What You Should Know:

• Today Innovaccer Inc. announced that Curana Health, an innovative, fast-growing healthcare organization on a mission to improve the health, happiness, and dignity of senior living residents, is expanding its partnership with Innovaccer to meet strong market demand for its services, and to support the expansion of its value-based programs for high-risk populations nationwide.
• Last year Innovaccer announced that Curana Health had chosen Innovaccer’s Best in KLAS data and analytics platform, care management solution, and point-of-care physician engagement solution to create a new technology platform purpose-built for senior living communities. Curana Health is a provider-led, primary and post-acute organization, that works with Skilled Nursing Facilities, Assisted Living Communities, Memory Care Communities, and Life Plan Communities / Continuing Care Retirement Communities

Expanding Access to Value-Based Care Across the Nation

Since then, Curana has undergone significant growth, expanding its presence to 30 states and establishing partnerships with over 1,100 senior living communities, including various types of care facilities such as skilled nursing facilities, assisted living, memory care, life plan communities, and continuing care retirement communities. This expansion has provided over 750 healthcare providers with the opportunity to excel in value-based care delivery. Curana has achieved this through a provider-led medical group, Medicare Advantage health plans, a Medicare Shared Savings Program (MSSP), and a newly formed ACO REACH organization. Notably, Curana’s MSSP, known as Elite Patient Care ACO, performed exceptionally well in its inaugural year, ranking in the top 1% of all ACOs. It achieved impressive gross savings of $2,235 per beneficiary per year, marking the highest per beneficiary per year savings for a first-year MSSP ACO since 2012.

“We’re committed to technology innovation that improves the experience, communication, and clinical decision-making of our networks’ care teams to enhance health outcomes; and support the performance of value-based contracts among one of the industry’s highest risk populations,” said Todd Tyler, CIO of Curana Health. “We chose the Innovaccer platform so we could work with not only our own EHR, but with any EHR or systems we need to integrate to extend the Innovaccer technology platform. Innovaccer is enabling us to scale population health management for more and more partners in our footprint, and to support innovative VBC models, such as our new ACO REACH program. With the Innovaccer platform, we can unify patient records, share care plans, and maintain continuity of care across all care settings and value-based contracts as fast as we grow.”

Innovaccer and Curana are joining forces to enhance care access, quality, and outcomes for high-risk populations. They’ll achieve this by consolidating patient records across various systems, automating care management, enabling remote patient monitoring, addressing social determinants of health, identifying at-risk patients with AI analytics, closing care gaps, enhancing clinician experience, and more.

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.

What Should Know: 

– UnitedHealthcare has announced the Surest™ health plan leads to more preventive care, improves satisfaction and lowers costs for members and employers.  

– UnitedHealthcare’s Surest, which eliminates deductibles and offers upfront pricing information to people in advance of treatment, helps members more frequently access preventive care services and lower out-of-pocket costs, according to recent data. 

– Hundreds of employers with a combined workforce of more than 4.4 million employees have opted to offer Surest as an option for 2024, including 1 in 6 of UnitedHealthcare’s national accounts customers – making Surest the fastest-growing plan among UnitedHealthcare’s commercial offerings.

What You Should Know: 

– Ounce, a company bridging the gap between health and housing has raised a $5.2M seed round co-led by Meridian Street Capital and Flare Capital Partners with participation from Chelsea Clinton’s Metrodora Ventures Wilshire Lane Capital, Chris Nassetta (Hilton CEO), Taylor Justice (Unite Us cofounder), and others.

– Ounce Community Health Workers (CHW) currently serve more than 2,000 D.C. residents, helping them enroll in Medicaid, apply for energy assistance, schedule PCP and pediatrician appointments, avoid eviction, and connect with community resources for transportation and nutritious food, among many other services. 

Building Bridges Between Housing and Health

Today, more than 300,000 D.C. residents are enrolled in Medicaid and approximately 27,000 low-income D.C. households face housing hardship. Making matters worse, as of June 21 this year, Medicaid redeterminations have resulted in 3,000 D.C. residents losing access to critical health coverage. Access to health insurance and a safe and affordable place to call home is fundamental to many areas of life, including school performance, job retention, physical and mental health, and economic security. Medicaid managed care organizations (MCOs) are committed to improving health outcomes for this population, but struggle to engage them due to factors such as invalid or frequently changing contact information, lack of trust in the healthcare system, limited access to transportation, low health literacy, and inadequate childcare support. 

