Concerns about deadly fungal infections are growing nearly as fast as the outbreaks themselves. From popular television shows to recent articles in the Wall Street Journal and Fast Company, the attention has been swift and breathless.

Unfortunately, lost in the scramble to highlight their potency and develop a cure has been any agreement on an effective strategy for cutting into their spread. Over centuries of fighting diseases, humanity has developed a proven approach to containing outbreaks by first identifying how they spread and then breaking the chain of infection.

Like using preventive measures such as diet and exercise to stave off heart disease and other dangerous health conditions, healthcare has a distinct opportunity to prevent the spread of infections by addressing one of the primary root causes, improper cleaning and disinfecting.

The Rise of Fungal Infections

Earlier this year, the Centers for Disease Control and Prevention (CDC) issued a warning on the spread of Candida auris, a fungal infection that is one of the more prominent multi-drug resistant organisms today. Hard to diagnose and highly lethal in those infected, it has expanded quickly across large swaths of the United States, having grown from 53 people diagnosed in 2016 to at least 2,377 people in 2022, with cases tripling year over year. 

Severe fungal infections are deadly, with some having fatality rates of greater than 50%. And research shows that the risk of death can double for some fungal infections if treatment is delayed by even a day. In total, fungal infections kill at least 1.6 million people per year, according to the Global Action for Fungal Infections, but the actual number is likely much higher because of misdiagnoses.

Preventive Interventions Buy Time

History tells us we should be moving quickly to break the chain of infection to slow or halt the spread of Candida auris and other fungal outbreaks. 

One of the hard-won lessons from the COVID-19 pandemic is that a lack of uniform adherence to preventive guidance allowed the virus to spread rapidly, causing millions of unnecessary deaths before vaccines were made available. Even though compliance across the entire general public is admittedly difficult to sustain, enforcement of preventive best practices in our healthcare systems should be achievable.

When presented with an urgent, rising infection concern like Candida auris, the smart first step is to refine and augment our preventive efforts.

I saw this firsthand early in my career fighting the Ebola outbreak in West Africa. It was the heroic effort of rapid response teams and healthcare workers at Ebola Treatment Units conducting contact tracing, isolating those exposed, and adhering to rigorous infection prevention and control standards that helped contain the disease while a vaccine was developed and deployed.

An additional benefit of leaning into better cleaning and disinfection is that a large number of epidemiologically important pathogens are transmitted through surfaces, like C. difficile, methicillin-resistant S. aureus (MRSA), and vancomycin-resistant enterococci (VRE), meaning improved disinfection targeting one disease also has the potential to broadly prevent the spread of other diseases at the same time.

Hospitals as Primary Lines of Defense

Unfortunately, our places of healing also seem to be the most adept at spreading fungal infections. In fact, a CDC paper found that most Candida auris transmission in the U.S. to date has occurred in long-term healthcare facilities.

This is partly because studies show that many healthcare facilities have a significant opportunity to improve their disinfection compliance, which – when done poorly – leaves the door open for the rapid spread of contagion. A 2010 study across 27 hospitals found the average percentage of high-touch surfaces cleaned was 49.5%, while a study published this year by several Veterans Administration hospitals and long-term care facilities reported compliance at 33.6%.

The good news is that a handful of innovative hospitals have demonstrated how even incremental process change can lead to a real impact on patient safety. 

In 2006, researchers at Rush University Medical Center found that a proactive effort of training environmental services staff and improving cleaning metrics from 48% to 87% led to a 50% reduction in the acquisition of VRE. In 2008, a team at Brigham and Women’s Hospital found that bringing cleaning compliance from 44% to 71% was linked to a 49% reduction in MRSA. 

Most recently, a new study published this year conducted across eight hospitals at Trinity Health demonstrated that using a sporicidal disinfectant hospital-wide and improving cleaning quality from 59% to 93% was associated with a 50% decrease in hospital-onset C. difficile infections.

What’s compelling about these data sets is that they don’t necessarily require an impossible standard of 100% perfection to reduce infections – improvements that lead to compliance rates near 80% or better were typically enough to make a difference.

And they can be instituted quickly. Canada’s second-largest health system Fraser Health deployed an updated infection prevention process combining new technology with basic improvements like standardized cleaning carts. Weeks after rolling out these changes and with comprehensive staff training, Fraser Health documented a containment in outbreaks this past winter season compared to historical ones.

The bold headline in all of this is that room for immediate improvement exists. Fungal infections are a clear and present threat that has the potential to spiral out of control if not properly contained. But we can slow this spread through an emphasis on better cleaning techniques and training across our health systems, buying us time to develop better pharmacological interventions and a potential cure. The key is that we act now before the problem gets worse.

About Jason Kang

Jason Kang is the Chief Innovation Officer and a co-founder of Kinnos. Prior to this role, Jason served as Kinnos’ Chief Executive Officer. Jason previously conducted biomedical research at Harvard Medical School and Columbia University and served as the VP of Engineering at Jibon Health Technologies, where he brought a medical device to clinical trials in Bangladesh. For his pioneering work, Jason has been named to Forbes 30 Under 30 in Healthcare, served as an AAAS-Lemelson Invention Ambassador, was recognized as a Bluhm/Helfand Social Innovation Fellow, and was selected as one of Crain’s New York Business Notable Leaders in Health Care. Jason studied Biomedical Engineering at Columbia University as an Egleston Scholar and recently served on the Executive Board of Columbia Engineering Young Alumni.

You’ve probably heard about Ozempic, especially if you’re one of the millions who regularly scroll through TikTok or browse other social media platforms. It’s the drug that influencers are lauding as a revolutionary aid for weight loss, making it a hot topic of conversation. 

While Ozempic was initially developed to manage Type 2 diabetes, its emerging potential for weight loss is captivating medical professionals and the public alike.

How Ozempic Works: The Basics

Ozempic is a weekly injection containing the active ingredient semaglutide, FDA-approved in 2017 for adults with Type 2 diabetes. It helps control high blood sugar levels when used alongside lifestyle changes like proper diet and regular exercise. But the most intriguing discovery is its additional effect—weight loss—which is attracting interest well beyond the diabetic community.

Ozempic belongs to the class of drugs known as “GLP-1 receptor agonists.” It lowers blood glucose and stimulates insulin secretion, making it a mainstay in diabetes management. Furthermore, Ozempic also curtails the secretion of glucagon and slows down gastric emptying, which could help people feel full faster, making it an appealing option for potential weight loss prescriptions.

The Buzz on Social Media

There’s been a considerable surge in Ozempic’s popularity, fueled in part by social media influencers sharing their weight loss journeys. While Ozempic is not yet FDA-approved specifically for weight loss, some medical professionals are considering its “off-label” use as a weight-loss solution. 

It’s essential to note that its active ingredient, semaglutide, has already been approved for chronic weight management under the brand name Wegovy — which most recently, has shown positive effects on patients with heart failure — assuming the adult patient is overweight or obese and has at least one weight-related condition.

Navigating the Financials

While the enthusiasm around Ozempic’s potential is high, it’s worth mentioning that insurance usually does not cover off-label uses. Therefore, patients opting to use it for weight loss should be prepared for the cost, which could exceed $1,000 per month. 

Always Consult a Professional

While Ozempic has proven incredibly beneficial in managing Type 2 diabetes, just like any other medication, it does have its own potential set of side effects. There are some reports that have shown that Ozempic could potentially cause mild digestive side effects, among others. Therefore, consultation with a healthcare provider is critical for anyone considering Ozempic for weight loss. 

A Responsible Approach to Sharing Information

Social media has changed the way we perceive and consume medical information. While pharmaceutical companies are bound by rigorous standards and regulations, independent influencers are not held to the same criteria. In a digital age where personal testimonials can go viral and reach millions, it’s crucial for both medical professionals and social media users to share information responsibly. 

That being said, the majority of the information currently being shared regarding Ozempic’s effects is because there are clear, positive results that individuals are experiencing. At the end of the day, however, it is both the consumer’s responsibility to do their research and the company’s responsibility to provide the most up-to-date and accurate information on their products. 

