI applications in healthcare. By focusing on data integrity and designing systems to enhance, not overshadow, human decision-making, we can advance innovation responsibly while addressing the needs of the industry.

While AI offers tremendous potential for improving access to care, what steps do you think healthcare systems need to take to ensure equitable AI adoption, especially for underserved populations?

AI adoption in healthcare, especially for underserved populations, requires a focus on data fidelity, diversity, and aggregation. In an industry beset by fragmented data silos, the ability to unify and analyze information is crucial. Generative AI has the potential to create life-saving connections by integrating patient records, population health disparities, and propensity models to improve diagnosis, treatment, and care outcomes. However, these advancements depend on using bias-free datasets at scale to avoid perpetuating inequities.

Responsibility doesn’t rest solely with health systems. A unified approach is needed, starting with standardizing AI deployment at scale. Sensible, national-level regulations can ensure AI improves our collective healthcare while, at the same time, must avoid overreach that stifles innovation. Overly restrictive measures risk hampering progress, but clear guidelines on infrastructure, usage, and data governance are essential. These standards can help address bias, mitigate risks, and foster a system where AI elevates care quality for all patients, not just the privileged few.

From a founder’s perspective, what advice would you give to entrepreneurs looking to bring AI into healthcare, considering the unique regulatory and ethical challenges of the industry?

Successful entrepreneurs, particularly in healthcare, must not only challenge the status quo but also reject the notion that the system is beyond fixing. The opportunities to improve healthcare are immense, but once you dive deep into the self-imposed complexities and the hurdles the industry presents, the scale of the problems can seem overwhelming. True innovation requires resilience—the ability to confront these challenges head-on and to remain steadfast in your mission. Your vision to improve care and outcomes must always outweigh the obstacles of scaling technology.

Success in healthcare isn’t just about the technology – it’s also about aligning with the needs of patients, providers, and systems, and having the resolve to smile even when the path gets steep. My advice: Stay adaptable, embrace setbacks, and focus on building solutions that solve for immediate, real-world problems.

Looking ahead, what are the most exciting AI advancements you foresee in the next 5–10 years for healthcare, and what specific areas do you think AI will struggle to penetrate?

Predicting the future is tricky—it’s uncertain and ever-changing. With thousands of companies exploring AI from every angle, the potential is incredible, but so are the challenges. What we do know, however, is that AI is poised to fundamentally reshape how care is accessed, delivered, and experienced. One of the most exciting advancements I foresee over the horizon is truly personalized medicine—tailored treatment plans and unique therapeutic “cocktails” designed to give each patient exactly what they need to heal and thrive.

Healthcare – long hamstrung by fragmented data and outdated systems – is on the brink of breaking free. And by connecting patient records, addressing population disparities, and using predictive models, AI has the power to create life-saving solutions while shifting the focus of healthcare toward greater access and consumer-centric care.

We’re still in the early stages of this journey and navigating unknowns. While we can’t predict the exact breakthroughs ahead, we know AI is steadily improving how care is delivered—driving better outcomes for patients and empowering providers. The progress already being made is inspiring, and I’m proud to contribute to this transformation.

Thank you for the great interview, readers who wish to learn more should visit DexCare. 

[industryupdate]

Global Data Center Market to Hit $622.4B by 2030, Led by IT & Telecom Advances

According to the latest market research study published by P&S Intelligence, the global data center market is on a growth trajectory, projected to reach USD 622.4 billion by 2030. A key trend in the industry is the push toward carbon-neutral data centers by the decade’s end, with companies implementing strategies to meet this objective. According to the IEA, the U.K. aims to reduce greenhouse…

[techdriveplay]

Understanding the Difference Between 4G and 5G Networks

As our reliance on mobile connectivity grows, so does the need for faster, more efficient networks. Understanding the difference between 4G and 5G networks is crucial as 5G technology becomes more widely available, promising to revolutionise how we interact with the digital world. From browsing the web to powering autonomous vehicles and smart cities, 5G is set to offer significant advancements…