To address these issues, Ounce embeds its team of trained Community Health Workers (CHWs) within affordable housing properties where they directly connect and regularly engage with residents, building trusted relationships over time. The CHW model is widely recognized as playing a crucial role for Medicaid beneficiaries by providing personalized support, education, and guidance that empowers individuals to navigate complex healthcare systems, adhere to treatment plans, and address social drivers of health, ultimately leading to improved health outcomes.

Ounce CHWs evaluate residents for gaps in care, host onsite health clinics and screenings, enroll residents in public benefits like Medicaid, SNAP and disability, and connect residents to healthcare and social services, including scheduling primary care and pediatric appointments or helping residents apply for rental assistance. This approach benefits not only residents and Medicaid MCOs, but also property owners, who choose to work with Ounce because it’s a scalable solution that can help them demonstrate positive health and social impact from their property services.

“There is an enormous gap between health plans and where their members spend over 70 percent of their time – their homes. Our highly trained team leverages technology to conveniently engage people where they are, deliver impactful services, and lower healthcare costs for residents and insurers,” said Rachel Munsie, co-founder and CEO, Ounce. “Our success is largely due to the trusted relationships we’re uniquely able to build with residents and the convenience of our services, all delivered within the existing community infrastructure. Our integration with the properties and our proximity to residents gives us the opportunity to quickly intervene with support when we see red flags like eviction notices or other indicators for housing instability, which has clear links to healthcare outcomes.”

Initial Service Launch in Southeast DC

Ounce chose to launch its services in Southeast D.C. before expanding to the rest of the city. Southeast D.C., which is predominantly Black, has higher rates of poverty and gun violence due to chronic underinvestment and has been identified as both a food and healthcare desert. Despite these challenges, Ounce was able to engage and enroll over 30 percent of residents into its program just months after launching, immediately expanding access to care and critical benefits where it’s needed most. Ounce has since maintained engagement rates that are significantly higher than the single-digit rates typical of traditional care models. As a result of this high level of direct engagement, residents who get support from Ounce receive, on average, multiple services at a time. High engagement rates can also be attributed to Ounce’s practice of recruiting CHWs who are from or deeply familiar with the communities they serve.

Strategic Partnerships with with AmeriHealth Caritas DC

In addition to its close partnership with AmeriHealth Caritas D.C., Ounce has partnered with the National Housing Trust, a nonprofit organization that focuses on preserving and improving affordable homes for low-income families. “By combining our expertise in affordable housing preservation with Ounce’s innovative approach to resident services, we are creating a transformative impact on the well-being of our communities, ensuring that quality housing and comprehensive health support go hand-in-hand,” said Priya Jayachandran, CEO of the National Housing Trust. 

Ounce also works closely with D.C.-based providers such as C3Cares and Urgent Wellness, along with several local community organizations including: Bread for the City, Capital Area Food Bank, Giant Healthy Living, Latin American Youth Center, Martha’s Table, So Others Might Eat, UPO Workforce Institute, and many more.

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.

What You Should Know:

• The American Telemedicine Association (ATA) announced this week that its CEO’s Advisory Group on Using Telehealth to Eliminate Disparities and Inequities is releasing three new tools this week, to inform ways in which telehealth can impact disparities and inequities.
• All three tools were released today, to commemorate the third annual Telehealth Awareness Week. This year’s events will highlight the value telehealth brings to patients and helps to expand access to quality care, how virtual care is addressing many of the challenges faced by healthcare providers, and its role in building a modern, omnichannel care delivery system.

Improving Accessibility to Healthcare Via Telemedicine

“We launched the advisory group in 2021 to address the unique ways telehealth could be used to eliminate health disparities in the U.S. We are confident that the tools we are launching this week will support decision-making related to targeting and funding interventions that improve health in communities,” said Ann Mond Johnson, CEO of the ATA. “Our Advisory Group is comprised of national healthcare leaders uniquely focused on health disparities. Led by co-chairs Kristi Henderson, DNP, Yasmine Winkler and Ron Wyatt, MD, and facilitated by David Smith, CEO of Third Horizon Strategies, their groundbreaking work will further position our community to  leverage telehealth to eliminate healthcare disparities.”

1. The Digital Infrastructure Disparities Score and Map uses a newly created composite measure designed to score a community’s digital infrastructure on a scale of 1-100.
2. The Economic and Social Value-Added Calculator tool is designed to scope the cost of telehealth-based clinical or social interventions, including estimates for the total value of an intervention created in favor of payers, providers, government, and business. The calculator analyzes the capital and operating costs for these interventions, including technology platforms (telehealth solutions) and funding needed to ensure community members have solid, reliable, and contiguous broadband connectivity.
3. The third tool is a toolkit summarizing all resources the group has released to date, including a new roadmap to address inequalities in the delivery of healthcare information and services with a focus on both access and improving outcomes.