To this extent, social media influencers — particularly those within the healthcare space — should understand the power that they have, and always keep in mind that information should always be shared responsibly. 

A Bright Future

Ongoing evaluations are looking into Ozempic’s potential role in weight loss. While it’s currently essential for managing Type 2 diabetes, its potential extends further, possibly helping millions more in their weight loss endeavors. The key is to approach this medication responsibly, guided by proper medical advice.

So, while the future seems promising for Ozempic as a groundbreaking treatment for both diabetes and potentially obesity, consultation with healthcare providers is essential for its safe and effective use.

About George Kramb
George Kramb is the CEO and co-founder of PatientPartner, a platform he created after recognizing the anxiety patients felt before medical procedures. With a background in supporting doctors in the operating room, George saw the need for more significant support, education, and compassion for patients facing stressful medical experiences. PatientPartner connects patients in a community of empathy and support, boasting over 100 PatientPartner Mentors who share their own medical experiences to help others. George, a Bachelor of Science in Economics graduate from the University of Oregon, has been featured in prestigious publications like Inc and Forbes 30 Under 30 for Consumer Technology and is a regular contributor to Entrepreneur. Under his leadership, PatientPartner has also built a network of over 50 doctors who prioritize improving their patients’ experiences through connections with relatable individuals.

Unlocking data silos using Federated Computing (FC) has the potential to achieve a positive impact across the healthcare industry, ranging from clinical care quality improvement and accreditation to population health management, precision public health and equitable drug development.

We define FC as the leverage of federated learning and edge computing technologies to enable federated data access, enabling analytics and Artificial Intelligence (AI), using linked, but not co-located, data. In turn, the superior privacy posture offered by this approach is appealing to data owners as it lets them remain in control of their data at all times, and thus reducing their administrative overhead and increasing their willingness to participate in data-driven innovation. 

By leveraging this emerging technology, innovators and AI developers can enjoy more diverse data to develop AI models that help drive positive transformation of the industry, while data owners who may not have the resources to develop AI models still get the opportunity to participate in- and access innovation. The same holds true for large-scale quality improvement efforts, which typically are held back by the challenges of accessing and analyzing data from large networks of providers, making them costly to participate in. Based on early signals from our partners and from the broader ecosystem, we anticipate that the effects will be most palpable across five primary segments (all depicted below).

1. Enabling Large-Scale Quality Improvement- and Accreditation Efforts

The strong privacy posture offered by privacy-preserving, distributed analysis compared to direct data sharing makes it easier for healthcare providers to participate in quality improvement efforts by lowering barriers to scalable quality benchmarking. This is accomplished by reducing the administrative burden and cost for providers (e.g., data sharing agreements, compliance), as well as by lowering data privacy risks. In addition, capabilities to run data harmonization and other operations to prepare data for analysis reduce the intensity of project management and coordination needed to orchestrate efforts across sites (which otherwise tends to increase exponentially in complexity as these networks scale). 

FC has a role to play in this ecosystem by allowing high-quality centrally defined risk adjustment models and quality metrics to be developed and validated in broader settings, ensuring a fair and unbiased assessment of quality, as well as by being more readily deployed and executed at individual provider sites without direct data sharing. In practice, using FC, high-quality risk adjustment algorithms and comprehensive quality metrics can be developed and validated by leading quality assessment entities, including accreditation agencies like the American College of Radiology (ACR) or bodies that develop, validate and measure quality, like the National Quality Forum (NQF) or the International Consortium for Health Outcomes Measurement (ICHOM), to be subsequently applied to assess the quality of care across multiple healthcare providers. 

The resulting improved transparency on quality of care then allows for identifying best practices for others to learn from and is likely to attract the interest of public funding bodies who are increasingly interested in reimbursing for value. By linking reimbursement to care quality, the healthcare system can adopt a more value-based approach, triggering a virtuous cycle where healthcare providers are primarily incentivized towards improving patient health. Different entities are already investing significant efforts in comparing health outcomes and various process metrics across healthcare providers, but given the complexities of execution, these are often limited in scope and require much time to execute. 

By making it easier to obtain transparency on quality, FC thus has an important role to play in establishing this value-based care ecosystem. Beyond enabling value-based reimbursement, the resulting transparency can exert a positive impact by helping fuel a palette of applications that empower patients to make more informed choices about their care, much like what is observed in other industries, where platforms for comparing price and performance of products and services are commonplace.

2. Enhancing Population Health Management

Improved population health management (PHM) capabilities can be achieved by effectively disseminating more generalizable patient risk segmentation models, to identify individuals at high risk of experiencing poor health outcomes. FC will let leading developers create robust analytical approaches and risk segmentation models, trained on data from diverse populations, which can then be distributed to healthcare providers that may lack the expertise to develop such models themselves. 

By identifying patients at high risk of poor health outcomes in advance, these risk segmentation models enable timely interventions, such as primary and secondary preventive care, resulting in improved patient outcomes. As data remains within the data custodian’s control and behind their firewalls, FC reduces the risk for individual institutions to participate in PHM efforts, driving wider dissemination as well as making data from more diverse populations available for model training. In turn, this will improve the generalizability and performance of the models, which translates to an increased ability to find the patients who need intervention before it becomes too late.

3. Syndromic surveillance

In addition to creating data silos that impact the external validity of insight and the generalizability of models, the current barriers to accessing and deriving insights from data across a network of institutions severely impact the ability to identify signals of emerging epidemics. Given the often rapid spread of contagious disease, it is important that data can be accessed and analyzed as early as possible when disease spread begins, to enable public awareness and intervention. Horror stories from the recent COVID-19 pandemic depicted how medical students were commissioned by the hour to manually abstract data from unstructured EHR notes into an array of disease registries, which came at a high cost and with a data velocity that was not conducive to tracking pandemic spread in a manner suited for timely intervention.

To ensure that the next pandemic is detected in time for institutions to prepare and monitor in a manner that allows for successful intervention, ideally avoiding some of the strict lockdown restrictions from a few years ago, governmental agencies should consider investing in developing a distributed network that allows for near real-time access and analysis of real-world data. The need has already been recognized at the grassroots level, as is for example illustrated by networks of hospitals that collaboratively work to harmonize data and make it useful for collaborative analysis. However, the computational infrastructure for operationalizing such data without the need for transferring it across institutions remains to be implemented.

4. Advancing Precision Public Health

While FC clearly can help advance traditional precision-medicine use cases such as enhancing response rates to medicines by enabling AI models that better match patients with the appropriate therapy, it also has a role to play in conjunction with the future of public health. In particular, the emerging paradigm of precision public health (PPH) holds promise to better target public health efforts within populations, to ensure effective and equitable allocation of funds as precision medicine gradually will transform care delivery models. 

While it is well known that not all individuals in a population respond equally well to a given therapy, e.g., due to differences in genetic makeup that impact metabolization patterns, or due to concomitant medical conditions, the standard approach to finding a treatment that works is based on doctors iterating through different treatment approaches. In turn, this trial-and-error approach poses risks to patients and also drives cost, as patients tend to receive (costly) medications that may not be safe or effective for them before settling on one that is. In the future, recommendations from AI models trained on patient data can help doctors narrow down treatment options to those that are expected to work and thus support them in making safer, more effective and less costly choices for their patients. This benefit of moving away from the ‘one size fits all’ paradigm holds for public health initiatives as well, as not all interventions will be equally effective for everyone, thus driving low value care in certain populations. 

While the direct physical- and financial risk resulting from subjecting a patient to an ineffective public health intervention may be lower than subjecting them to an ineffective medication, we expect that better allocation of public health interventions will translate to better overall cost containment in the healthcare system, as well as to improved patient outcomes. In this context, FC again acts by lowering barriers for individual institutions to participate in the development of models for assessing the likelihood of an intervention (e.g., a public health program) being effective in a given population, thus leading to greater diversity of the data available for model development and as a result to improved model performance.