[newsepick]

Google CEO Sundar Pichai says, ‘PM Modi asked to make sure AI benefits India! Google and Nvidia plan to enhance their presence in India, focusing on artificial intelligence (AI) following a meeting between their CEOs and Prime Minister Narendra Modi. During Modi's U.S. visit, Pichai and Huang praised his vision for a "Digital India" and the potential of AI to improve sectors like healthcare and education. Both companies aim to tailor AI solutions for India's unique needs and expand infrastructure, with Nvidia already collaborating with Yotta Data Services and Indian academic institutions to boost AI training and resources.

[ajmishra]

Dominating the Market with Cloud Power

Explore how leveraging cloud technology can help businesses dominate the market. Learn how cloud power boosts scalability, reduces costs, enhances innovation, and provides a competitive edge in today's digital landscape. Visit now to read more: Dominating the Market with Cloud Power

[luckyonexcel]

Exploring the Future of IoT | Internet of Things

Internet of Things (IoT) has already transformed the way we perceive and interact with technology connecting everyday objects to the digital world. As we navigate through a rapidly evolving technological landscape it becomes crucial to delve deeper into the future of IoT and the endless possibilities it holds. Let’s explore the exciting advancements and emerging trends that will shape the future…

[gavstech]

Social engineering is a form of psychological manipulation used to gain access to confidential information or resources. This tactic is often used by criminals and hackers who use deception, manipulation, and influence tactics to exploit people’s trust in order to gain access to sensitive data in IT operations.

[covidsafecosplay]

The People’s CDC COVID-19 Weather Report: October 14, 2024

The People's CDC has released another updated report on COVID-19 data and action items for the United States of America.

Highlights:

According to data last updated 10/5/2024, the CDC’s national wastewater map shows 16 states with “High” or “Very High” wastewater levels.

According to the Wastewater COVID-19 National and Regional Trends dashboard, all regions continue to show a downward trend over the last several weeks.

Many Bay Area counties are set to reimplement mask mandates in hospitals from November 1 through Spring 2025. Some of the rules apply to only certain healthcare staff while others include visitors and patients. Though these mandates are limited in scope, duration, and geography, a few are expanded compared to last year’s Bay Area mask rules, a sign that pressure on decision makers is working. 

In the past week, the California Department of Public Health reported that 6 new cases of bird flu (H5N1) were confirmed in dairy workers in California, with each case being connected to contact with infected cattle in California’s Central Valley. While there is yet no documented human-to-human transmission, each new case presents a greater risk of the virus mutating to spread from human to human.

The Texas State Affairs Committee posted notice of a hearing at the Capitol on October 16 to discuss, among other things, “Unmasking Protestors.” Opposition is mounting, and people are organizing.

Read the rest of the report here:

Please note that the CovidSafeCosplay blog and its admin are unaffiliated with the People's CDC or its management, and are simply sharing the resource.

Via the People's CDC About page:

The People’s CDC is a coalition of public health practitioners, scientists, healthcare workers, educators, advocates and people from all walks of life working to reduce the harmful impacts of COVID-19.  We provide guidance and policy recommendations to governments and the public on COVID-19, disseminating evidence-based updates that are grounded in equity, public health principles, and the latest scientific literature. Working alongside community organizations, we are building collective power and centering equity as we work together to end the pandemic. The People’s CDC is volunteer-run and independent of partisan political and corporate interests and includes anonymous local health department and other government employees. The People’s CDC is completely volunteer run with infrastructure support being provided by the People’s Science Network

[jcmarchi]

Unveiling Neural Patterns: A Breakthrough in Predicting Esports Match Outcomes

New Post has been published on https://thedigitalinsider.com/unveiling-neural-patterns-a-breakthrough-in-predicting-esports-match-outcomes/

Unveiling Neural Patterns: A Breakthrough in Predicting Esports Match Outcomes

In a groundbreaking discovery, NTT Corporation, a leading global technology company providing services to consumers and businesses as a mobile operator, infrastructure, networks, applications, and consulting provider has identified neural oscillation patterns that are closely linked to the outcomes of esports matches, achieving prediction accuracy of approximately 80%. This innovative research marks a significant advancement in understanding the brain’s role in competitive performance and opens new avenues for individualized mental conditioning.

