What You Should Know:

• Researchers at the Icahn School of Medicine at Mount Sinai found that applying machine learning models to data collected passively from wearable devices can identify a patient’s degree of resilience and well-being. The study, published in JAMIA Open, supports the use of wearable devices, such as the Apple Watch, to monitor and assess psychological states remotely.
• The researchers note that mental health disorders account for 13 percent of the burden of global disease and that there are disparities in access to mental health care. Therefore, a better understanding of who is at psychological risk and improved means of tracking the impact of psychological interventions are needed. Wearable devices could provide an opportunity to improve access to mental health services for all people. “Wearables provide a means to continually collect information about an individual’s physical state. Our results provide insight into the feasibility of assessing psychological characteristics from this passively collected data,” said first author Robert P. Hirten, MD, Clinical Director, Hasso Plattner Institute for Digital Health at Mount Sinai. “To our knowledge, this is the first study to evaluate whether resilience, a key mental health feature, can be evaluated from devices such as the Apple Watch.”
• The study analyzed data from the Warrior Watch Study, which comprised 329 healthcare workers in New York City who wore an Apple Watch Series 4 or 5 and completed surveys on resilience, optimism, and emotional support. The metrics collected were predictive in identifying resilience or well-being states, supporting the further assessment of psychological characteristics from passively collected wearable data. The researchers intend to evaluate this technique in other patient populations to improve its applicability.
• In essence, the study highlights the potential for wearable devices and machine learning models to monitor and assess psychological states remotely, improving access to mental health services for all people. Further research is needed to refine the algorithm and improve its applicability in a range of physical and psychological disorders and diseases.

What You Should Know:  

• Kaiser Foundation Hospitals and Geisinger Health are teaming up to launch Risant Health and a definitive agreement to make Geisinger the first health system to join Risant Health to expand access to value-based care in more communities across the country. Upon regulatory approval, Geisinger becomes part of the new organization through acquisition.
• Risant Health is a new nonprofit organization, created by Kaiser Foundation Hospitals, to expand and accelerate the adoption of value-based care in diverse, multi-payer, multi-provider, community-based health system environments.
• Jaewon Ryu, MD, JD, has been selected to serve as CEO of Risant Health. Dr. Ryu will transition from his current role as president and CEO at Geisinger Health as the transaction between Risant Health and Geisinger closes.

Risant Health’s Vision

Risant Health is a nonprofit affiliate of Kaiser Foundation Hospitals, which will be headquartered in the Washington, DC, metro area. Risant Health’s vision is to improve the health of millions of people by increasing access to value-based care and coverage and raising the bar for value-based approaches that prioritize patient quality outcomes. In addition to Geisinger, Risant Health will grow its impact by acquiring and connecting a portfolio of likeminded, nonprofit, value-oriented community-based health systems anchored in their respective communities.

Health systems acquired by Risant Health will   continue to operate as regional or community-based health systems serving and meeting the needs of their communities, providers and health plans while gaining expertise, resources, and support through Risant Health’s value-based platform. Risant Health will operate separately and distinctly from Kaiser Permanente’s core integrated care and coverage model while building upon Kaiser Permanente’s 80 years of expertise in value-based care.

Geisinger Acquisition Impact

Geisinger will maintain its name and mission, and will continue to work with other health plans, employed physicians, and independent providers. At the same time, Geisinger will build on its foundation by benefitting from Risant Health’s value-based platform that offers the best in value-based care practices and capabilities in areas such as care model design, pharmacy, consumer digital engagement, health plan product development, and purchasing. As the first health system to become part of Risant Health, Geisinger will participate in developing the organization’s strategy and operational model.

Electronic medical records (EMRs) – software systems where physicians, nurses, and other healthcare workers store, retrieve, and act on clinical data – are fundamentally broken. This sentiment is so widely shared among healthcare workers that it has become almost trite to point it out. Patients feel it too – we’ve lost count of the number of times we’ve heard “isn’t it in my chart?” when we ask a question during a clinical visit.

Unfortunately, the vast majority of EMRs do not facilitate storing, retrieving, or acting on information in an efficient or intuitive way. The most broken element of most charts is the free-text segments – where clinicians store narrative text data about the patient’s medical concerns, their own diagnostic impressions, and their treatment plans.

Free-text segments are critical both to pass information forward into the future and to collaboratively manage information across a team of generalists and specialists in different roles. It’s not possible to store all of that information in your head anymore, even if it was feasible 50 years ago (which is also doubtful). It’s a disservice to patients to imagine that we could. So we need a good electronic system to help. There are many ways a clever system designer could build software to organize free-text data for a single patient – data about multiple medical topics, collaboratively stored, retrieved, and used by numerous healthcare professionals, evolving over the course of years. An ideal system would, at a bare minimum, make it easy to store and organize information intuitively, such that it would be quick to retrieve relevant data later.

The specific way that most clinicians and EMR companies (in America, at least – we can’t speak to anywhere else) have chosen to organize this data is empirically terrible. It’s terrible because clinicians hate using it. It’s terrible because you can’t find relevant information quickly because charts are riddled with useless, out-of-date, and erroneous information, scattered across hundreds of different documents. The information which is both relevant and correct requires herculean effort to find. Clearly, the EMR is failing at its most basic job. Beasley et al elucidated a great framework for this ‘information chaos’ over 10 years ago, and it’s still accurate.

In our study, we used the information chaos framework: particularly, the two hazards described in the Beasley paper as “information overload” and “information scatter”. We examined a corpus of >100 million free-text notes written by thousands of different healthcare workers at our hospitals and clinics to quantify information overload and scatter. Information overload is pretty easy to quantify. We just counted the total free-text data in the corpus; this was ~32 billion words, eight times the size of the English Wikipedia at the time we checked. It was astonishing to us that a single academic healthcare system in one city in one country over 6 years produced eight times more free-text data than the global resource dedicated to capturing all of the human knowledge worth knowing. Not all of that information is relevant to a particular doctor visit or hospital admission, to be sure, but a clinician is still responsible for knowing the subset of the information that is relevant. To do that, you need a system that facilitates finding the relevant information among the irrelevant noise. The more noise there is, the more infeasible this gets and the more acutely healthcare workers feel the pain of a badly designed system.