While the need to address social determinants of health (SDOH) is definitely not new, 2023 marks the first year SDOH is codified into national and statewide value-based payment program mandates. These mandates are designed to hold Managed Care Organizations (MCOs) and Accountable Care Organizations (ACOs) accountable. While the rollout of SDOH code sets across our healthcare ecosystem is one phase, alone it’s not enough. The next phases are even more critical: codes must be collected, used, reviewed, and acted upon within value-based payment programs to ensure patients realize the benefits of a more inclusive and accessible healthcare system. 

The newest value-based payment program purposely designed to address SDOH is the ACO Realizing Equity, Access, and Community Health (ACO REACH) model, launched by the Centers for Medicare & Medicaid Services (CMS). ACO REACH participants are required to develop a health equity plan to identify underserved patients within their population and implement initiatives to measurably reduce health disparities. While this is not the only requirement, it will challenge ACO REACH participants to collect complete and accurate SDOH data. 

For health plans, they’ll need to sharpen their data collection processes to encompass critical non-medical information. Traditional methods of data collection, such as complex care case management assessments, are no longer sufficient. Payers must have access to and include publicly available data collection aimed to offer a more comprehensive view of a member’s health and social circumstances to comply with CMS guidance. The data payers collect must also be consistent and precise across populations. 

Without standards-based data collection, coding, and uniform information sharing of SDOH data between healthcare providers, health plans (including MCOs) and community-based organizations, it will be extremely difficult — if not impossible — to effectively improve health outcomes.  

States like Massachusetts, New York and Oregon, are leading the way in addressing SDOH data use in value-based payment programs for Medicaid beneficiaries. These early adopters are highlighting how the collection and use of SDOH data leads to better and more equitable health outcomes and the industry is watching. We’ll all learn from how each state addresses the challenges of collecting complete, accurate, standards-based SDOH data, as well as how that information is shared with providers and community-based organizations. With insights from these states, the industry will be better equipped to develop consistent approaches that lead to improved health outcomes and increased health equity. 

While underutilized, one standards-based solution to the challenge of quantifying social, economic, and environmental factors known to affect health and health-related outcomes already exists. In 2021, the CMS Office of Minority Health published data on the use of ICD-10-CM Z codes. Since 2016, Z codes have been available to capture SDOH data at the point of care delivery. Providers submitting claims using ICD-10-CM Z codes to document SDOH have been steadily increasing, from less than 946,000 claims in 2016 to more than 1.2 million in 2019, according to the CMS report. Though that may seem like a large number, as a proportion of the 33.1 million people enrolled in Medicare that year, less than 2% had claims that incorporated Z codes. 

Our current Z code submission rate, while limited, is a great step forward to capture standards-based SDOH data at the point of care for our nation’s most at-risk people; however, more widespread adoption is required to comply with the SDOH requirements mandated in CMS and state value-based payment programs. Look to Standards Development Organizations (SDOs) like the Council for Affordable Quality Healthcare (CAQH) to drive this adoption by adjusting data collection operating rules that define key infrastructure and data content requirements.  One example of this work can be standardizing the submission of ICD-10-CM Z codes on claim transactions to support SDOH data capture at the point of care.  Millions of these claim transactions are already being passed between payers and providers every day.

Integrating SDOH data into value-based payment models also comes with some challenges – beyond figuring out a standardized approach that works. Data privacy and security concerns are paramount, with additional information being collected on individuals. Additionally, there is an abundance of interoperability issues to be addressed at the health IT system level to ensure collaboration and in order to guarantee the seamless exchange of data for maximum outcomes.

As we look ahead, standards-based SDOH data collection — from claims, publicly available information, data from care assessments, integration with clinical notes in electronic medical records, and more — will be essential to remove the barriers to care that value-based payment programs were designed to eliminate. 

We all aim to build a healthcare system that treats the root cause of health disparities, ultimately leading to healthier communities and better health outcomes for everyone. As leading ACOs and MCOs demonstrate the power of harnessing SDOH information to create more equitable and effective care models, the transformative potential of SDOH data promises to reshape the entire healthcare landscape for all. 

About Michael Pattwell

Michael Pattwell is the principal business advisor at Edifecs, a software provider that enables payers and providers to maximize the performance of their value-based contracts and offerings. Michael has more than 30 years’ of experience in health care and currently chairs national value-based payment workgroups at WEDI, CAQH and DaVinci. An author of several articles on our national transition to a value-based payment model and our industry focus on population health management.