Key Findings:

Patterns in Pre-Match EEG Linked to Outcomes: Specific neural oscillations were found to be strongly associated with match results.

High Accuracy in Predicting Match Outcomes: Including the prediction of upsets, the research achieved an 80% accuracy rate.

Potential for Personalized Mental Conditioning: Insights from neural oscillation patterns can be used to optimize brain states for improved performance.

Figure: Pre-round EEG correlates with match outcomes in fighting video game.

The Research Journey

NTT’s Communication Science Laboratories have long focused on how the brain regulates mind and body to enhance individual capabilities. Athletes, especially, strive to reach optimal mental states under competition pressure, a practice known as mental conditioning. Despite advancements in sports analytics, accurately predicting outcomes of “similar-level matches” or “upsets” has remained elusive.

Breakthrough in Esports

By focusing on a fighting video game in esports, researchers could observe and analyze players’ brain states during matches using electroencephalography (EEG). This method allowed for the identification of pre-match brain activity patterns strongly linked to winning or losing. Esports, a rapidly growing field, provides a unique opportunity to study these brain patterns due to its emphasis on mental over physical skill.

Discovery of Brain Activity Patterns

The study measured the neural oscillations of skilled esports players during real competition conditions. Results indicated that left frontal gamma oscillations, related to strategic decision-making, and left frontal alpha oscillations, associated with emotional control, were significantly increased in winning matches. These findings highlight the brain’s critical role in determining competitive outcomes and suggest that certain neural states can predict success.

Predicting Match Outcomes with High Accuracy

Machine learning models trained on pre-match EEG data were constructed to predict match outcomes. These models achieved an 80% accuracy rate, outperforming traditional models based on past match data. The high predictive accuracy was consistent for both similar-level matches and upsets. This breakthrough demonstrates the potential of EEG-based predictions in fields where traditional data analytics fall short.

Implications for Mental Conditioning and Performance Enhancement

This research not only reveals the existence of an ideal brain state in competitive situations but also suggests that mental conditioning based on bio-information can enhance performance across various fields such as sports, healthcare, and education. By understanding and optimizing the brain states associated with peak performance, individuals can improve their outcomes in high-pressure environments.

Applications Beyond Esports

The implications of this research extend far beyond esports. The ability to predict performance based on brain activity can be applied to traditional sports, where mental conditioning plays a crucial role. In healthcare, understanding brain patterns associated with optimal performance can aid in the treatment of mental health conditions. In education, insights from this research can help develop techniques to improve learning and cognitive performance.

Future Research Directions

NTT Corporation plans to continue exploring the applications of neural oscillation patterns in various fields. Future research will focus on refining the prediction models and expanding their use to other competitive environments. Additionally, the potential for transferring skills through digital twin computing represents an exciting avenue for further investigation.

The Digital Twin Concept

The digital twin concept involves creating a virtual representation of an individual’s brain state, which can be used to transfer skills and knowledge. By digitizing the brain states of experts, this technology can facilitate skill transfer and training in various fields. This approach has the potential to revolutionize how we learn and acquire new skills, making advanced training more accessible and efficient.

Enhancing Well-Being Through Bio-Information

NTT Corporation aims to enhance well-being by using bio-information-based mental conditioning techniques. By providing feedback on optimal brain states, individuals can learn to manage stress and improve their performance in various aspects of life. This approach aligns with the broader goal of improving mental health and cognitive function through innovative technological solutions.

Conclusion

NTT Corporation’s pioneering work in identifying neural patterns linked to esports match outcomes represents a significant leap forward in both neuroscience and competitive gaming. By harnessing these insights, there is potential to revolutionize mental conditioning and performance optimization in multiple domains. As research continues, the applications of this technology will expand, offering new opportunities to enhance human capabilities and well-being.