Speaking of noise, we next looked at a subset of information overload well-known to clinicians – duplicate information. This is information that is already in a patient chart, but for whatever reason a clinician sees fit to repeat it again in a separate text document in the same chart (in clinical parlance, each individual document is called a “note”). We found that just over 50% of words were duplicated, that this fraction has been increasing over the past 6 years, and that this phenomenon is ubiquitous across all patients, clinicians, and healthcare worker types. That means 16 billion words have been duplicated over the past 6 years in just one health system. Many clinicians who reached out to us were surprised that the fraction was so low – predicting that 70% or more would be duplicated. This staggering statistic illustrates the degree to which the current free-text information management paradigm is broken. It should be a call to action – to deeply revamp documentation to save patients from medical error and clinicians from information management burnout.

“Now, wait a second!” some clinicians might be saying. “Sometimes information stays the same, so it makes sense to re-document it!” For instance, if a patient has a cough on July 3rd when they see you in the clinic, and they still have the same cough on July 12th, maybe you re-write (or more likely, copy and paste) the phrase “patient has a productive cough” in the July 12th note. Of note, information gets duplicated both across time (from past notes into future notes) and across teams (from one doctor or nurse’s note to another). Doesn’t it make sense that if information stays the same over time, you should re-document it?

Well, it would make sense if you take for granted everything about the underlying documentation paradigm, which you certainly shouldn’t. The obvious responses by anyone familiar with modern word processing software outside of a healthcare context are “(1) Why do you have to make a new text document every time you see the patient? Can’t you just edit the old document and track changes?” and “(2) Why does every healthcare worker have to maintain their own separate set of text documents? This sure sounds like a lot of wasted effort finding and collating information from other people’s notes. Can’t they just collaborate on a single shared document?” It’s hard to argue with these points. Sure, we all know colleagues who still send around multiple versions of word documents with convoluted names like “prospectus_020122_jsedits_v2_finaledits_060220” when collaborating, but we can likely all agree that collaborative documentation systems like Wikipedia or Google Docs provide much better software paradigms for collaborative editing of a text document which evolves over time. There’s absolutely no principled reason we can’t have a similar model in clinical documentation systems.

We believe that what we call the “note paradigm”is a key cause of massive amounts of duplication. The “note paradigm” is simply the two assumptions contested in the above paragraph: (1) that every new patient encounter requires a new document, and (2) that every healthcare worker must create their own documents. When a phenomenon is as ubiquitous and predictable as duplication, we can’t blame it on individual clinicians being “lazy” or even individual EMR vendors designing slow software or overwhelming user interfaces. The problem is deeper than the EMR level. It’s at the paradigm level, which underlies the assumptions about how documentation is done, how documentation systems should be built, and how medical care is regulated by the government and billed by insurance companies. It’s taught in medical schools that you have to write a “progress note” every time you see a patient, and that different specialists have to write their own “progress notes”. At this point, the note paradigm is the water we swim in; it becomes hard for many to even recognize that it is a specific design choice, or that it could be otherwise.

It’s easy to see how the note paradigm leads to information overload if you think about documentation incentives. Imagine a primary care clinician responsible for a patient with 5 different medical problems, all of which require adjustment of medications and 3-month check-ins. In this situation (assuming no eidetic memory), every 3 months, the clinician will need to remind themselves of all the relevant information about those problems, gather new information, incorporate it into decision-making, and document the new current state of the patient’s medical problems after the visit. Under the current paradigm, their choices are either (1) to use each of their notes as a complete and comprehensive state-of-the-patient, adding new information each time but keeping all of the old information around, or (2) just document the changes from the last visit to this visit in each note. Choice (1) leads to high information duplication as old information is persisted in every new note, but low scatter because all the relevant information is in the most recent document. High duplication increases textual errors as out-of-date information is perpetuated without change. On the other hand, choice (2) leads to shorter notes, low duplication, and high scatter because the information is now only contained in the entire set of notes, not just the most recent. High scatter necessarily increases the time needed to collate and synthesize the relevant text as all notes would need to be reviewed at every encounter to get the full story.

So without implementing a collaborative documentation system, there will remain an extremely strong trade-off between duplication and scatter and this will play out differently depending on the author’s role in a patient’s care. In particular, we’d expect that healthcare workers who treat patients’ medical problems over time (primary care doctors, psychiatrists, or specialists) would prefer to minimize scatter at the cost of high duplication. Extra work is done upfront to collate information so it can be copied forward and persistently available with minimal work. On the other hand, healthcare workers who treat patients’ problems temporarily (urgent care doctors, surgeons, nurses answering triage phone lines) would have no incentive to collate information and so would write brief notes that capture the problem at hand at the cost of high scatter. The real loser in these situations is the patient, who would be better treated if the long-term care team knew about the short-term problems, and the short-term care team had all the relevant context of the patient’s long-term care plan. 

This trade-off is exactly what we empirically see when we plot scatter vs. duplication for different note types in our study. Some note types have high duplication and low scatter, exemplified by physician progress notes which aim to summarize the entire current ‘state of the patient’. These notes are comprehensive (low scatter) but duplicate lots of past information. Other note types have high scatter and low duplication, exemplified by note types that document a single isolated event e.g. (“result” notes, which comment on the results of a particular lab test; or telephone encounter notes, which document a short phone call with a patient). Very few note types have both high duplication and high scatter, except for those that are almost entirely auto-generated boilerplate text. From this picture (and our own clinical experiences), we can infer that clinicians often duplicate text because the highly scattered alternative would be worse.

The electronic medical documentation system is broken and causing clinician burnout. It affects every patient and clinician, regardless of their medical problems or clinical role, and it should be taken seriously. If we want to fix the problem, we need to properly identify and label it. The software wrappers – the systems we use every day – are only a symptom of the real problem, the note paradigm and the underlying assumptions about documentation. Individual rules to “ban” or “limit” duplication provide a solution for a different problem, not for remedying the root cause of duplication. To address that, we have to understand the motivation, which is clearly to minimize scatter, and so any limitation on duplication has to be paired with a non-duplicative tool for decreasing scatter or increasing information density per screen. Acknowledging these problems is easy. Fixing them on the other hand, will require deep cultural changes in medical training and practice, as well as changes in the billing practices, governmental regulations, and legal requirements surrounding medical documentation. But what better way to answer the question, “Isn’t it in my chart?”, than “You’re right! It’s right here.”