5. Enabling Equitable Drug Development

In addition to the challenges of matching the right patient to the right intervention, the healthcare industry struggles with inequitable care in the context of life sciences innovation that insufficiently takes into account traditionally disadvantaged populations. This largely comes down to the fact that executing development programs and clinical trials in these populations is sometimes challenging due to a number of reasons not all elaborated here. While this pain point has caused real-world data (RWD) vendors and related service providers to increasingly take patient diversity into account, the footprint of these platforms is still largely confined to the sites and populations that tend to be well represented in clinical development programs already. 

By reducing the data privacy risk for clinical sites to participate in pre-screening and trial site-selection endeavors, FC can help lower the barriers for non-traditional sites to participate in clinical development. In practice, this would let them swiftly undertake feasibility screening using algorithms that have been developed elsewhere, in a secure manner that does not involve any data transfer to a third party. The larger the number of diverse clinical sites that make their RWD available to the life sciences industry for such pre-screening, the more effective trial site allocation becomes and the more likely it is that trials can be completed on time and in a diverse enough population to make them externally valid. 

Beyond helping to ensure that medicines are developed for everyone, broader geographical coverage can help life sciences companies identify clinical sites that may have been overlooked previously, but that have a high potential for successful patient recruitment and limited competition from biopharma peers. Finding such sites promises significant savings in terms of time and effort, and can lead to shorter-term returns on investments in the proposed federated infrastructure.

About Mathias C. Blom

Mathias C. Blom (MD, PhD, MSc) is the Partnerships Vice President at Rhino Health. As a Lund University and Harvard graduate, Mathias’ career has focused on innovating and advancing the technologies shaping the future of healthcare. From developing machine learning pipelines to leveraging predictive analytics for accelerating innovation in healthcare applications and medical research, Mathias is passionate about making a positive change in all life sciences sectors to improve patient care.

One of the most pressing issues in healthcare today is the growing talent shortage of qualified medical professionals. These critical staffing talent shortages could jeopardize communities’ access to care and result in dire consequences. The staffing shortage existed before the pandemic, but it’s only worsened during the past few years. According to government reports, 23% of hospitals are experiencing a significant staff shortage. 

Since February 2020, hospital workforces have been reduced by more than 105,000 employees. Many hospitals increasingly rely on contract labor from healthcare travel staffing firms to mitigate these talent shortages. While there are pros to this approach, such as allowing providers to expand their offerings, this type of labor is often more expensive, increasing hospital and patient costs.

This is making hospitals face even more financial challenges. This talent shortage affects the quality of patients’ care and poses a significant threat to their safety. A 2021 Mercer study revealed that the healthcare industry had experienced a workforce loss of 20-30%. The study also forecasts that many remaining workers will consider changing jobs this year. Furthermore, it predicts that 900,000 nurses will permanently leave the industry by 2026. Twenty-nine states face a nursing talent shortage, and if current trends persist, they will be short by nearly 100,000 nurses in the next five years.

This talent shortage has serious implications for patients, as it can lead to longer wait times, reduced access to medical services, and an increased burden on existing healthcare professionals. Staffing shortages are truly a matter of life and death, potentially increasing patients’ risk of death by 4% to 6%. Areas with struggling hospitals can expect higher death rates and co-morbidity in their communities.

The shortage increases costs and leads to burnout

Significant shortages of physicians, allied health professionals, and behavioral health care providers will likely occur in areas serving marginalized urban and rural communities. Research from the Annals of Internal Medicine shows physician burnout and turnover cost $4.6 billion annually. The Syntellis Performance Solutions 2023 CFO Outlook for Healthcare shows that total labor expenses increased by 20.8% from 2019 to 2022. 

Additionally, studies reveal that the healthcare worker shortage can contribute to higher rates of physician burnout, lower job satisfaction, and increased healthcare costs. In a survey by the American Hospital Association’s American Organization for Nursing Leadership, the “emotional health and well-being of staff” was one of the top challenges and reasons for nursing staffing shortages.

How to address the shortage

Too often, healthcare workers flee rural communities for the perks that big healthcare organizations and cities can provide. But rural providers don’t have to stand pat; they can take matters into their own hands. Today’s job market is as competitive as ever, making it challenging for providers in communities to retain skilled professionals. Urban and rural providers have similar challenges in this arena, particularly as both often have higher populations of at-risk patients.

Rural and urban healthcare providers need to rethink their incentives and how they recruit talent. While it seems simple enough to suggest that increasing salaries and benefits packages is the solution to the staffing shortage, it’s not that simple. Workers today also want opportunities for professional development and career growth, and right or wrong, they often perceive a lack of opportunities in rural and urban environments.

Talent management is a two-part proposition. First, it requires attracting the right talent; secondly, it requires keeping the right talent. Incentives aren’t always about higher salaries. Sometimes it’s about the intangible benefits that attract people to a job.

Addressing this issue requires a concerted effort from stakeholders, including healthcare organizations, policymakers, and patients. No option, such as increased resources to provide incentives to attract and retain healthcare workers, is off the table. Enhancing loan repayment and other incentive-based programs are ways to make working in a rural environment too enticing to pass up.

Once on board, health institutions need to think with an eye toward the long term. Providing career growth opportunities and opportunities for employees to gain new skills will help improve the work environment. Additionally, reducing administrative tasks is the best way to prevent burnout and make the best possible environment. The easiest way to accomplish this is through the deployment of technology.

Technology has a potential two-fold benefit. It streamlines the bureaucratic red tape patients must navigate just to seek care, and it frees up doctors and nurses to focus on what matters to them the most: patients. The pandemic has prompted many providers to make necessary changes to address long-standing challenges.

To succeed, providers must invest strategically in solutions enabling digital transformation, particularly in cybersecurity, analytics, and cloud-based platforms. These investments will pay off for years to come. The demand for healthcare services will continue to rise, and unless the industry takes decisive steps to address this critical challenge, it will reach a tipping point where it’s no longer possible to address the issue. We’re not there yet, but it’ll be here before we know it if we don’t act soon.

About Khue Tran

Khue Tran is the Chief Strategy Officer at Azalea Health where she is responsible for driving growth opportunities, business development, and strategic partnerships. With a decade of expertise in healthcare IT, she has excelled in diverse roles encompassing product strategy, business operations, and customer success.

What You Should Know: 

• Texas Department of State Health Services (TX DSHS) has partnered with SAS to develop new public health dashboards for tracking influenza data across the state, unifying multiple flu surveillance sources into a central visualization platform. 
• The flu data visualizations and analytics will be instrumental for Texas DSHS in anticipating regional surges in cases and allocating state resources to the areas with the most testing and vaccination needs while keeping the public informed on their local outbreak risk. 
• With a more accurate and detailed picture of the influenza risk county-by-county, drawn from updated weekly data, Texas DSHS can initiate preventative measures that can mitigate the severity of outbreaks and save more lives across the state.

Support More Informed Decision Making 

The Texas DSHS dashboards and analytics are powered by SAS^® Viya^®, the company’s cloud-based AI, machine learning, analytics and data management platform. A clearer and more digestible representation of data will allow health providers to make informed decisions faster, especially during peak seasons of activity. At the same time, SAS Viya’s ability to unify what has historically been a siloed data aggregation process onto a single dashboard dramatically reduces flu data analysis from hours down to minutes. The result is that providers can respond quickly with more influenza testing and vaccinations while accelerating the ability of health stakeholders to identify outbreaks.

What You Should Know: 

• TELUS Health today released its monthly Mental Health Index which revealed that workers who collaborate with others in the workplace have a better mental health score than those who work exclusively independently. 
• The Index also showed that the mental health scores of workers who do not feel supported in their mental health and wellbeing by their employers scored 10 points below the national average.

Collaboration aligns with better mental health

• Nearly two in five (37 percent) workers report needing to collaborate with coworkers all the time; this group has the highest mental health score (72.9), five points higher than workers who do not need to collaborate for their roles (67.8) and nearly two points higher than the national average (70.9).
• Nearly two in five (38 percent) of those surveyed reported that they would prefer to work alone most of the time; the mental health score of this group is more than four points below the national average.
• The mental health sub-score of isolation is the lowest among employees who prefer to work alone most of the time, nearly 12 points lower than employees who don’t prefer to work alone.