The discovery of neural oscillation patterns associated with competitive performance opens new possibilities for understanding and improving the brain’s role in various activities. With continued research and development, these findings could lead to significant advancements in mental conditioning, skill transfer, and overall performance enhancement across a wide range of fields.

[covid-safer-hotties]

Also preserved in our archive

By Julia Doubleday

For many disabled and immunocompromised people, hospital settings are a significant threat to health and safety. Since the beginning of the COVID-19 pandemic, nosocomial- or healthcare acquired- SARS-COV-2 infections have been an additional risk for sick and vulnerable people seeking care. As of today, there have still been no updates to national-level guidance to reflect that SARS-COV-2 was determined to be airborne in 2021.

In 2020, such a risk was to be expected; hospitals were overwhelmed with patients, PPE was in short supply, proper isolation wasn’t always possible, and public health guidance about transmission was confusing and, it turns out, incorrect. Early on, the WHO confidently and wrongly asserted that COVID was not airborne; this decision led national health bodies to advise against full airborne precautions in healthcare.

But in the nearly five years since, one might assume that any patient visiting their local hospital could reasonably expect safety from infection with COVID-19. After all, we’ve had five years to study transmission, update guidelines, redesign infrastructure, upgrade ventilation, purchase PPE and train staff, right?

As a matter of fact, the CDC has yet to even issue updated infection control recommendations, much less have we seen implementation. The CDC did ask their infection control advisory body, HICPAC, to update the Guideline to Prevent Transmission of Pathogens in Healthcare Settings, last reviewed and updated in 2007. But when HICPAC submitted a first draft of the updated guidelines in November 2023, it was over loud public objections registering that draft’s inadequacy to control airborne infections.

Now, HICPAC is continuing to insist that surgical-style masks are equivalent to N-95 respirators as it pushes forward with its draft guidelines. This decision is emblematic of its commitment to preserving ineffective droplet-based infection control in spite of new information and evidence. While bizarre from a purely scientific standpoint, it makes more sense from a cultural, political and economic point of view.

I’ve written at length about the political and economic factors that led the WHO to immediately claim that COVID wasn’t airborne without the scientific evidence to do so in Spring 2020. Perhaps just as irresponsible as their early decision to spread this misinformation has been their subsequent reluctance to correct their mistake as loudly as they first made it, and ongoing refusal to unequivocally recommend airborne precautions in the years since.

This year, the WHO released a document that rescinded the previous distinction between “droplet” and “airborne” transmission of viruses. This represents progress, as new data showed that no viruses actually transmit solely via “droplets”- i.e., only via sneezes and coughs.

The evolution of the science was tracked beautifully in this Wired article. It’s astonishing that we had such basic science so wrong, for so long. But it’s critical to note that for decades, there was a large financial incentive against looking too closely at the claim that flus, colds, and other common viral and bacterial infections were being spread only via large “droplets.”

“Droplet” precautions are relatively cheap and easy compared to the more complex and expensive requirements of controlling fully airborne infections. If a virus spreads through coughs and sneezes, how do you prevent transmission? Well, we all remember early pandemic guidance. Loose fitting surgical masks, social distancing and keeping diners (or patients) six feet apart, putting up physical barriers to protect from spit, and simply washing hands and covering coughs and sneezes are all examples of droplet-based infection control measures.

But airborne spread is far more difficult to control. Now we’re talking about viruses spreading well beyond six feet, well beyond the radius of a single cough or sneeze. We’re talking about the virus spreading, not just via coughs and sneezes, but via the simple act of exhaling. And not only that, but because airborne particles are so light, they don’t quickly fall to the ground the way droplets do; instead, they can hang in the air, much like smoke. So now, a waiting room or crowded examining area full of patients with flus, colds and COVID suddenly represents a much more complicated and expensive infection control problem for a hospital.