About Subha Airan Javia, MD

Subha Airan Javia, MD, FAMIA, is the CEO of CareAlign, a clinical workflow management technology company. She is also a hospitalist at Penn Medicine.

About Jackson Steinkamp, MD

Jackson Steinkamp, MD, is an internal medicine resident at Penn Medicine with a degree from Chobanian & Avedisian School of Medicine at Boston University.

Hospitals are increasingly motivated to drive digital transformation in order to improve patient outcomes, reduce costs, meet regulatory requirements and stay competitive. Additionally, digital transformation can support medical research and drive innovation in healthcare, as well as generate new revenue streams. An increasingly important tool as hospitals undergo these transformations is federated learning, a technology that we will expand on later. Federated learning is a machine learning approach that enables the collaboration and sharing of data between multiple institutions while preserving patient privacy and security.

Going back to the general topic of digital transformation of hospitals, we have seen several trends, some of which have been long-standing and some less so:

1. Adopting electronic health records (EHRs) has already been encouraged by the Health Information Technology for Economic and Clinical Health (HITECH) Act’s ‘Meaningful Use’ clause, and EHRs have been used over the last decade to improve communication and coordination among healthcare providers. Additionally, digitized health records have been used to make patient information more easily accessible, first to meet Health Insurance Portability and Accountability Act (HIPAA) and HITECH mandates, and now, increasingly, to meet the 21st Century Cures Act ‘Final Rule’ mandate, requiring timely and standardized access to all patient data.
2. Implementing telemedicine and remote patient monitoring have grown in popularity for years now, and were especially accelerated during the COVID-19 pandemic, in order to increase access to care and reduce the need for in-person visits. They were also enabled by regulatory changes that allowed cross-state patient care and other ways to relax the burden on provider organizations and patients alike.
3. Data analytics and population health management tools are often layered on top of the medical records in order to identify high-risk patients and improve care coordination, as well as adopt value-based care models that focus on outcomes and cost-effectiveness (such as the MACRA-MIPS reforms, encouraging the formation of ‘Accountable Care Organizations’).
4. Increasing the use of technology such as AI and ‘Robotic Automation’ to improve administrative efficiency, diagnostic accuracy and treatment planning. This is the newest trend, reaching broad adoption over the last 2 years (or so), and we will later focus on that as a driving force and component of digital transformation.

As one could assume, the implementation of hospital digital transformation creates significant demands on data availability and interoperability. These demands include:

1. Data Availability: Hospitals need to have access to complete, accurate, and up-to-date patient data in order to provide effective care. This includes both structured data (such as lab results and medications) and unstructured data (such as notes from doctors and nurses).
2. Data Interoperability: Hospitals need to be able to share data with other healthcare providers and organizations in order to coordinate care and avoid duplicate tests and treatments. This requires the use of common data standards and protocols, as well as the ability to securely exchange data across different systems.
3. Data Security: Hospitals need to protect patient data from unauthorized access, use, and disclosure. This requires the use of robust security measures such as encryption, multi-factor authentication, and regular security audits.
4. Data Governance: Hospitals need to have effective policies, procedures, and systems in place to manage and control access to patient data. This includes managing data access controls and permissions, monitoring data usage, and implementing data quality and integrity checks.
5. Data Analytics: Hospitals need to be able to analyze patient data in order to identify trends, patterns, and insights that can inform care decisions and improve patient outcomes. This requires the use of advanced computational and analytics tools and techniques, as well as the ability to integrate data from multiple sources.

These demands are increasingly being met with additional technological innovations entering the conservative hospital world. Despite advances in data interoperability, such as the adoption of FHIR APIs and increasing leverage of Common Data Models (CDMs), the hospital IT world is still highly fragmented, and even the advent of Cloud Compute has not drastically reduced that fragmentation. Moreover, in order to meet these increasing needs, hospital IT must now implement a record number of new technologies in a short period of time, and despite a fairly consolidated EHR market, the rapid cycles of innovation and massive capital investments pouring into the Healthcare IT market have resulted in more vendors than ever before.

How could Federated Learning assist in clinical transformation?

First of all, let’s define federated learning. Federated learning is a powerful machine learning technique that allows for the training of machine learning ‘models’ on multiple disparate datasets. That means that data does not need to be shared/centralized in order to leverage it for creating powerful analytics and algorithms. Thus, federated learning could assist in clinical transformation by allowing hospitals to collaborate and share data in a secure and privacy-preserving way. If provided alongside a comprehensive platform that supports integrating with different infrastructures found in different hospitals, federated learning can assist in, alleviating many risks around data sharing such as compliance risks (e.g., HIPAA, GDPR regulations), data privacy risks (ie, that extend beyond the regulations), reputational risks (e.g., in the case of ‘data leaks’ and malicious use of data by a 3rd party) and financial risks (e.g., the investments required to setup massive repositories and leverage centralized ‘data lakes’). Some specific ways it could be used include:

1. Eliminating the need to create multiple ‘data flows’ to the cloud, and keep all data under the ‘sovereignty’ of the hospital at all times.
2. Reduce the need to integrate multiple technologies one-at-a-time, by having a standard communication method to connect (often) multiple internal ‘data silos’ with external data consumers.
3. Facilitating foundational and clinical research by allowing hospitals to share data insights for research purposes, without driving an ever-growing amount of labor-intensive efforts (e.g., anonymizing, certifying, contracting and governing). This in turn drives translation of ‘better baked’ medical AI models into the clinical workflow, as well as better commercialization of inventions that have been afforded with external data validation (ie, the model works elsewhere) and market validation (users wish to use the model elsewhere).
4. Capture value by increasing the value of data, and enabling hospitals to tap into new revenue streams such as the ones from drug development. Federated learning allows pharmaceutical companies to access sought-after ‘multi-modal’ data from multiple hospitals in order to identify potential drug candidates and evaluate drug safety and efficacy. In addition, this enables hospitals that implement new technologies to ‘leapfrog’ many traditional players that already capture value from such efforts, and ‘take out the middleman’ in the form of data intermediaries that erode the hospital’s value.
5. Enhancing disease surveillance by sharing data insights across multiple jurisdictions to track the spread of diseases in real-time, identify outbreaks quickly and plan interventions accordingly.