Massive disparities continue to plague healthcare in the United States. Many Americans do not have access to quality care, leading to higher rates of diseases like diabetes, hypertension, cancer, and obesity. Health equity means ensuring that health resources and services are accessible and affordable for everyone, regardless of gender, sexual orientation, race, geography, ethnicity, or financial circumstances. 

Health equity allows people to lead active and productive lives, reduces the healthcare burden on the government, and contributes to economic growth. By one estimate, healthcare improvements accounted for one-third of the economic growth of developed nations over the last century. Achieving health equity presents an urgent challenge that demands attention from all stakeholders.

However, actual medical care accounts for 20% or less of what affects population health. The remaining 80% comes from the social determinants of health, such as public safety, the availability of stable jobs, access to green spaces, cultural practices, and more. For example, people living near industrial zones tend to have lower life expectancies or are prone to certain diseases. Rural communities may lack easy access to preventive care and screenings. Language barriers may deter certain populations from finding accurate information. The costs are astronomical. Health inequity costs the nation $320 billion a year, a figure that could balloon to more than $1 trillion by 2040, according to Deloitte.

Several roadblocks hinder progress in achieving health equity, of which the perennial issues of funding and staffing are often in the spotlight. But there is another hurdle that is just as significant, and that is the lack of quality data on these social determinants. Data-driven insights are crucial in understanding health disparities. By comparing quality-of-care data with population, income, and ethnicity across the U.S., we can identify gaps and define appropriate next actions. 

Digital technology has transformed many industries in recent years. However, healthcare is often left behind, with many healthcare organizations still struggling to collect important data. The Institute for Healthcare Improvement found that while 59% of health systems named health equity as a top priority in 2021, 38% of those health systems pointed to inconsistent data collection as a top barrier to achieving that goal. And only 25% of U.S. hospitals screen patients for the social determinants of health and other markers.

Much in the same way “food deserts” limit people’s ability to choose healthy eating options, the healthcare industry faces a “data desert” that has real-world repercussions. There is no readily available database on the disease burden by population segment. Doctors have no access to data about the social determinants of health, hampering their ability to tailor care to patients. With incomplete data, certain populations are overlooked during the development of new drugs. It’s not a stretch to say that your phone knows more about many of these key factors than your doctor.

The industry will never topple barriers to health equity without changing the way providers and payers approach health data. For example, many companies are not aggregating the data they already have to generate insights. Additionally, sharing information between payers and providers is inefficient, leading to physician and patient fatigue. 

However, we can learn and build on efforts already underway to address this. Importantly, the Centers for Medicare & Medicaid Services (CMS), the largest payer in the country, whose services touch 170 million people, is rolling out a comprehensive 10-year initiative to understand the causes of disparities, improve accessibility to care, and better address the social determinants of health. The first priority is to expand the collection, reporting, and analysis of standardized data. 

It’s not just large-scale initiatives that will help. Payers and providers can implement small changes that can do a lot of good. Technology can play a crucial role in advancing health equity by bridging the data gap. Telemedicine connects underprivileged populations with remote, real-time care. Smart devices and mobile health apps empower individuals and make interactions more seamless – from viewing test results to reminders to get vaccinated to sending surveys on care quality. Responsible AI can remove biases, improve diagnostics, and enhance clinical decisions. Aggregation and integration of business and patient data can help create a deeper understanding of patients. Digital and process automation can alert providers to non-compliance. Data analytics can unearth patterns from real-world data to better understand the root causes of health inequities and provide targeted interventions.

Attaining health equity means we must work collectively to break down barriers and ensure that every individual has access to the care they need. By stepping up efforts to collect and share data on the social determinants of health and embracing technology to bridge the gaps, we can create a healthier future for all Americans. It’s time to join hands and take meaningful steps toward a more inclusive and equitable healthcare system.

About Alok Mandal

Alok, the head of healthcare consulting for Virtusa, specializes in healthcare-focused enterprise architecture, digital process automation (DPA), data engineering, robotics, artificial intelligence (AI), and cloud-first strategy.

In a society where so many want more—more money, more time off, more adventure—few stop to question the logic of insatiably wanting “more.” Perhaps, no place does the consequence of wanting more negatively impact people than with healthcare treatments. Medication use, for example, shows clear dose-response curves, where over-use can have fatal consequences; negative consequences and death also can result from too much chemotherapy, radiation, antibiotic use, or complications from unnecessary surgical procedures. Within behavioral healthcare, negative outcomes have been across all populations and treatment interventions. Patients receiving cognitive behavioral therapy, for example, who fail to show significant change within an expected number of sessions have an incredibly low likelihood of achieving clinical behavior change making further therapy a misallocation of resources and potentially harmful if it prevents the patient from finding a more effective treatment. As a result, medical and behavioral health treatments often have well-defined standards of care that outline minimum and maximum levels of treatment to optimize effectiveness, with one exception -autism spectrum disorder (ASD). Here’s why stakeholders need to figure it out… 