Proper airborne infection control procedures are expensive, but they are not mysterious. Some changes would be relatively simple; masking with proper respirator-style masks, rather than surgical, is an obvious, necessary upgrade. New ventilation and filtration standards are a simple fix technologically, but require investment. Tools like Far UVC are exciting and could mean drastic leaps forward in both patient outcomes and occupational safety for HCW.

Most likely, in order to save money long term and make airborne infection control sustainable, hospitals themselves would be constructed with airborne infection control, patient isolation, airflow, ventilation, etc. as major priorities in the process of designing the infrastructure.

Airborne infection control would require, rather than tinkering at the edges of existing practices, a top-down rethinking of hospital protocols. How are patients being screened upon entry into the hospital? How can COVID, flu, RSV, etc. positive patients be protected from one another in a waiting room? Why are so many hospitals designed without windows in patient care areas?

Are you beginning to see how the economic incentives align against admitting the need for airborne infection control?

Let’s return to the WHO’s document, the one that rescinded the distinction between airborne and droplet spread. Instead, all viruses which spread through the air are now referred to as “infectious respiratory particles” or IRPs. The document encourages moving “beyond the dichotomy of previous terms known as ‘aerosols’ (generally smaller particles) and ‘droplets’ (generally larger particles).”

But problems arise when the WHO attempts to apply what we’ve learned practically- or rather, doesn’t attempt to apply it. Here, it balks at what would be a massive undertaking. As I reported previously, back in 2020, the WHO had been quick to claim:

“Would there be evidence of significant spread of SARS-CoV-2 as an airborne pathogen outside of the context of AGPs [aerosol-generating procedures], WHO would immediately revise its guidance and extend the recommendation of airborne precautions accordingly”

But in 2024, the WHO, now well aware that SARS-COV-2 is a fully airborne pathogen, adopts a new approach to infection control. It’s one totally unprecedented for any other pathogen in healthcare. They advise:

There is NO suggestion from this consultative process that to mitigate the risk of short-range airborne transmission full ‘airborne precautions’… should be used in all settings, for all pathogens, and by persons with any infection and disease risk levels where this mode of transmission is known or suspected. But conversely, some situations will require ‘airborne precautions’. This would clearly be inappropriate within a risk-based infection prevention approach where the balance of risks, including disease incidence, severity, individual and population immunity and many other factors, need to be considered, inclusive of legal, logistic, operational and financial consequences that have global implications regarding equity and access.

In other words, we shouldn’t always try to control airborne disease. That would be so hard and annoying! The document then goes to state that “risks” have to be balanced and goes on to list a bunch of factors that are never considered when it comes to the spread of other pathogens in healthcare.

When it comes to the spread of norovirus in healthcare, do doctors weigh whether to wash their hands, based on the local levels of diarrhea? When it comes to the spread of bacterial wound infections, do doctors clean surfaces based on how deadly they think the wound will be? I mean, if it’s not going to kill you, why bother, right? When it comes to bloodborne illnesses like HIV, do doctors no longer test for it because it’s now a treatable disease, no longer a death sentence?

Or, when you apply this logic to any other type of infection, is it clear that this is an absurd attempt to continue evading liability for nosocomial airborne infections in healthcare, including SARS-COV-2? People should not be infected with diseases in hospitals. Period. Regardless of disease severity. Of course, SARS-COV-2 is also incredibly severe for hospitalized patients; in Australia, nearly 1 in 10 patients who caught COVID in hospitals in 2022 and 2023 died. And these events are far from rare. Of 206 patients admitted for strokes in a hospital in Japan, 44 were infected with COVID-19. 6 of them - or 13% - died. Globally, we see the same thing over and over again: lack of airborne infection control, high rates of nosocomial infections, high rates of patient death.

The WHO chose to incorporate “balance of risks”, “disease severity”, “immunity,” and the rest of its laundry list of “factors”, not because it expects infection control bodies to do serious risk assessments, but in order to provide cover for them not to do any such thing. Universal airborne infection control would be expensive and disruptive so the WHO simply gives disease control bodies a series of “outs”.