A specific area that is mentioned above and is dear to my heart, is supporting the translation of algorithms created by researchers in hospitals. Federated learning supports this, often grueling and difficult, process by reducing the barriers for researchers and clinicians who would like to collaborate, and thus enabling what could often remain as a good publication, turn into a product used to improve patient care, and let hospitals once again take the lead on innovation. The sad reality today is that without being able to translate ‘homegrown’ models into clinical impact, the ability to capture value is reduced, and few models have been licensed to date. Ultimately, I believe ‘Medical AI’ will follow pathology in providing ‘lab developed tests’ as diagnostics. Lab-developed tests (LDT) are tests that are developed, performed and analyzed in-house by a laboratory. One of the key things keeping medical AI behind, is the need for much bigger datasets and need for much broader diversity in order to create and validate a performant model. These needs are not supported by the current paradigm of single-site research and ‘once in a blue moon’ massive collaborations (that usually use redacted data or small amounts of patient data). Federated learning can fix this.

Alongside the many promises, it is important to note that Federated Learning is a complex technology, it requires a well-designed infrastructure and a platform that supports a complex workflow, strong data governance and robust security protocols, a vendor that can take on liability and proper certifications in order to be implemented. FL also requires hospitals and researchers to work closely together to ensure that data is shared in a way that is both secure and compliant with regulations. I am a staunch believer in this approach, and believe that it will lead to (finally) the actual ‘democratization’ of healthcare data and innovation, drive adoption of responsible AI and ultimately lead to improved outcomes for patients and cost savings for the entire industry.

About Ittai Dayan, MD 
Ittai Dayan is the co-founder and CEO of Rhino Health. His background is in developing artificial intelligence and diagnostics, as well as clinical medicine and research. He is a former core member of BCG’s healthcare practice and hospital executive. He is currently focused on contributing to the development of safe, equitable and impactful Artificial Intelligence in healthcare and life sciences industry. At Rhino Health, they are using distributed compute and Federated Learning as a means for maintaining patient privacy and fostering collaboration across the fragmented healthcare landscape.

What You Should Know:

• A new study by Cedars-Sinai investigators describes how ChatGPT, an artificial intelligence (AI) chatbot, may help improve health outcomes for patients with cirrhosis and liver cancer by providing easy-to-understand information about basic knowledge, lifestyle and treatments for these conditions.
• The findings, published in the peer-reviewed journal Clinical and Molecular Hepatology, highlight the AI system’s potential to play a role in clinical practice.

Helping Patients of Chronic Liver Disease Via Artificial Intelligence

“Patients with cirrhosis and/or liver cancer and their caregivers often have unmet needs and insufficient knowledge about managing and preventing complications of their disease,” said Brennan Spiegel, MD, MSHS, director of Health Services Research at Cedars-Sinai and co-corresponding author of the study. “We found ChatGPT—while it has limitations—can help empower patients and improve health literacy for different populations.”

Patients diagnosed with liver cancer and cirrhosis, an end-stage liver disease that is also a major risk factor for the most common form of liver cancer, often require extensive treatment that can be complex and challenging to manage. Personalized education AI models could help increase patient knowledge and education, noted Alexander Kuo, MD medical director of Liver Transplantation Medicine at Cedars-Sinai, and co-corresponding author of the study. One of those is ChatGPT, which stands for generative pre-trained transformer. It has quickly become popular for its human-like text in chatbot conversations where users can input any prompt and it will generate a response based on the information stored in its database. It has already shown some potential for medical professionals by writing basic medical reports and correctly answering medical student examination questions. 

To verify the accuracy of the AI model in its knowledge about both cirrhosis and liver cancer, investigators presented ChatGPT with 164 frequently asked questions in five categories. The ChatGPT answers were then graded independently by two liver transplant specialists. 

Each question was posed twice to ChatGPT and was categorized as either basic knowledge, diagnosis, treatment, lifestyle or preventive medicine. 

Study results include:

1. ChatGPT answered about 77% of the questions correctly, providing high levels of accuracy in 91 questions from a variety of categories.  
2. The specialists grading the responses said 75% of the responses for basic knowledge, treatment and lifestyle were comprehensive or correct, but inadequate.
3. The proportion of responses that were “mixed with correct and incorrect data” was 22% for basic knowledge, 33% for diagnosis, 25% for treatment, 18% for lifestyle and 50% for preventive medicine. 

The AI model also provided practical and useful advice to patients and caregivers regarding the next steps adjusting to a new diagnosis. 

Still, the study left no doubt that advice from a physician was superior. 

Despite holding the promise of delivering superior patient outcomes while lowering healthcare costs, many providers remain reluctant to embrace value-based care (VBC) reimbursement models. Progress toward VBC adoption hasn’t achieved its potential yet, hovering around 60% of all payment models from 2018 to 2021, with the remaining 40% comprised of traditional fee for service (FFS).

Though some providers simply are hesitant to abandon the FFS model that has served them well, others are leery of the technological and management challenges they associate with VBC models. According to consulting firm RTI Health Advance, these include:

• Administrative complexity within the value-based payment ecosystem
• Transitioning upside risk-only to fully accountable care; many providers are challenged to operationalize programs and afford the necessary time and finances
• Value-based models must incorporate and address specialty care as part of the continuum of covered services
• Health equity plans now are required as part of new value-based contracts with the Centers for Medicare and Medicaid Services (CMS) 

The CMS Innovation Center set a goal for all Original Medicare beneficiaries and most Medicaid beneficiaries to be in VBC relationships by 2030. These risk-based care models are designed to encourage proactive care, better population health and reduced spending across the healthcare spectrum. To meet that deadline, provider organizations will need technology tools for administering relationships within a value-based network. 