Employer mental health and wellbeing support

• The mental health score for workers who do not feel supported by their employer for their mental health and wellbeing needs is 10 points below the national average. Employees who feel less supported now versus early in the pandemic have an even lower mental health score (57.3) than those who never felt supported in the first place (60.6).
• Fifteen percent of workers surveyed indicated that their employer has improved the level of mental health support; this group has a mental health score of 71.5.
  • Laborers are 40 percent more likely than service industry workers, and 30 percent more likely than office workers, to report their employer has improved the level of support.

With the growing concern around the current climate crisis, industry leaders everywhere seek new ways to reduce their carbon footprint. The healthcare industry alone accounts for 8.5% of emissions in the United States, with medical devices and products contributing to a significant portion of the 5.9 million tons of healthcare waste each year. However, healthcare leaders are ready to make a change. In 2022, 61 of the largest U.S. hospital and health sector companies joined the Health Sector Climate Pledge, committing to reduce greenhouse gas emissions by 50% by 2030. 

By seeking innovative alternatives to traditional soft goods, plastics, and textiles, healthcare facilities can reduce their environmental waste – without compromising their standard of care. With over 15% of the country’s hospitals committing to the Health Sector Climate pledge so far, it’s clear that the healthcare industry is beginning to prioritize cleaner, more sustainable practices.

The commitment to a greener healthcare system may seem overwhelming – but industry-wide change can start with simple adjustments, such as finding sustainable versions of common, frequently-used products.

The environmental impact of hospital pillows alone is substantial. Since pillows are often designated for single-patient use, hospitals must replace them frequently and in large quantities – resulting in more significant carbon emissions and waste production. Approximately 14 million healthcare pillows are disposed of in the United States yearly. This generates 3.6 million square feet of waste, accumulating over time without degrading. 

Here are five ways healthcare facilities can reduce waste provided by soft surfaces:

1. Seek suppliers that offer a feasible alternative to traditional products

Information is power, and meaningful change will only be possible once healthcare facilities understand that greener alternatives are on the market. If facilities aren’t proactive in understanding the best options available for the products they purchase, it will limit their ability to achieve a greener future. Ask existing suppliers to provide details on their environmental practices, such as using sustainable materials, recycling programs, and energy efficiency measures. 

Hospitals should also always explore new technologies on the market and learn what is available. In doing so, they will be able to continually evaluate suppliers based on their environmental practices and other factors such as product quality, pricing, and customer service to determine whether they continue to use existing vendors or seek alternatives that are not cost-prohibitive.

2. Adopt multi-patient use products when possible

Several types of medical products can be safely used for multiple patients, assuming proper cleaning protocol is followed between patients. These products include blood pressure cuffs, pulse oximeters, nebulizer masks, tubing, and more. However, to improve sustainability efforts and reduce waste, healthcare facilities must be open to expanding their multi-patient use product offerings. 

New technologies have been developed that enable products that were previously considered single-patient use to be safely and effectively used for multiple patients. Adopting more multi-patient use products allows facilities to streamline purchasing efficiencies, reduce waste and carbon footprint, minimize costs, and improve patient and caregiver safety. However, it’s important to note that proper cleaning and disinfection procedures must be followed to ensure these products are safe for multi-patient use. Hospitals should also consult with their infection control team to develop appropriate protocols for using products on multiple patients.

3. Use biodegradable or compostable materials and products

Sourcing products made from biodegradable or compostable materials is another great way to reduce a facility’s carbon footprint. Currently, medical devices and products contribute to a significant portion of the 5.9 million tons of healthcare waste yearly. This waste accumulates in landfills without degrading over time. By converting to products that can maintain their structure during use, but can also break down when exposed to naturally occurring elements, healthcare facilities can significantly reduce their environmental impact without sacrificing product quality. 

4. Find technologies and products that serve multiple functions

Similar to the benefits of adopting multi-patient use products to improve sustainability, hospitals can also use multi-function products to reduce waste. For example, rather than using a boot to prevent heel breakdown and a positioner or pillow from maintaining patient alignment, find a product that can achieve both simultaneously. This will limit the number of products ordered and reduce the number of healthcare-related products disposed of yearly. 

5. Implement a textile management program

By implementing a textile management program, hospitals can reduce their environmental impact, save money, and improve comfort and safety for both patients and staff. Healthcare facilities can begin by conducting a baseline assessment of the current state of textile management practices that evaluates existing inventory, usage patterns, and disposal practices. Once the evaluation is complete, they can make more informed decisions regarding practices moving forward. Staff training is also essential to the practical implementation of textile management. Hospitals should train staff on using and caring for textiles to prolong their lifespan and reduce waste. This includes proper laundering techniques, handling and storage practices, and infection control protocols. 

Hospitals can significantly reduce their annual waste production and environmental impact by adopting these strategies. However, they can only achieve a greener future with cooperation from healthcare suppliers, who ensure the healthcare industry has the tools it needs to achieve a more environmentally-conscious future.

About Bill Purdy:

Bill Purdy is the CEO of Spry Therapeutics, a health technology company that uses a proprietary soft-surface filter technology to block all pathogens from entering or exiting any soft surface to which it’s applied. The Company is committed to providing effective, sustainable alternatives to traditional pillows and positioners that enable healthcare facilities to improve patient and caregiver safety, while reducing carbon emissions.

What You Should Know: 

• The Centers for Disease Control and Prevention (CDC) has recently released its Fentanyl Study Dashboard, an innovative tool that utilizes data from the Toxicology Investigators Consortium (ToxIC), to track and monitor nonfatal overdose trends associated with fentanyl. 
• The dashboard,  “Fentalog Study: A Subset of Nonfatal Suspected Opioid-Involved Overdoses with Toxicology Testing” went live in May of 2023 aims to provide vital insights to healthcare professionals, policymakers, and researchers, enabling them to respond effectively to the ongoing opioid crisis.

The ToxIC Fentalog Study

The ToxIC Fentalog Study collects data from 10 geographically diverse hospitals in 9 states to identify risk factors and evaluate optimal treatments for nonfatal overdoses involving fentanyl, fentalogs, illicit benzodiazepines, and adulterants (such as xylazine). Now in its 4th year, the study has over 1300 cases that are utilized to characterize synthetic opioids used, evaluate treatments, and track regional trends in fentalog overdoses.

The American College of Medical Toxicology (ACMT) Toxicology Investigators Consortium (ToxIC) Fentanyl Analog Study, also known as the Fentalog Study, is a five-year initiative (2020-2025) conducted through a National Institute on Drug Abuse RO1 grant (NIDA R01DA048009) at the Icahn School of Medicine at Mount Sinai. It examines the clinical effects of fentanyl analogs among suspected opioid overdoses and utilizes ToxIC’s extensive network of healthcare facilities to aggregate and analyze nonfatal overdose data.

Three years after the World Health Organization declared COVID-19 a pandemic, the Public Health Emergency (PHE) enacted in the United States came to an end this May. As much as we would like to go back to normal, it seems that simply turning the page on the PHE without carrying forward what we learned during Covid will leave millions of Americans scrambling for healthcare and disengaging from essential preventive health services. The result will be a devastating impact on those with chronic conditions, today’s leading cause of death in the U.S.

We can’t celebrate the end of one pandemic and at the same time plant the seeds for the next health crisis to erupt. Health plans, providers, and digital health companies must act now to ensure necessary, preventive tests are accessible to everyone.  

The end of the emergency period this month means the end of associated benefits and programs that have sustained many Americans throughout this challenging period. Some telehealth services—essential to people with transportation and accessibility barriers—might become less accessible in the near future. In addition, according to experts’ estimations, 17 million people could lose Medicaid coverage in just a few months. 

Even with the PHE’s assistance in 2022, 38% of Americans skipped or delayed medical care because of cost concerns. The end of the PHE will have a particularly adverse effect on low-income communities, who are more likely to get sick with chronic diseases in part because they already have less access to preventive care. The conclusion of the PHE’s assistance, combined with overall rising prices, will lead to more people rationing their doctor visits and fewer patients following up with routine testing and monitoring, which can be lifesaving. 