This is the international backdrop against which the US has also been updating infection control guidance. The CDC, like other national public health bodies, does not directly report to the WHO; the WHO does not have enforcement power over the CDC. However, guidance from the WHO is taken seriously at the CDC, and experts at the CDC also influence the WHO.

The WHO’s document constructs a mile-wide loophole for HICPAC to drive through. Although HICPAC provides no evidence whatsoever that the characteristics of SARS-COV-2 (or flu, or RSV for that matter) would justify dropping airborne precautions, the language in the WHO document exists to justify dropping them in the face of the ongoing, global pandemic. Despite SARS-COV-2 being a systemic, multi-organ disease with the potential to cause long-term disability, and highly fatal when contracted by vulnerable patients, culturally and politically, we are treating it like a cold. HICPAC members are not making scientific decisions, but political ones.

The science on disease transmission has advanced tremendously since 2020. In a world that actually wanted to implement what we’ve learned from COVID, this would mean dramatically safer care for patients and healthier workplaces for HCWs. Instead, HICPAC does the opposite, working to ignore the advancements in scientific knowledge and fighting to keep infection control as similar as possible to the outdated droplet model of the pre-pandemic era.

For example, they advise that N95 respirators should be worn for “new and emerging pathogens,” but make an irrational distinction between these and other viruses that are already in circulation. You know, the ones that are actually, currently infecting patients. “Emerging/new” isn’t a type of transmission, so shouldn’t denote a type of infection control.

Even the CDC balked at HICPAC’s initial draft, sending it back with pointed questions about this bizarre distinction and other inadequate protections. It asked for clarification, stating:

Another issue relevant to preventing transmission through air is to make sure that a draft set of recommendations cannot be misread to suggest equivalency between facemasks and NIOSH Approved respirators, which is not scientifically correct nor the intent of the draft language. Although masks can provide some level of filtration, the level of filtration is not comparable to NIOSH Approved respirators.

Why would HICPAC equate surgical masks with respirators? HICPAC’s draft was not designed to protect patients; it was designed to protect the status quo and allow hospitals to continue to infect patients with COVID and other airborne diseases. It’s likely that the CDC’s decision to push back on this claim was influenced by the massive outpouring of public outrage at the draft, which was seen in both the public comments submitted and read at HICPAC’s meetings.

Additionally, both OSHA, the Occupational Safety and Health Administration, and NIOSH, the National Institute for Occupational Safety and Health, agree with both the CDC and patients that surgical masks are not sufficient protection. N95s are required to control airborne infections.

However, despite months of pushback, the tears of suffering and scared patients, the word of the experts who design respirators, as well as the input of occupational safety leaders, HICPAC remains unmoved on the subject.

In a series of votes held last month, HICPAC stuck to their guns. Lisa Baum of the New York State Nurses’ Association was the sole dissenting member of the committee, as reported by Judy Stone of Forbes. She not only voted against the anti-science equating of surgical and N95 masks, but also against allowing COVID positive staff to return to work 3 days after a positive test. The 3-day time frame has absolutely no scientific basis, and return to work should be based on negative tests, not on an arbitrary time window or symptoms. Since a quarter of all COVID cases are asymptomatic, staff should also be asymptomatically screened; they aren’t because hospitals don’t want staff taking time off. Again, these are economic, not scientific, decisions.

Putting these two votes together, HICPAC has voted to allow sick, infectious, COVID+ staff to go to work without proper PPE and infect fellow HCW and patients, in hospitals without proper ventilation and filtration. Patients who are infected in hospitals using outdated droplet precautions will have a 10% risk of death. Coworkers- even if fully vaccinated- will have a significant risk of developing a long-term health condition following their acute infection.

At a time when hospitals remain crushed by the ongoing burden of both COVID and post-COVID health problems, failing to protect workers is a particularly short-sighted decision. Studies have already shown that HCWs suffer unusually high rates of Long COVID, with a recent one in the UK finding a whopping 33.6% reporting symptoms, and 7.4% of respondents reporting an official diagnosis.