How Value-based Administration works

VBC networks are comprised of multiple stakeholders that may include hospitals, health systems, private practices, payers, accountable care organizations (ACOs), clinically integrated networks, social service networks and community-based organizations (CBOs). Successful implementation of value-based programs, therefore, requires complex hierarchy support for onboarding, data capture, data digitization, payments, and data exchange. These technologies must support social determinants of health (SDoH) and facilitate value-based payments, quality reporting and other use cases. 

Within VBC networks are many-to-many relationships in which an entity in one network may be engaged in several networks under various contractual engagements with other entities. Such a “network of networks” can work only with an infrastructure that supports the hierarchies between these entities. The architectural framework and processes used to run VBC networks collectively are referred to as value-based administration (VBA).

Figure 1 shows how VBA helps stakeholders across the healthcare continuum – providers, payers, patients, and CBOs – eliminate barriers to participating in a VBC network while also delivering measurable clinical and operational benefits.

Inadequate digital infrastructures

Most healthcare organizations, however, lack the digital infrastructure necessary for VBA. “We can’t graft a new digital, platform-based healthcare system onto healthcare infrastructure designed to support traditional operations and care models,” Mayo Clinic President and CEO Gianrico Farrugia writes in an article for the World Economic Forum. “Healthcare needs transformation. And to truly transform healthcare, we must simultaneously build physical and digital frameworks to meet the evolving needs of patients worldwide.”

Fortunately, healthcare organizations can implement VBA without embarking on a costly rip-and-replace strategy. This can be done through a platform infrastructure that can be deployed as a DaaS (Data-as-a-Service) or as PaaS (Platform-as-a-Service) or the traditional SaaS (Software-as-a-Service) model.  Such an infrastructure allows partner firms and/or clients to use existing applications served up via microservices or extend/create microservices and business applications for their own needs.  

What’s needed to enable VBA 

To fully leverage relationships in a VBC network, providers must: 

1. Implement a robust cloud-based data infrastructure to allow real-time clinical decision-making, information sharing and analytics
2. Realign downstream reimbursement to include both medical and non-medical providers (behavioral health services, drug treatment centers, etc.)
3. Incorporate SDoH resources and partners, such as CBOs
4. Have a dashboard view into real-time performance against all contracts 

An integral part of effective VBA infrastructure is ML (Machine Learning) and Artificial Intelligence (AI) technologies.  A key to implementing digital transformation is data digitization and amalgamation of that data with structured and external data sets so that a 360-degree view of the patient can be achieved to provide actionable insights to Payers, Providers and Patients.  AI technologies, coupled with ML algorithms in a robust data engineering framework that enables to-and-from integration between systems with this digitized data, are needed to make this a reality.  These facilitate better automation of tasks and decision-making processes since data-driven insights require digitized data in order to automate processes. A set of secure and scalable cloud-based microservices – on which different applications and integrations are built – then helps facilitate data interoperability as well as opportunities to build/partner/deploy different workflow-based applications for the end users. 

Final thoughts

Though structural and technological barriers impeding VBC adoption persist, many large healthcare organizations are working with technology partners to improve patient outcomes and reduce healthcare costs. Implementing VBA to manage VBC initiatives will empower healthcare organizations to deliver on the full promise of patient-centered, value-based healthcare.

About Rahul Sharma

Rahul Sharma is the CEO of HSBlox, which enables SDOH risk-stratification, care coordination and permissioned data sharing through its digital health platform.

About Lynn Carroll

Lynn Carroll is the chief operating officer of HSBlox, which assists healthcare stakeholders at the intersection of value-based care and precision health with a secure, information-rich approach to event-based, patient-centric digital healthcare processes – empowering whole health in traditional care settings, the home and in the community.  

About one out of five Americans with serious illness struggled to access care during the pandemic, and rates were significantly higher among disadvantaged populations, a 2022 study found. Now, as mental health-related visits in emergency departments (EDs) continue to rise, healthcare professionals must consider: “How can we create better behavioral health supports for people in crisis?”

It’s a question that has significant implications for quality of care as well as cost.

The High Cost of Poor Behavioral Healthcare

A recent study indicates 10% of patients account for 70% of the nation’s costs and that more than half of these patients have a diagnosed mental health disorder. When these individuals face mental health challenges, they often seek care in the ED—the point of least resistance to care access—because they lack quick access to care in lower-cost settings. 

But EDs are ill-equipped to treat these complex health issues. Not only do ED staff lack the time and training to deliver the nuanced behavioral health assessments and treatment these individuals need, but the often noisy, fast-paced ED environment makes it difficult to provide this type of care. In addition, the complexities associated with finding the appropriate follow-up care for patients’ behavioral health needs create “a cycle of ED help-seeking behaviors and mental states that worsen with early discharge,” researchers say.

Now, as Medicare and Medicaid continue to move toward value-based contracts, developing practical strategies for meeting the behavioral health needs of vulnerable populations has become even more critical. But too often, hospitals and health systems direct resources toward population-specific solutions without seeing significant change. That’s an approach healthcare organization can no longer afford to take, given already-significant pressures on margins and staff.

Innovating for a Better Behavioral Care Encounter

Innovative organizations are finding value in solutions that better identify patients’ behavioral health needs at the point of care and connect these patients with the appropriate outside support. Here are three examples of behavioral health innovations in the ED that are making a difference in quality of care, patient health and cost.

1. Receiving real-time alerts at the point of care. When it comes to behavioral health crises, timely intervention is everything. Across the country, innovative EDs rely on real-time notifications pushed directly into the EHR to rapidly identify behavioral health patients with multiple behavioral health-related ED visits and alert appropriate care team members. These data feeds supply information from the health professional’s own facility as well as other area hospitals, primary and behavioral healthcare providers, and health systems.
   