Chronic kidney disease (CKD) is one example of a chronic illness for which routine testing and monitoring are often overlooked. Although there are 37 million Americans living with CKD, nearly 90% are unaware. Known as a ‘silent killer’ for its lack of symptoms, CKD can be treatable—and kidney damage reversible—when caught in an early stage. A simple annual albumin-to-creatinine ratio (ACR) test, which checks levels of a protein called albumin in the urine, can provide an early indication of kidney damage. Despite clinical recommendations and the clear benefits of the test, 80% of at-risk Americans fail to take it, and only 30% of primary care physicians regularly order it. 

I know too well about the heavy price of late detection. When a close family member died recently from the complications of undiagnosed CKD, the pain of knowing we could have found it earlier, and perhaps prevented it and saved her life, was unbearable.  

To prevent other families from experiencing this tragedy, it is critical that health plans, providers, and digital health companies work together to make ACR testing as accessible as possible for all at-risk patients.

Reaching over 60 million untested Americans requires an all-hands approach that includes incentivizing health plans and better-informing providers. New policy initiatives, such as the proposed KED measure that links the valued star ratings to early detection, are a good first step, but they are not enough. As was the case with Covid, in order to reach the target population, we must implement clinical-grade, at-home solutions and prioritize innovation to improve not only the efficiency of our health system but our ability to scale our efforts and engage the hardest-to-reach communities.

Working in our health system for the past two decades, I know how fragmented and siloed it can be. But in the past three years, I have also seen tremendous efforts: colleagues thinking outside the box and cutting red tape to prescribe new telehealth services to quarantined patients; senior executives coming up with never-before-seen reimbursement models for at-home covid tests; cutting-edge regulatory initiatives that lowered stubborn health barriers and provided testing and vaccines free of charge; and dedicated advocates pushing for national priority changes that made pharmaceutical companies cap insulin prices—turning a scenario once considered science fiction into a reality.

The first pandemic of the digital age showed us that our healthcare system could be more patient-focused, more digitally proactive and that it could meet people where they are. The PHE may have ended this month, but the lessons and creativity we gathered along the way must not disappear with it. 

About Paula LeClair 

Paula LeClair is the U.S. General Manager of Healthy.io, the global leader in providing platforms and services that transform the smartphone camera into a medical device. Paula LeClair has over 20 years’ of experience in healthcare. Prior to joining Healthy.io, she held executive roles with Glytec, Onduo, and served as President and CEO of Telecare. Paula has an MBA from Bentley University and an MA in Healthcare Delivery Science from Dartmouth College. She serves as Chair of the Board for the American Diabetes Association New England Community Leadership Board.

In 2020, the Department of Justice estimated that fraudulent, wasteful, and abusive (FWA) billing practices account for more than $100 billion of the nation’s healthcare expenditures.¹ Today, the National Healthcare Anti-Fraud Association (NHCAA) conservatively estimates that healthcare FWA costs the nation about $68 billion annually, representing 3% of the nation’s $2.26 trillion in healthcare spending.²  FWA estimates from commercial health plans range as high as $230 billion annually, or 10% of total healthcare spending.³ 

This lost money is far from a concept or abstraction. Every dollar lost to fraudulent, wasteful or abusive billing hurts patients, honest providers, payors and governments. Third-party benefits providers often receive outsized blame for these costs, when in reality, fraud, waste, and abuse is extremely difficult to detect using conventional methods because providers submitting excessive or fraudulent billing claims are constantly changing their methods to avoid detection. 

Fortunately, new advances in artificial intelligence (AI) technology provide our industry a clear path forward to lowering healthcare costs by reducing excessive or overbilling in a way that rewards good providers and returns more dollars to patient care. By helping healthcare payors detect and prevent fraudulent, wasteful and abusive billing practices in greater quantities and before payments are made, it is estimated that up to $1 trillion in fraudulent, wasteful, and abusive costs can be eliminated from U.S. healthcare by 2030. It’s time to stop blaming benefits providers for spiraling costs and start addressing the technology that powers their day-to-day healthcare claims editing, audit and review systems. Here are the key concepts to consider. 

Static Claims Editing Systems Are Exploitable

Most healthcare benefit systems are based on a static, rules-based or use case-based technology that audit a very narrow set of criteria in determining whether a healthcare claim should be paid to the provider. While these systems do a good job of processing and paying billions of claims each year, their antiquated technology allows hundreds of billions of dollars in excessive bills or fraudulent bills to be paid. It’s not because the claims management companies don’t want to stop fraudulent and excessive billing, it’s because their technology can’t see the exploitation that’s occurring. 

Technology Has To See Provider Behaviors, Relationships and Outliers 

When cases are reviewed and adjudicated using traditional rules-based, use case-based and conventional AI methods, dynamic provider behaviors, relationships and outliers are hard to detect. You have to see a provider’s behavior around a claim and all claims and that provider’s relationships with other providers in order to detect fraudulent, wasteful and abusive billing at a significant level before claims are paid out. This means that this sophisticated, interdependent relationship between providers, a current claim form, historical claim forms, and all other providers in a network has to be able to be identified, analyzed and reported on in less than one second when a claim is submitted for payment. 

The Promise of Artificial Intelligence 

AI scares a lot of people, because it is hard to wrap your arms around what it is. Simply stated, one definition of artificial intelligence (AI) is technology that thinks and does what a human can do, but much faster. Even this simple description leaves out the benefit of unsupervised AI being able to identify an infinite number of ‘math problems’ that a human might not even know to look for in a data set. 

Early AI, and much of the conventional AI used in healthcare FWA detection and payment integrity work today, is not much more than a really advanced Excel spreadsheet. Much of the conventional AI operates using structured machine learning. This means that a machine is trained to perform an algorithm or series of algorithms that take an “if-then” approach to analyzing data. 

These structured machine-learning approaches are very helpful, but miss a lot of the dynamic trends, patterns and outliers that can be detected by advanced, unsupervised machine learning. To ‘see’ all of the FWA activity, you have to deploy unsupervised machine learning that identifies trends, patterns and outliers without being “told” specifically to go perform the task. This enables payors to see new fraud trends and patterns forming in near real-time that are indicators of behaviors and relationships that may be signs of excessive payments, over-payments, or even fraud. In short, you can see things and stop things from happening that you did not even know to tell your technology or staff to pursue. 

The Reality Of Integr8 AI^™ Technology In Stopping FWA 

Integr8 AI technology is a new generation of artificial intelligence that is patented for the detection of operational threats. The first application of the technology is to enable healthcare payors – commercial health plans, TPAs, CMS programs, etc. – to take a dynamic, provider-centric approach to processing, auditing and paying healthcare claims. This technology has proven to increase FWA detection by 2X to 10X in initial commercial use, all because it can “see” FWA activity that conventional technology can’t see. And Integr8 AI can see it in a way that does not slow down the claims editing, review and payment process. 

As one payment integrity executive said, “We need to be able to see the FWA activity that we all know is there. Current technology just doesn’t let us see the volume of FWA that next-generation Integr8 AI technology enables. The best part is that this type of technology operates on top of our current claims editing system. We don’t have to make new capital investments to make a big difference fast.”  

The Bottom Line for Benefits Providers

The battle against spiraling healthcare costs has important implications for every stakeholder in the healthcare value chain, but third-party benefits providers stand to benefit the most when fraudulent, wasteful and abusive costs are controlled. Today, almost a third of all insured Americans receive their health coverage through a third-party provider. Removing fraudulent, wasteful, and abusive costs helps benefits providers lower the cost of benefits for customers and their employees, automate and streamline operations, and increase bottom-line profitability. Technology, like Integr8 AI, enables the benefits to be quantified quickly and recognized almost immediately – regardless of what claims editing and adjudication system is being used. 

Now is the time for benefits providers to embrace sophisticated AI solutions for claims management, moving from a relatively static, claims-based model to a dynamic, provider-centric model. It’s time to take control in the fight against adaptable, malicious actors. That fight starts and ends with thinking about the technologies we have in place. 