The prevalence of autism has continuously risen over the past 20 years along with a continued shortage of Board Certified Behavior Analysts (BCBA) to provide Applied Behavior Analysis (ABA) treatment, the only evidence-based, empirically proven therapy for ASD. In a rush to meet the resulting access issues, the elephant in the room that people look past, however, is the lack of standardization and high variability for recommending treatment intensity individuals with autism clinically need. The result is a system where treatment recommendations can range from focused to comprehensive, from 5-to-40 hours per week, and for between 18 months to 5 years—often under the assumption that more hours will always translate to more progress. But is the old adage that “more is better” uniquely applicable to ABA? 

There is not a “one size fits all” approach within ABA and it’s important to consider various factors which may lead to some undesirable effects that comprehensive treatment may have on families. Recommendations of 30+ hours/week pose a lengthy list of flags, questions and concerns including the financial impact on the family, coordination of care and transition planning.  Having a therapist in your home for several hours every day is seen by many as an intrusion of privacy. It also takes away precious time for other social/community involvement, reduces a parent’s ability to work, and can lead to the deterioration of parent-sibling and marital/couple relationships. Children receiving ABA in clinics have added impact from the time driving back and forth, limited parental insight into what their child does all day, and their treatment gains may not generalize to other environments. In short, therapy-life balance is important for the child in treatment, their parents, and their siblings. 

More controversially, several pieces of evidence suggest some autistic individuals have better treatment outcomes with fewer hours directly contradicting the “more is better” assumption from above. The key component here is that treatment recommendations are individualized relative to each patient’s baseline skill levels (skillset prior to receiving treatment) and target skills that the providers believe to be most important to improving the child’s quality of life. For example, if the goal is to optimally increase communication skills, comprehensive services may be the answer. If the goal is to reduce general ASD symptom severity and parental stress, more ABA may not be the answer. Finally, research examining dose-response relationships suggests the duration of treatment has a stronger impact than intensity on outcomes (here’s another example for adaptive skills, motor skills, and executive functioning). 

The ask and answer: Individualize treatment tailored to optimize ABA effectiveness for each child! No more blanket business models at 35 hours/week for every child. No more requesting excessive hours “just in case” of cancellations and school vacations. No more requesting hours to substitute for school enrollment. Instead, services should be outcome-based and guided by clinically validated data to drive hours of recommendations and treatment to best meet individual goals. Providers have good intentions but also have conflicts of interest. Let’s use patient characteristics, goals, skill sets, and historical data on how ABA actually improves the lives of each unique client to determine precise, individualized treatment intensity recommendations that optimize outcomes and pay providers accordingly. Examples of how this can be done already exist here, and here, and here. All it takes for all individuals with autism to benefit is to start questioning the assumption that “more is always better.”

About Dana D’Ambrosio, MS, BCBA, LBA

Dana D’Ambrosio leads Clinical Development for RethinkFutures. She is a New York state-licensed and Board-Certified Behavior Analyst. She brings over a decade of clinical knowledge, with experience spanning from direct patient care in various treatment settings to utilization and care management within the payor realm. She specializes in the creation and enhancement of technology solutions utilized by providers and health plans, to ensure best practice, high quality, coordinated care and streamlined review processes for all parties. 

Far too often, substance use disorder (SUD) is viewed as an “acute condition,” one that can be “cured” with short-term treatment, such as a week-long stay in a detox facility. This could not be further from the truth. The failure to understand the science behind addiction leads individuals who are undertreated or inappropriately treated to return to use again and again.

SUD is not a moral failing. It is not a behavioral issue. It is not a choice. The leading health organizations around the world agree―based on a multitude of scientific research―SUD is a chronic brain disease rife with biological underpinnings. As such, the genetic component of SUD should not be a surprise. If you have addiction in your family, you are approximately 50% more likely to be affected, too.

SUD can be managed very successfully―and for a lifetime―if individuals in treatment, in need of treatment, and in recovery (along with their loved ones) fully understand the need to manage it as a chronic disease. When individuals harbor misconceptions about what addiction is, they may not seek treatment, they may not seek the right treatment, or they may not continue in treatment. Self-detox is not a viable option and, in some cases, can be fatal.

When viewed as a behavioral issue or a choice, there is a stigma surrounding SUD that can prevent individuals in need of treatment from seeking care. According to the 2021 National Survey on Drug Use and Health conducted by the Substance Abuse and Mental Health Services Administration (SAMHSA), 46.3 million Americans are struggling with substance use disorders, but only a small fraction—6%—receive treatment.