   By enabling ED staff to quickly bring in and coordinate their efforts with those who are familiar with the patient’s case, both immediate treatment and ongoing follow-up care improve. For example, staff at Rappahannock Area Community Services Board (RACSB), based in Fredericksburg, Va, receive alerts when a patient with a behavioral health-related challenge has recorded five ED visits within the past 12 months. Within seconds of the patient’s arrival, real-time notifications are delivered to the members of the patient’s care team—including specialty physicians and case managers—who are best positioned to intervene. As a result, patient care, workflows, and documentation improve, allowing RACSB to leverage data through the platform, identify homelessness as a key need for many of these patients, and obtain a $819,577 grant to build supportive housing for individuals with serious mental illness.

2. Providing 24/7, personalized support for patients with high utilization. Not all crises occur between 8 a.m. to 5 p.m., and studies have shown that the timing of a crisis can play a critical role in patient outcomes. In fact, one 2020 study shows increased ED admissions on nights and weekends, a time when specialized providers may be less available. As a result, poorer health outcomes were reported for patients who were admitted to the ED outside traditional business hours.
   
   Successfully meeting the needs of vulnerable behavioral health populations requires putting systems in place to ensure personalized behavioral health support is available 24/7. This means improving in-house, after-hours staffing. It also means assigning community workers that know the individual’s circumstances and are available 24/7 to meet with the patient in real-time at the point of care. Having this assigned support ensures that reliable information regarding care plans, lists of current medications, and names of key service providers and community organizations with whom the patient is connected are readily available to ED staff in moments of crisis, further improving health outcomes and reducing costs of care.

For the High Utilizers of Virginia program, a state-based program dedicated to reducing unnecessary ED utilization among individuals with behavioral health needs, use of real-time alerts and 24/7 access to community health workers cut ED visits for this population by one-third within one year. Other results include a 94% reduction in state hospital psychiatric admissions, an 84% drop in state psychiatric hospital admit days and more than $2 million in savings—without compromising the quality of care.

3. Building trust by prioritizing rapport. Robust patient data is key to anticipating and shaping patterns of behavior. For example, data may reveal that a patient is prone to arrive in the ED on the weekends when a patient’s routine care team is not available. It might also highlight social determinants of health exacerbating a patient’s mental health challenges, such as lack of stable housing, challenges acquiring prescribed medicines, or food insecurity. Unfortunately, without trust, the patient is unlikely to open up about these challenges.
   
   Medical mistrust, especially from traditionally marginalized populations, continues to be a barrier to providing both physical and behavioral health care. Increasing awareness and expanding the diversity of staff is an important part of addressing this issue, but behavioral health professionals suggest that even the most diverse staff will struggle to identify outstanding needs if sufficient time for rapport building and assessment is not provided. Trained community workers, or even peer support, can help close this gap by providing an affordable alternative to increasing the time spent by doctors and case managers in developing the rapport necessary to conduct the necessary assessments. It’s a move that protects patients’ health while reducing the stress on ED resources and staff.   

By optimizing the ED encounter with real-time data, patient-specific context, and 24-7 community support, health systems can create more time for the behavioral health encounter, reducing unnecessary use of the ED while making a significant difference in patient outcomes and costs of care. 

About Ben A. Zaniello, MD MPH

Ben A. Zaniello, MD MPH, is the Chief Medical Officer of PointClickCare, the largest Post-Acute and Acute Care Network in North America. He has worked in care transformation for over a decade, formerly at Collective Medical, which PointClickCare acquired in 2020. Before Collective, Dr. Zaniello worked at Providence Health, the 53 Hospital Seattle-based health system as their Chief Medical Information Officer in Population Health.

About Dr. Enrique Enguidanos

Dr. Enrique Enguidanos is the founder and CEO of CBC Solutions and has over 20 years of clinical experience in Emergency Medicine, much of this time also serving in organizational and systems management roles. For well over a decade he has developed and fine-tuned systems of care and community management systems that have proven very effective for frequent utilizers, and that is now organized in a manner that allows CBCS to continuously reproduce care results across varying communities and health care systems.

Staffing levels continue to plague health systems across all of the clinical and administrative areas, with no real signs of easing in the next several years. Employee retention efforts have never been more critical and leaders are looking to technology to help their staff work smarter. While AI promises to be everything to everyone, the use cases where it is successful are actually quite narrow. However, there has been great progress in automating administrative tasks, particularly in revenue cycle operations, that are producing meaningful productivity improvements and easing the workers’ burden. Collecting every dollar counts and these improvements are making a real difference for revenue cycle teams.

Burnout among providers is at an all-time high causing many to leave the workforce and a healthcare staffing crisis. Despite the promise of technology, to date technology has been more of a contributor to provider burnout than an aid. We must adopt health IT solutions with our providers in mind – implementing technologies that automate and augment repetitive provider tasks, freeing up valuable time for our workforce.

A powerful Master Patient Index (MPI) allows organizations to safely and accurately manage data with fewer resources. Many organizations employ a few to dozens of data stewards to eliminate duplications and resolve record overlays. The number of data stewards required can be reduced drastically through a powerful MPI and referential matching combined with machine learning capabilities.

Health IT is a misnomer. Very little of the health IT industry is focused on improving health; instead it is however focused on collecting codes, rather than innovating workflows that enhance patient care and support providers. The burden that the current state of healthcare IT places on providers directly leads to physician burnout and a reduced capacity to deliver quality patient care.

Imagine if a health system could partner with a tech-enabled virtual care team to offload routine and commoditized tasks. This would open up virtual care capacity for mild urgent and chronic issues, while also freeing up office-based providers to focus on more complex patients. This strategy would also improve clinician burnout by making the primary provider the head of a team that could manage a greater number of people, meaning they could increase their own revenue while ensuring better access for their patients.

Leading hospitals and health systems in North America are using virtual care technology that supports an augmented care environment where a virtual team doesn’t replace, but rather, provides support to the bedside team, enabling health systems to reduce labor costs while liberating their bedside nurses to provide elevated, hands-on patient care. For example, telesitting technology allows health operations staff to raise their patient management abilities from one patient per staff member to up to 16 with virtual monitoring. The solution also enables new Virtual Nursing models which provide health systems with a tool to help address clinician burnout and staffing shortages by efficiently leveraging their most experienced nurses to support bedside care teams and enable more efficient clinical workflows. At Trinity Health, falls declined from as many as 62 in the second quarter of 2020 to as few as 28 in the third quarter of 2021. Not only was patient safety better protected through virtual monitoring, but Trinity Health was also able to reduce its costs by $23M by avoiding non-reimbursed services for those injuries.