These decisions not only mean infected doctors and nurses returning to work actively ill; they also mean that hospitals will continue to reinforce false information about how COVID spreads, purposely miseducating doctors and nurses in their employ to save money.

The members of HICPAC understand that surgical masks aren’t really the equivalent of N95s, they simply believe HCWs are more likely to wear surgicals (they’ve explicitly stated such; this is not, incidentally, how infection control decisions should be made). But this reasoning is not shared with patient-care level HCWs. Instead, HCWs are told that surgical masks are a sufficient infection control measure for COVID-19 when infectious. When an informed patient seeking care tries to correct them, they are greeted with condescension; after all, the doctor’s information comes directly from the CDC.

Disabled and immunocompromised people relate stories of medical professionals who believe COVID spreads via droplets, who wear surgical masks instead of N95s, who draw curtains to prevent the spread of COVID and other viruses; in other words, they are continuing to adhere to outdated precautions. This is unsurprising, because they have never received accurate guidance reflecting our updated technical knowledge about how SARS-COV-2 and other common viruses actually spread.

They’ve never received updated information because the medical system does not want to spend money to protect workers or patients.

At the end of the day, this story is not about droplets and airborne particles as much as it is about dollars and cents. What sounds like an in-the-weeds scientific debate, is no more than a common tale of industry greed. We know- and have known- exactly what it would take to protect patients in healthcare settings. Instead, our leaders sit back and watch as day after day, more unnecessary infections and deaths accumulate. As day after day, more healthcare workers acquire illnesses at work which lead to staff shortages, worse patient outcomes, long-term departures, and the loss of talented, highly trained people from the field.

All of us, patients, doctors, nurses, and other healthcare staff alike, deserve medical leadership that will value our rights to safety in these settings. We deserve medical leadership that won’t actively try to slow scientific progress, and instead will welcome its arrival. We deserve to enter a hospital knowing we won’t be infected and killed because HICPAC would rather allow airborne nosocomial infections to continue on its watch than spend money preventing them.

Right now, the biggest factor protecting hospitals as their negligence rolls on into year five is the ignorance of the public. Most people have no idea how COVID and other viruses spread, have no idea that it’s so dangerous to contract COVID as a vulnerable patient (thanks to years of normalizing propaganda), and may themselves believe that social distancing or curtains prevent infections. This public ignorance is a deliberate tool which enables continued public health negligence on multiple fronts. Continuing to educate ourselves and each other is resistance when the state relies on ignorance to tamp down resistance to policies of mass infection and death.

[techdriveplay]

What Should You Know About Edge Computing?

As technology continues to evolve, so do the ways in which data is processed, stored, and managed. One of the most transformative innovations in this space is edge computing. But what should you know about edge computing? This technology shifts data processing closer to the source, reducing latency and improving efficiency, particularly in environments where immediate action or analysis is…

[thedialoguedilemma]

President Donald Trump has signed an Executive Order officially withdrawing the United States from the World Health Organization

The World Health Organization (WHO) is a specialized agency of the United Nations responsible for international public health.

Its primary role is to direct and coordinate global health efforts along the metrics of Health leadership and advocacy, disease control and prevention, research and data, emergency response and global healthcare infrastructure building.

[centrally-unplanned]

would there have been a point to harris campaigning more on economic measures instead of focusing a lot on abortion? or was there no saving this one.

i mean, could always promise more infrastructure investments, housing, etc.

There is both a wide range of things one could do differently, and right now we don't have the full data on who voted how to really say definitively. My instinct though is that not really? It is very hard for her to say "Hey, I didn't do the inflation thing, trust me bro", and she did campaign heavily on issues like healthcare spending and even affordable housing. Voters just didn't trust her on it, Republicans just have an edge on that one - both generally and in this specific case.

If you want to run that campaign you bring in a new nominee, who didn't work for Biden and can authentically claim to be a new start.