About Theja Birur 
Theja Birur is the founder of 4L Data Intelligence and inventor of the patented Integr8 AI intelligence platform. She has 20 years of experience in analytics and artificial intelligence with most of that focused on solving payment and quality challenges for healthcare payers and public health agencies. Her career includes work in the government sector with the Ontario Ministry of Health in Canada, with IBM as a management consultant, and in the IBM Innovation Lab focused on analytics. Prior to founding 4L Data Intelligence, Theja worked as a consultant for the California State Compensation Insurance Fund where she was an Associate Director over Big Data and Data Warehouse functions.

What You Should Know:

• Today, the Drug Enforcement Administration (DEA) and the Substance Abuse and Mental Health Services Administration (SAMHSA) issued the “Temporary Extension of COVID-19 Telemedicine Flexibilities for Prescription of Controlled Medications” – a temporary rule that extends telemedicine flexibilities adopted during the COVID-19 public health emergency (PHE).
• ·         The temporary rule will take effect on May 11, 2023, and extends the full set of telemedicine flexibilities adopted during the COVID-19 public health emergency for six months – through November 11, 2023. For any practitioner-patient telemedicine relationships that have been or will be established up to November 11, 2023, the full set of telemedicine flexibilities regarding the prescription of controlled medications established during the COVID-19 PHE will be extended for one year – through November 11, 2024.

Background

On March 1, 2023, DEA, in concert with HHS, issued notices of proposed rulemakings (NPRM) to allow for prescribing of certain controlled medications via telemedicine without an in-person medical evaluation of the patient under circumstances that are consistent with public health, safety, and effective controls against diversion. The NPRMs received over 38,000 comments from the public and DEA, in collaboration with SAMHSA, is actively reviewing input in order to develop a permanent rule.

The COVID-19 pandemic shined a spotlight on the urgent need to modernize the nation’s public health system. Despite success in rapidly developing vaccines, the unprecedented public health emergency also exposed significant gaps in U.S. public health infectious disease data collection and analysis methods which are critical for identifying behavioral risk factors and preventive actions.

The Problem

Unfortunately, inefficiency remains a hallmark of the U.S. public health surveillance system due to the following two lingering issues:

• Disparate data collection systems

The CDC receives data from all 50 states and more than 3,000 local jurisdictions and territories. Hospitals, providers, and laboratories use a variety of systems to collect this data which is then reported to state, city, and local public health agencies. The information is then shared with CDC and other federal agencies. In general, each city, county, and state decide what information is collected, as well as how and when it can be shared with CDC.

What’s more, many current systems rely on disease-specific monitoring and manual data entry, which substantially burdens federal data partners. State and local reports to CDC are often delayed because the systems and data are simply not interoperable.

• Antiquated data-sharing methods

While data is increasingly shared via automated, electronic exchanges, some data is still being sent by fax machines, excel spreadsheets, or even by phone. The CDC encourages standardization, but it lacks the authority to receive data directly without establishing a data use agreement with each state and local jurisdiction. 

As a result, the agency must manually clean the data before conducting the analyses needed to provide an aggregated picture of public health. It can take weeks or even months to share the data with public health authorities, providers, and the scientific community,

The key challenge: how to collect and share information more efficiently so that information turns into actionable insights that can shape important public health decisions?

The Progress

The good news is CDC is leading multiple initiatives to make our public health infrastructure more connected and resilient. The CDC’s Data Modernization Initiative (DMI), launched in 2020, is a multi-year, billion-dollar-plus program to modernize core data monitoring and surveillance infrastructure across the public health ecosystem with the goal of enabling faster, actionable insights to support better decision-making. The recently created Office of Public Health Data, Surveillance and Technology will support this effort.  

Four key actions for fully modernizing the public health data infrastructure, and expanding data collection and sharing are:    

1. Adopt a Scalable, Federated Data Mesh Infrastructure

Today’s network of siloed, disease-specific systems creates significant redundancies and inefficiencies. It cannot scale to support the level of data aggregation, access, and speed public health agencies need. 

A scalable, federated data mesh infrastructure would allow federal agencies to curate high volumes of rich, interoperable data across their ecosystems. They could then accelerate their aggregation and analysis, and in turn, their public warnings and outreach, which are critical for fast-moving threats such as infectious diseases. 

By decentralizing data repositories, a data mesh allows those who are most knowledgeable about their data to control it, namely the public health entities functioning as nodes in a network. Via the mesh, the CDC would engage with electronic health records (EHRs), lab reports, genomic sequencing information, immunization, and other records. State and local agencies would then similarly engage. With CDC defining mesh policies and managing the mesh, data can be ingested, cleaned, standardized, and provisioned for use. 

With such a decentralized information technology architecture, federal agencies could also integrate technology to facilitate HIPAA-compliant patient record matching. This could be achieved without creating bottlenecks typically associated with centralized reporting and dissemination. 

Powered by robust metadata, search features and a centralized data catalog, the mesh would enable authorized personnel to effectively find, access, aggregate, and analyze public health data. This information could also be merged to support the principal guidelines for sharing and managing data adopted by research institutions worldwide, known as the FAIR Principles (Findable, Accessible, Interoperable and Reusable).

2. Protect Privacy 

Protecting the confidentiality of patient health information must be a top priority when modernizing public health infrastructure. The data mesh described above can integrate privacy-preserving record linkage (PPRL) technology which allows for data to be linked across different data sets without exposing individuals’ personal information.

PPRL technology maintains HIPAA compliance while enabling the matching of identifiable patient data without compromising patient privacy and confidentiality. For example, PPRL employs hashing to convert variables such as names, birthdates, and addresses into encrypted tokens that preserve the original values.

Linking data at the patient level enables a comprehensive view of an individual’s health, allowing researchers to answer questions that would otherwise require extensive primary data collection or complex data use agreements.

By integrating PPRL with standardized Fast Healthcare Interoperability Resources (FHIR) data components, public health agencies would be able to ingest and collect data from multiple sources and feed it into scalable analytics and modeling tools.      

3. Expand Data Sources

Currently, limited  EHR and social determinants of health data (such as access to transportation, rates of chronic disease, food insecurity, and crime) are interoperable via the established standard – the United States Core Data for Interoperability (USCDI). This data should be augmented by structured health data which is currently siloed in other agency systems including:

• Geospatial data such as walkability and access to care
• Remote-sensing data, such as wastewater testing and satellite imagery
• Mobility data from smartphones, GPS, and sensors along highways 

By layering additional data from siloed health systems and non-health sources, public health agencies could enrich the baseline USCDI data to gain deep insights. Recent efforts demonstrate the value of multilayered data to track the spread of COVID-19 in wastewater samples across the country, understand the impact of social distancing during the pandemic, and predict obesity rates.     

While encouraging, however, these results are limited in scope. Real-time, actionable surveillance at scale is impossible because of the lack of interoperability across data sources. Alternate approaches that bring more data into public health models and simulations must be pursued.

By extending interoperability and connecting the universe of rich, relevant data, public health agencies could boost the accuracy of prevalence estimates, counter-balance biases in traditional data collection, effectively target control and prevention strategies, and better allocate resources.

4. Harness Intelligent Automation 

Modernizing surveillance systems without burdening the public health workforce is a major challenge.

Public health agencies at all levels face a dire shortage of workers, with roughly 44 percent considering leaving their jobs within the next five years. That’s why public health agencies should adopt intelligent automation tools.

Intelligent automation can significantly improve infectious disease reporting by automating the collection and transfer of relevant health information from EHRs. When a health worker records a particular symptom or disease case in a patient’s EHR, the system could automatically send the data directly to CDC, eliminating current administrative reporting burdens. Improvements in the EHR aren’t limited to public health use – intelligent automation systems can also enhance the care provided to patients and decision support provided to providers.

Intelligent automation systems could also scan and interpret lab reports and clinical notes to uncover disease cases that might otherwise elude health officials, and trigger reports to state and local authorities. Additionally, technology learns and adapts. Powered by artificial intelligence and machine learning, these systems can go beyond simple optical character recognition by leveraging natural language processing to understand context, reduce noise, and improve accuracy.