Hospitals face the challenge of increasing surgical revenue without adding OR staff or facilities. AI-powered automation in perioperative and inpatient settings, coupled with machine learning and behavioral science, allows systems to more efficiently schedule surgeries and reduce the length of stay. This drives OR growth and relieves overburdened staff of manual tasks.

Burnout threatens clinicians’ effectiveness, which ultimately can harm patients and contribute to costly readmissions. Health IT and intelligent automation that safely reduce the cognitive burden that repetitive and menial tasks place on already overloaded clinicians has never been more needed than it is right now. It also helps ensure certain processes are followed consistently and accurately since growing staff shortages force some hospitals to staff entire units or shifts with temporary or traveling clinicians. Technology can give time back to clinicians so they can focus on their patients – going beyond relieving burnout to reintroducing some of the joy in patient care that has been depleted for so many providers over the last several years.

Whether in a clinical hospital setting or a college campus counseling center, provider burnout is a massive problem touching every corner of care delivery. Fostering wellness in healthcare workers is key to addressing burnout, promoting well-being, and building resiliency among providers. A recent survey by CUPA-HR focusing on employee retention finds that supervisors’ top challenges on campuses are filling empty positions and maintaining staff morale, with almost two-thirds (63%) of supervisors indicating they find filling positions very challenging and over half (54%) facing low staff morale. The integration of medical and behavioral health technology for healthcare providers on college campuses can help relieve many issues, including fatigue and burnout, playing a critical role in fusing healthcare and technology that addresses these critical staffing shortages.

With clinician shortages and an overburdened workforce, healthcare organizations are turning towards digital health strategies to help streamline clinical workflows, boost efficiency, and reduce administrative burdens. Solutions such as remote patient monitoring (RPM) can enable providers to remotely manage patients’ health conditions outside the clinical setting, freeing up vital resources. RPM also allows for improvements in medication adherence, streamlining billing and reimbursement while enabling clinicians to spend more time on patient-facing and revenue-generating opportunities. Although there is no perfect solution for all the growing staffing challenges, digital health technology can help healthcare organizations reduce the burden of routine, manual tasks on clinical staff and deliver greater insights that allow them to focus more on patient care and enhanced outcomes.

In a recent survey, 30% of RNs and LPNs said that making a difference in people’s lives is the most rewarding aspect of the job. Yet, we continue to pile more tedious work on their plates, causing more burnout that results in more clinicians leaving the profession. It’s time to ask nurses to do less. By automating routine and mundane tasks, we can free up nurses to deliver more individualized care, spend time with those patients who need it most, conserve human resources, and reduce costs. Thoughtful automation that lets nurses work at the top of their licenses can have a lasting, material impact on attracting and retaining nursing staff.

With nationwide staffing shortages, budget crunches, patient surges, and the heavy burden upon nurses, physicians, and other healthcare workers during the pandemic era, health systems must make smart, well-informed decisions about staffing, resource use, and system capacity. Like evidence-based clinical decision-making, healthcare operations decision-making needs to be driven by innovative use of hard data and intelligent analytics. Healthcare IT tools, processes, and organizational models like the MDClone ADAMS Center help health systems use their human and physical resources wisely to optimize the care they can deliver to their communities while maximizing the support they give to their professional staff and preventing clinician burnout.

Persistent staffing shortages continue to exacerbate clinician burnout as stress and demands on their time mount. Medical NLP is one technology that holds promise to relieve some of that pressure by improving EHRs for their end-users. By turning the unstructured text in patient documents into succinct, searchable summaries, caregivers can have easier, faster access to the relevant information to patient care and spend less time searching for the ‘needle in the haystack’, reducing their screen time and improving the end-user experience.

Clinician burnout, ‘the great resignation,’ and pandemic-induced capacity issues have turned a glaring spotlight on some fundamental issues plaguing our healthcare system. It’s not a matter of ‘working smarter’ or throwing bodies at the problem, but of empowering our clinicians at the point of care. All too often, technology is a hindrance rather than an enabler. Physicians need immediate access to timely, detailed, and accurate information about a patient to inform therapy options. EHRs alone are not the answer, as they are heavily siloed and built for billing. To make deliberate, informed treatment decisions, clinicians need tools that unify and present relevant clinical data in a way that illuminates trends in real-time.

Most people who go into healthcare or behavioral health services are service-oriented, compassionate people. They’re focused on wanting to use their skills to serve people. Anything getting in the way of that happening creates dissatisfaction. Unfortunately, EMRs can increase burnout by forcing clinicians to spend excessive amounts of time navigating their screens and conducting data entry and administrative work. Telehealth is one of the keys to better work-life balance for providers because the setting gives them more control. It can also mitigate burnout by offering clinicians greater flexibility in how they work, enabling them to work on top of their license, and freeing up time to see more patients, all of which leads to improved job satisfaction.

Angie Franks, CEO of ABOUT Healthcare Inc., which provides access center solutions that enable hospitals and health systems to more effectively manage all aspects of patient transfers and optimize access center operations

The application of technology shouldn’t be limited to one health system or system of care. In fact, its impact can be much more profound when it extends to multiple systems under different ownership. The pandemic is a prime example. With it, we saw an exceptional surge in healthcare demand in a compressed timeframe. Moreover, many of these spikes were tied to geography. Information technology can help health systems load balance capacity across extended regional networks to ensure patient demands for care are met. When the boundaries to care are no longer limited to a specific hospital or health system, healthcare becomes more ubiquitous, and providers can ensure prompt access to care at every stage of the patient journey. And compressing the time to care promotes optimal patient outcomes, which is the ultimate objective.