For those who do seek treatment, many expect SUD to be remedied with a “one and done” approach, which is not realistic. Individuals in recovery then internalize that thinking and let their guard down, assuming it is not necessary to continue daily practices that support long-term recovery. The National Institutes of Health reports the relapse rate for SUD is between 40 and 60%.

In addition to understanding recovery is a long-term process, we must also recognize that clinical treatment alone is not enough. Individuals with SUD need ongoing psychosocial support from their families, their communities, and their employers. Recovering from addiction requires rewiring and retraining the brain, and it takes hard work and a significant amount of effort. Acknowledging this better serves patients and families going through the early stages of recovery, as well as in managing this disease long-term.

In the ideal world, unhealthy substance use would be identified early on, and intervention by a family member or healthcare provider would be delivered with compassion and without judgment. Too often the opposite is true, and when people seek medical or mental healthcare, they do not feel cared for.

While it may take many years for society to fully understand and identify SUD as the chronic condition it is, there is a particular treatment component―one that too few are providing or utilizing―that we can leverage immediately to support more individuals in their recovery journey. That component is the integration of peer support into every level of care.

The presence of peers throughout the recovery journey―peers who have overcome SUD and mental health challenges themselves and can inspire hope, offer compassion, and provide guidance along the way―is a complete gamechanger. This manner of support, especially during the most challenging moments, can mean the difference between recovery and return to use. The outcomes, which are clinically evident, are extraordinary.

It is frequently touted that “connection is the opposite of addiction.” And that feeling of connectedness is essential to long-term recovery. My hope is to build greater awareness and implementation of this peer support component in our collective mission to combat our country’s SUD crisis, and to ensure every individual has access to the tools needed to achieve lifelong recovery.

About Hans Morefield

Hans Morefield is Chief Executive Officer at CHESS Health, proudly leading a team that brings innovative and evidence-based solutions for addiction management and behavioral health to healthcare providers, health plans, and the public sector. CHESS Health’s platforms help get more patients into treatment for substance use disorder, increase adherence to treatment plans, reduce the rate and severity of relapses, and lower the total cost of care. Prior to joining CHESS Health in 2017, Morefield served as Vice President of 

Population Health and Care Coordination at Experian, where he led the team delivering the successful CareCertainty Platform to ACOs, health plans, and risk-bearing health systems nationwide. He previously served as Senior Vice President of Strategic Development at SCI Solutions, responsible for product management and strategic partnerships. Morefield earned his BA from Kalamazoo College, where he has served on the Board of Trustees for over 15 years. He also serves as a volunteer on the Community Relations Committee for Stepping Stones, the Historic Home of AA and Al-Anon Founders Bill and Lois Wilson.

What You Should Know: 

• UnitedHealthcare Community Plan of Indiana has provided $2.85M to four organizations working to advance the direct service health workforce in the state. 
• Direct service workers (DSWs) are essential in providing care to long-term services and support recipients who choose to age and live in their homes, especially those in underserved communities and rural areas. DSWs include certified nursing assistants, home health aides, direct support professionals, personal care aides and other nonlicensed workers.
• These donations are part of UnitedHealthcare’s commitment to making a positive impact on the lives of the most underserved and, particularly, the population aging at home.

Direct Service Health Workforce Grants

Donations have been provided to:

• Indiana Association for Home & Hospice Care — $1,100,000 for an assistance program that provides benefits to DSWs such as funding for child care, car repairs, gas money, financial well-being and other needs that may hinder their ability to be fully involved in their professional lives.
• Ivy Tech Community College — $1,000,000 for a Direct Service Worker Pathway program that trains and prepares juniors and seniors in high school to enter the direct service workforce right away after high school while also developing stepwise career development opportunities.
• Mobile Integrated Health-Community Paramedicine — $250,000 to employ community paramedics in Montgomery County to improve home health for individuals age 60 and over through a program that will focus on four areas: improve care coordination on 911 calls related to falls; enhance referrals to community paramedics; increase completion of wellness visits and preventive care; and increase use of telehealth to assist with management of chronic conditions.
• Indiana University School of Medicine Geriatrics — $500,000 for a Project ECHO initiative and Learning Collaborative to share know-how among providers. Project ECHO — Extension for Community Healthcare Outcomes — is a model that focuses on building provider capacity by connecting experts and specialists to local providers, fostering collaboration for increased knowledge. This model encourages a virtual, bidirectional exchange of information between peers and subject matter experts.