Conclusion   

With a more modernized data infrastructure, public health leaders will be better equipped to identify and contain outbreaks, understand disease burdens, guide policy changes, evaluate and improve prevention and control strategies, and target research investments. The bottom line: enhanced data collection and analysis capabilities are critical to improving our nation’s public health outcomes.

About Kenyon Crowley

Kenyon Crowley, PhD is the Health Analytics Lead for Accenture Federal Services. Dr. Crowley brings nearly twenty years of health information technology expertise to his role. In his role at Accenture Federal Services, Dr. Crowley will help to accelerate the responsible and ethical use of AI and other advanced analytics tools across the federal health sector to help improve the well-being of all people in the country.

What You Should Know:

• A new analysis shows more than 21% of U.S. adults without access to a vehicle or public transit went without needed medical care last year. These individuals were significantly more likely to skip care than those who reported neighborhood access to public transit services (9%).
• This analysis examining the association between transportation and access to healthcare was conducted by Urban Institute researchers with support from the Robert Wood Johnson Foundation. 

Analysing and Addressing Barriers to Healthcare

Research shows that public transportation expansions improve access to health care, especially for people covered by Medicaid.

Using June 2022 data from the Urban Institute’s Health Reform Monitoring Survey (HRMS), it was identified that there exists a link between transportation barriers to healthcare and the association between public transit accessibility and access to care. Focusing on adults without access to a privately owned vehicle, key findings identified are as follows:

• Approximately 5 percent of non-elderly adults did not get needed health care in the past 12 months because of difficulty finding transportation, and this experience was more common among adults with low family incomes (i.e., below 138 percent of the federal poverty level [FPL]), adults with disabilities, adults with public health insurance coverage, and adults without household access to a vehicle.

• While 91 percent of adults reported having household access to a vehicle, this figure was substantially lower among Black adults, adults with low family incomes, adults with a disability, and adults with public health insurance or no health insurance coverage.

• Adults without access to a vehicle who reported living in neighbourhoods with fair or poor access to public transit were significantly more likely to forgo needed health care because of difficulty finding transportation compared with their counterparts reporting excellent, very good, or good neighbourhood access to public transit.

• City-level transit scores from WalkScore.com, based on distance to transit stops and frequency of transit service, were less predictive of access to health care than self-reported measures of neighbourhood public transportation access.

Among the share of adults who did not get needed healthcare in the past 12 months because of difficulty finding transportation, responses varied significantly by demographic and socioeconomic characteristics.  Specifically, not getting needed health care because of difficulty finding transportation was significantly less likely among adults with the following characteristics:

• White adults and Asian adults compared with Black and Hispanic/Latinx adults.

• Adults who have family incomes between 139 and 399 percent of FPL or 400 percent of FPL or more compared with adults who have incomes at or below 138 percent of FPL.

• Adults who do not have a disability compared with adults who have a disability. 
• Adults who have private insurance compared with adults who have public insurance or no insurance.

• Adults living in an urban area compared with adults living in a rural area.

• Adults who have household access to a vehicle compared with adults who do not have access to a vehicle.

Additionally, it was also identified that demographic and socioeconomic differences in household access to vehicles follow similar patterns as unmet health care needs because of transportation barriers. Further details revealed that:

• 91 percent of adults reported having household access to a vehicle.

• Black adults were significantly less likely to have access to a vehicle than Hispanic/Latinx adults, white adults, Asian adults, or adults of other races.

• Adults with family incomes at or below 138 percent of FPL were significantly less likely to have access to a vehicle than adults with family incomes between 139 and 399 percent of FPL or 400 percent of FPL or more.

Lastly, among adults without a vehicle, self-reported fair or poor public transportation accessibility is strongly associated with not getting needed health care because of difficulty finding transportation, even after adjusting for other demographic, socioeconomic, and geographic characteristics, specifically race/ethnicity, family income, disability status, health insurance coverage, rurality, population density, and major metropolitan area of residence:

• 22 percent of adults reporting the ability to get around without driving in their neighbourhood is fair or poor did not get needed health care, compared with only 9 percent of adults who reported excellent, very good, or good ability to get around without driving.

• Similarly, 21 percent of adults reporting fair or poor access to public transportation had this experience compared with only 9 percent of adults who reported excellent, very good, or good access to transportation.

Over the last decade, the healthcare industry has experienced an explosion of digital innovation. Simultaneously, shifting consumer preferences around convenience and access to care has accelerated the pace of technology adoption at unprecedented speed, especially in the wake of the pandemic. 

The value of these digital tools is manifold: healthcare enterprises report increased operational efficiency, higher quality care delivery, cost savings, and the potential to deliver a more equitable patient experience by engaging all patients in their care. 

To most healthcare players, these advances would seem like a win-win. Yet, the industry’s expanding reliance on technology has fueled fresh concerns about disparities around how these digital health tools are accessed. When it comes to underserved populations, will they benefit? Or risk getting left behind?  

Health equity in patient portal use

The contributing factors leading to inequities in digital tool usage are complex, varied, and overlap with broader social drivers of health. The term “techquity,” or technology-related health equity, has been used more recently to draw attention to this persistent, and growing, challenge — and highlight the need to focus on equity in the design, development, and implementation of digital tools.  

The HLTH Foundation’s Techquity for Health Coalition report highlights the three core elements of techquity: access, initial uptake and use, and sustained engagement.

To narrow the digital divide in healthcare, we examined patient portals and their role in improving healthcare outcomes and patient experience. Patient portals empower patients to play more active roles in their care by providing access to their personal health information while increasing efficiency for providers and care organizations. Ideally, by streamlining patient communication and administrative tasks, providers should be able to minimize distractions and shift their focus to delivering high-quality care. 

If patients actually log in, that is. Today, 90% of hospitals and providers in the U.S. offer patient portals. Despite the high rates of adoption on the provider end, patient adoption is lagging; just 40% of patients accessed their online records at least once during 2020, though this number represents a 13 percentage point bump from 2014, according to the Office of the National Coordinator for Health IT (ONC). 

Research shows these adoption figures plunge across specific patient populations, revealing stark racial gaps in portal usage. A patient study conducted by the Ohio University School of Medicine found that Black patients were 40% less likely to use patient portals than white patients. 

Additionally, national market research conducted by Upfront Healthcare and Ipsos found:

• Hispanic patients were less likely than white patients to use portals to check their lab results (35.1% vs 56.5%); 
• Black and Hispanic patients were less likely than white patients to use portals to access medical records (30.8% and 27.6% vs. 42.2%); and 
• Both minority groups were less likely than white patients to use portals to communicate with their care providers (26.8% and 21.2% vs. 36.8%).  

Barriers to patient portal access 

Because race and ethnicity are social constructs and so tightly coupled with systemic inequities in the United States, we must dive deeper into these initial warning signs. This will enable us to better understand barriers and root causes of systematic differences in digital tool usage — and develop strategies for potential solutions and interventions. 

Despite slight increases in patient portal usage, there are multiple potential barriers to equitable use, including: 

Broadband Internet Access: According to a Pew Research Center survey, Black and Hispanic adults are less likely than White adults to have access to broadband internet at home. Of note, while smartphone ownership doesn’t vary substantially by race, 25% of Hispanic and 17% of Black adults rely solely on mobile device data and do not have access to broadband at home compared to 12% of White adults.     

Digital Literacy: Many portals are not designed with usability and accessibility in mind, and patients underserved in healthcare often experience unnecessary technological setbacks. The burden is put on the patient to proactively log in and sort through a number of screens to access the information they need.    

Lack of Awareness: Studies have found that Black and Hispanic patients are offered patient portal access less often than their white counterparts. While 65% of white patients said their provider offered them access to the patient portal, only 54% of Black patients and 49% of Hispanic patients reported the same. 

Health Literacy and Language: Patient portals contain complex medical information, and some may only be available in English, making them difficult to navigate for patients with low health literacy and limited English-speaking skills.  

History of mistrust: Trust and privacy concerns may also play a role in Black patients’ wariness in using portals, as they may be influenced by the systemic racism Black Americans have historically encountered within the healthcare system. In one study, Black and Latino patients preferred to speak directly to providers and were more likely to cite privacy and security anxieties as reasons for portal nonuse. 