What You Should Know: 

• ZeOmega announced it has integrated its Jiva Population Health Enterprise Management Platform’s SDOH Social Care solution with Microsoft Cloud for Healthcare built for Microsoft Azure. 
• The integration empowers healthcare organizations with Azure to achieve increased access, seamless compatibility, and unmatched administrative efficiency, enabling smoother processes and freeing healthcare professionals to prioritize exceptional patient care. SDOH takes center stage with data visualizations for informed decision-making and understanding patient needs. The measurement dashboard provides a comprehensive view of SDOH outcomes, empowering continuous improvement for optimized patient outcomes.

Integration Benefits

Social determinants of health (SDOH) such as lack of transportation and food insecurity are said to impact 50 percent of health outcomes. When patients face hurdles in adhering to care guidelines, even minor conditions can spiral out of control and lead to costly hospitalizations and procedures. The breadth and depth of ZeOmega’s SDOH data sources gives care coordinators and clinicians a complete, at-a-glance view of social needs by area, population, and individual so they can strategize and deploy appropriate interventions. Integration with Cloud for Healthcare and Microsoft Power Platform will enable case managers, clinicians, and other healthcare professionals to work from a single unified platform where they can access high-level visualizations of social, clinical, and behavioral information and take appropriate action within their existing workflows.

“Our SDOH solution integrated with Microsoft Cloud for Healthcare will help clients deliver even more effective and efficient member engagement as they identify risks and needs across geographic areas, populations, and at an individual level,” said Pravin Pant, MSHI, Vice President of Advanced Analytics, ZeOmega. “Equipping our robust platform with the capabilities of Microsoft Cloud for Healthcare and Power Platform functionality expands healthcare leaders’ access to actionable insights to develop precision strategy, and improve patient outcomes and ROI for their organizations, all from one unified workflow.”

What You Should Know: 

• Virgin Pulse launches a five-week global loneliness challenge for employers and health plans designed to foster social connections and reverse costly adverse health risks.
• Social isolation and loneliness is a worldwide problem and is clinically proven to be detrimental to individual and population health. 
• The  Striding for Connection challenge is being offered to all current clients worldwide to empower members to foster new connections while strengthening current relationships.  

Tackling Social Isolation and Loneliness

U.S. Surgeon General Dr. Vivek Murthy recently declared loneliness a public health epidemic, stating that the health risks of loneliness and social isolation increase the risk of premature death, heart disease, stroke, and mental health issues. During the Striding for Connection challenge, members will be challenged over the course of five weeks to get moving via simple, everyday actions – whether walking, running, or some other form of step-taking activity – connecting with their colleagues, friends, or family members for healthy competition and accountability. 

Designed for both introverts and extroverts, the clinically validated challenge content will also embolden and teach members to deepen their social connections in many areas of their lives, encouraging them to strike up conversations with neighbors, attend a local reading or community social group, or just nurture a relationship by acknowledging a birthday or initiating a meetup. These connections will help form a sense of community, combat feelings of loneliness, and further support their emotional and physical wellbeing.  

“Social connection is fundamental to survival. It creates a sense of belonging and is linked to reduced risk of depression and anxiety, lower stress levels, increased motivation to engage in self-care, and longer life,” said Jeffrey Jacques, MD, chief medical officer for Virgin Pulse. “Employers, health plans, and other organizations are at the epicenter of addressing this epidemic and stimulating meaningful relationships. Our new global challenge will help clients take steps to improve social wellbeing and reverse the adverse effects of loneliness and isolation worldwide.” 

What You Should Know: 

• UnitedHealthcare, today announced it is awarding $11.1 million in grants to 66 nonprofit organizations across 12 states through its Empowering Health program. 
• These grants address social determinants of health (SDoH) and help uninsured individuals and underserved communities. 
• Since launching its Empowering Health commitment in 2018, UnitedHealthcare has invested more than $62 million in Empowering Health grants reaching more than 11 million people through partnerships with community-based organizations in 30 states and the District of Columbia.

Addressing SDoH to Serve Underseved Communities

The grants will help those struggling with food insecurity, social isolation, behavioral health issues, improve health literacy efforts and more.  The grants include:

• $300,000 to Community Servings in Massachusetts to research, design, pilot and test a Step-Down Program that will support clients as they transition off a medically tailored meals program.
• $300,000 to CHRIS 180 in Atlanta, Georgia to support trauma-informed mental and behavioral health and social services through a community health worker program for low-income residents of Atlanta’s westside.
• $200,000 to Consejo Counseling and Referral Service in Pierce County, Washington to support the addition of culturally relevant wellness programming to support all aspects of mental and physical well-being for youth and families across Pierce County and rural areas.
• $200,000 to Trellis in Minneapolis and St. Paul, Minnesota to reduce social isolation among people living with memory loss and their caregivers with targeted outreach to convene community leaders to provide input, complete needs assessments, develop culturally appropriate materials, identify areas of greatest need and host community events bringing awareness to memory loss and providing practical solutions for addressing social isolation.    
• $165,000 to The Update Foundation in Syracuse, New York to support the Upstate Medical University’s “She/We Matter Program”, a peer-to-peer community outreach program designed to reduce health disparities by making health screenings, particularly mammograms, a priority among low-income Black and Latinx women.
• $65,000 to The Providence Center in Rhode Island to strengthen community-based mental health services by expanding the specialized “Emergency Services Program” for children.

Suicide is a major public health crisis in America, resulting in one death every 11 minutes, on average. 

In 2020, suicide was among the top 9 leading causes of death for people between 10 and 64 years of age. Each year, suicide and nonfatal self-harm cost the nation nearly $490 billion in medical costs, work-loss costs, the value of statistical life, and quality-of-life costs, according to statistics cited by the U.S. Centers for Disease Control and Prevention. 

For America’s veterans, the problem of suicide is even more grave. For example, in each year from 2001 through 2020, age- and sex-adjusted suicide rates of veterans exceeded those of non-veteran U.S. adults, according to the U.S. Department of Veterans Affairs (VA). Among veterans between the ages of 18 to 44, suicide was the second-leading cause of death.

To counter this serious issue, the VA in 2018 launched its “National Strategy for Preventing Veteran Suicide,” a roadmap for its plan to address the tragedy of suicide among veterans. A key piece of this wide-ranging initiative involves using synthetic data to build models that identify risk, tailor recommended treatments, and engage care to at-risk veterans as early as possible.

Why synthetic data?
Because veteran suicide is a complex, multifactored issue, VA leadership knew that achieving suicide-prevention goals would require an innovative, data-driven approach. This led to the VA employing synthetic data as one means of better understanding and reducing veteran suicide. 

Synthetic data represents a form of data anonymization. Think of it as a way of taking private patient information and enabling researchers and other users to access the information contained within the data without compromising patient privacy. This process allows for greater utility to users of private patient data by creating a statistical model and populating it with new data points, novel patients, and synthetic patients. 

The end result of that model is a data set that has the same statistical properties as the original data but doesn’t contain any of the original patients and therefore does not compromise their privacy. However, despite the absence of identifying patient information, synthetic data delivers full utility of the data because researchers can freely explore the information.

Synthetic data offers the potential to mimic the characteristics of a real dataset, without sensitive patient information, making it a good option for analyzing large but sensitive samples of real individual-level patient data. Synthetic data differs from de-identified data in that it is built from scratch, as opposed to being based on individual patient records, which means synthetic data cannot be de-anonymized. 

Predicting mental health distress
The VA has leveraged synthetic data based on the real needs of various veteran patient populations to deliver an accurate picture of overall needs, and trends across populations at high suicide risk, and to proactively identify veterans at increasing risk of a suicide attempt.

Specifically, the VA has used synthetic data in the following four areas to predict suicide risk and advance suicide prevention:

1. Predictive modeling: By clarifying and confirming the mental-health challenges veterans are confronting, predictive modeling helps the VA understand how and where to focus suicide-prevention efforts. 

2. Quality improvement: The VA is using synthetic data to understand clinical variation – the use of different healthcare services and practices – to identify which options have yielded the best outcomes in terms of mental health improvement and suicide reduction.

3. Population health management: Through population health management that relies on synthetic data, the VA can identify veterans at high risk for suicide who have been undertreated for mental health concerns. 

4. Optimizing diagnosis and treatment: With new data sets produced via synthetic data, the VA can pinpoint trends that signify undiagnosed mental health concerns that are likely to increase veterans’ risk of suicide or self-harm. 

Like many healthcare organizations, the VA experienced challenges with fragmented patient data and stringent, yet essential, privacy regulations. To overcome those roadblocks, the VA turned to synthetic data to accelerate its capabilities toward identifying and predicting veteran suicide risk and optimizing treatment. As a result of the program’s early success, the VA is expanding its synthetic data initiatives to include new models to improve treatment for heart disease, sleep apnea, and Alzheimer’s disease.

About Josh Rubel 

Josh Rubel leads MDClone’s commercial team with a focus on building relationships with public and private health systems, life science, and health plan organizations through direct sales, partners, and channel alliances. Prior to joining MDClone, Josh spent 20 years in both established and new venture healthcare IT organizations including commercial leadership roles at GE Healthcare, Optum, and Enli Health Intelligence.