Lack of Personalization or Need: Uptake and sustained engagement may also be low because patients do not see a need for the patient portal. In a 2020 survey, 63% of patients said they did not access their portal because they didn’t have a need. 

More work is needed to address existing inequities

To address the existing inequities in patient portal use, healthcare providers and organizations must take steps to ensure that all patients have equal access to these platforms. 

It’s critical to ensure health systems are not throwing yet another piece of technology at patients without consideration of how it meets patient needs or fits into the existing patient experience. This includes a reexamination of the initial value of patient portals and whether current tools are meeting the mark. It’s now nearly 14 years following the passage of the 2009 HITECH Act, which provided incentives for health systems to adopt patient portals in the first place. 

If patient portals are being optimized to deliver a cohesive and better patient experience, providing digital literacy training and ensuring that patient portals are available in multiple languages is necessary. Health systems can promote portal usage in all communications, and help patients understand the value portals provide in meeting their healthcare needs — for example, scheduling a visit or refilling a medication.  

Providers should also work to build trust within Black and Hispanic communities and address cultural barriers to their portal use. Providers must recognize which patient populations are not likely to utilize the patient portal and encourage them to do so by directly addressing their specific concerns. 

One way to build trust is to personalize communications with patients. Healthcare is extremely personal, so patient communications and outreach should follow. Tailoring messages to the patient’s relevant needs and perceived fears makes them feel seen as an individual person, not just a number, and encourages engagement.  

Today, advanced technologies and patient engagement platforms, as a complement to the portal, are elevating personalization and ensuring that the experience is inclusive for all patients. These technology solutions can create more tailored content that addresses the barriers to portal usage and can help inspire patient confidence and trust within the healthcare system.  

About Lindsay Zimmerman, Ph.D., MPH VP, Bartosch Patient Activation Institute, Upfront Healthcare

Lindsay Zimmerman, PhD, MPH is a healthcare expert bringing together rigor and humanity to solve our most complex social and public health challenges. She believes in a true interdisciplinary approach to problem-solving, represented by her background in academic research, data-driven technologies, and patient-focused care models.

Prior to Upfront, Lindsay led large-scale projects at health systems, non-profits, and innovation centers focused on optimally leveraging social factors to proactively engage patients to become partners in their healthcare. Lindsay also co-founded Socium Health, an NSF-funded collaborative to research and prototype patient engagement and care coordination solutions. She has her Ph.D. in Health Informatics from Northwestern University and a Master of Science in Public Health from the University of Illinois Chicago in Epidemiology.

What You Should Know:

• 2023 started off with the hallmarks of a rebound year. While Q4 2022 signaled the tail end of the digital health funding cycle, January and February funding numbers began to suggest that sector investment was slowly but surely inching back upwards. Inflation was easing ever so slightly. Investors were rediscovering their confidence and launching new projects, signaling optimism in the sector, according to a new Rock Health report.
• However, recent news—the collapse of Silicon Valley Bank, the seizure of Signature Bank, Moody’s downgrading of bank credit ratings, and another Fed rate hike—was a stark reminder that the choppy waters of 2022 aren’t over yet. 

Key Trends and Insights from Q1 2023 – Digital Health Funding

There’s no denying that Q1 2023’s economic conditions, bank scares, and regulatory changes have digital health startups of all sizes nervous, whether they’re trying to raise their next funding round or waiting for the right time to exit.

The following key trends from Rock Health’s report are a review of the venture, banking, and policy waves breaking within digital health, coupled with insights regarding the volatility of the modern-day regulatory landscape, how the financial market seems different for everyone, and how small-scale startups have it the hardest.

Q1 Funding Soars, But 2023 May Struggle to Catch Up to 2019

Q1 2023 U.S. digital health funding closed with $3.4B across 132 deals, with an average deal size of $25.9M. While this quarter exceeded both Q4 2022’s $2.7B and Q3 2022’s $2.2B funding pots, Q1 isn’t enough to signal a new “bull run.” If funding for the next three quarters matches the average funding across the prior three quarters, 2023 is on pace for the lowest level of annual funding since 2019. The truth remains that the founder-friendly market of 2021 and early 2022 has tilted sharply toward investors.

Notably, within its $3.4B raised, Q1 2023 saw heavy representation of mega deals. After only six digital health raises over $100M across Q3 and Q4 2022 combined, Q1 2023 logged six megadeals from Monogram Health ($375M), ShiftKey ($300M), Paradigm ($203M), ShiftMed ($200M), Gravie ($179M) and Vytalize Health ($100M)—accounting for 40% of the quarter’s total digital health funding.

Silicon Valley Bank’s Collapse

SVB’s collapse nearly precipitated a liquidity crisis in the sector, and concerns circulated that startups might need to engage in distressed debt buys or raise emergency bridges—possibly with “lender-friendly” terms or at slashed valuations—in order to secure working capital. It’s worth pointing out that not all digital health startups carried the risk burden equally. Startups with well-established investors were more likely to have the assurances of cash floats and level-headed perspectives from advisors who have been around the block a few times, while those with greener syndicates were left unsure of whether their own funders could even weather the storm.

After seeing their investors operate in crisis mode this March, several digital health founders may feel compelled to re-evaluate their cap tables and possibly move forward with different investors for future raises. Startups were left with another conundrum after SVB’s collapse—which banking institution to choose next. SVB was known to offer startups loans during high-growth periods and took on companies that were too early to demonstrate product-market fit. While late-stage startups likely have the capital and credit requirements to bank with high-street institutions, nascent teams or those based outside of the US will need to turn to more restrictive and expensive alternatives to establish financial operations and secure loans.

The IPO Market and Q1

Q1 2023 logged another quarter with zero digital health IPOs. Digital health stocks started 2023 trading almost 50% lower than they did at the start of 2021, pushing some recently-exited players like Pear Therapeutics to explore going private. No later-stage digital health players felt compelled to venture into IPO territory this quarter, fearing that the market would yield bottom-barrel issue prices.

In December 2022, healthcare data startup Komodo Health raised $200M alongside a restructuring plan that laid off 9% of its workforce. In January, hybrid care provider Carbon Health closed a $100M Series D while also trimming its RPM and chronic care divisions and completing its second round of layoffs.1 That same month, nurse staffing solution Shiftkey announced its $300M raise, accompanied by a quartet of new executives. Connected fitness startup Tonal is rumored to be pursuing private funding at a $200M-$300M valuation, a nearly 90% decline from the $1.9B valuation it floated back in September 2022.

Regulatory Developments and Adapting Digital Health Startups

If circumstances weren’t treacherous enough, digital health startups are bracing for impending regulatory changes. In Q1 2023, an acronym soup of federal agencies (FDA, CMS, DEA, FTC) announced preliminary steps and timelines for refining policies across digital health. These revised guidelines have far-reaching impacts, affecting telehealth reimbursement, controlled substance distribution, healthcare service pricing and rebates, and patient data management. Top of mind is the announcement to end the COVID-19 public health emergency (PHE), which is slated to expire on May 11, 2023.

In the realm of telehealth delivery—perhaps the biggest area of healthcare expansion during the pandemic—telemedicine will officially lose its status as an excepted benefit2 and certain federal penalties for HIPAA non-compliance of telehealth platforms will be reinstated. In alignment with PHE’s conclusion, other government bodies are rolling back pandemic-era measures. State agencies are beginning to unwind expanded Medicaid coverage in conjunction with the expiration of a 2020 federal provision requiring continuous enrollment.

States resume disenrollments, anywhere from 5 to 14 million Americans stand to lose Medicaid coverage and associated benefits, with the hardest-hit populations being low-income youth and working individuals without employer-sponsored plan access. In terms of data privacy and security, Congress introduced the Upholding Protections for Health and Online Location Data (UPHOLD) Privacy Act to regulate companies’ use of health data, the FTC settled investigations into BetterHelp and GoodRx with hefty fines, and the FDA enhanced cybersecurity requirements in regulatory applications for medical devices. Finally, on the billing and coding front, CMS issued its 2024 Medicare Advantage Advance Notice to root out aggressive upcoding practices.