Prior authorization remains a massive administrative burden for payers and providers, despite ongoing improvement efforts. Patients are frustrated by the care delays that result. Clinicians are experiencing burnout due to the extensive amount of paperwork associated with documenting and conforming to health plan policies. CMS aims to improve prior authorization with a recently proposed rule. It’s a step forward to ease some of the daily administrative workloads. As the conversation continues about reducing health worker burnout, more health plans will start by adopting new technologies to comply with upcoming regulations. Still, many will begin to think bigger and use AI and machine learning in real-time to automate prior authorization decisions – resulting in up to a 60% reduction in administrative work.

What You Should Know:

– A recent study published in JAMA found that conventional genomic tests commonly used for breast cancer tumors can be less accurate for Black women. This news comes at a time when Black women with breast cancer are experiencing mortality rates that are 41% higher than white women.

– Dr. Nathalie Johnson, MD FACS and President of The American Society of Breast Cancer Surgeons is among numerous doctors who advocate for Agendia and its tests which look beyond race, ethnicity, age, or menopausal status, to provide information based solely on biology. This precise information allows women and their care teams to be empowered to select the best treatment option based on their unique cancer.

Understanding and Addressing Racial Disparities in Breast Cancer Care

Racial disparities in medical care continue to pervasively affect the most vulnerable communities. Understanding such disparities within the context of racial inequities and societal institutions allows for systemic discrimination to be addressed. Such discrimination is not the aberrant behavior of a few but is often supported at an institutional level, propagated additionally by implicit biases and negative stereotypes. Stark disparities in breast cancer care have been brought to light recently by a stream of research papers highlighting a glaring issue: Black women disproportionately suffer negative outcomes in breast cancer care, as opposed to their White counterparts.

A recent cohort study shows that Black women in the United States were more likely to have a high-risk recurrence score and to die of axillary node-negative breast cancer compared with non-Hispanic White women with comparable recurrence scores. This shows that the Oncotype DX Breast Recurrence Score test, which is used to analyze the activity of a group of genes that can affect how an early-stage breast cancer tumor is likely to respond to treatment, has lower prognostic accuracy in Black women. This, in turn, suggests that genomic assays used to identify candidates for adjuvant chemotherapy may require model calibration in populations with greater racial/ethnic diversity.

Dr. Johnson is currently the President of The American Society of Breast Cancer Surgeons, as well as the Medical Director of the Legacy Health System Cancer Institute and the Legacy Breast Health Center in Portland, Oregon. She is considered to be one of the world’s leading authorities in breast cancer, not only because of her impeccable reputation as a distinguished surgeon, but also because of the fact that having survived breast cancer herself allows her to empathize with her patients, and understand breast cancer in an unparalleled manner. 

To learn more about racial disparities in breast cancer care, we spoke with Dr. Johnson for her insights: 

When talking about breast cancer, you often bring up the notion of “every woman having her own unique cancer”. What does this mean, and how can more widespread understanding and acceptance of this notion empower Black women and other marginalized communities?

Dr. Johnson, MD FACS and President of The American Society of Breast Cancer Surgeons: The notion of ‘every woman having her own unique cancer’ is, to me, the true definition of personalized medicine. Understanding each patient, what they bring to the disease and where they come from helps one understand the things that would make them most comfortable with the treatment. It also gives one an insight into why certain options feel good, and why some don’t. This also allows us to take the time and explain to the patient certain things that they might not be too happy to have, for instance – chemotherapy. Nobody is happy to have chemotherapy, but by understanding the patient, one is able to teach them about why they need these treatments for their specific tumor. This is one of the reasons why I am a strong advocate of neoadjuvant therapy because it has allowed us to treat people who we initially thought were not going to get better.

For Black women in particular, there are different options. I am trying to educate people about recurrence scores and the genomics of cancer. We have begun to realize that the widely used genomic test ‘Oncotype DX’ does not represent the biology of African American women as well as another genomic score might. This puts Black women with estrogen-positive breast cancer at a disproportionate disadvantage. Trying to understand tumor biology specific to the patient also allows one to consider pre-surgical endocrine therapy, which can provide evidence as to whether the tumor is endocrine-sensitive in the way you might have imagined. 

How would starting the conversation around ‘ethnically representative tumor biology’ address the racial disparities we see in breast cancer?

Dr. Johnson: Because we see Black women with the same Oncotype recurrence score as their white counterparts having a much higher mortality rate, we can extend that logic and apply it to other ethnically marginalized communities as well. Everyone benefits from this conversation. For each ethnic group, we want to do the best that we can, and ultimately help each and every patient that walks through our door, we want to fully understand the biology of their tumor and what nuances there may be. The same principle exists for genomic testing as well. When we do studies, we often don’t have enough representation from under-represented minorities, and this really highlights the need for having representative samples in clinical trials, otherwise, we may not do as good a job as we could of understanding their particular set of genes.

What are some barriers that discourage more Black women to take part in clinical trials, and how can we overcome these barriers?

Dr. Johnson: We can definitely do a better job at having everybody – Black women and all, included in studies. One of the major issues is trust. Being able to sit down and explain the aims and objectives of the study to the patients in detail allows for better trust-building. In some ways, there may be some implicit bias that goes into enrolling patients into trials, which could manifest in ways like not thinking that some patients may not understand the study objectives when in reality they would if you took the time to explain. In some of the recent genomic trials, like the ‘RxPONDER Trial’, there was some concern that Black women were not as compliant with therapy as white women. However, it turned out that Black women were the most compliant group in that entire trial. For other groups, one thing we can do is to ensure that consent forms are in languages spoken and understood by those communities. Having consent forms in different languages is one of the things that The American Society of Breast Cancer Surgeons wants to work on, so we can enroll diverse participants.

What prognostic and predictive value do advanced gene expression profiling solutions such as Agendia provide to Black women?

Dr. Johnson: As an advocate of MammaPrint, I try to educate people about these advanced gene expression profiling solutions. Based on many studies, Agendia’s MammaPrint appears to be a more representative genomic score for Black women in particular. MammaPrint’s prognostic value is far greater than the genomic scores we use today because it accurately classifies African American women as ‘high risk’ which impacts the treatments we give them and also improves their outcomes. Additionally, with MammaPrint, the number of genes tested is greater, which allows you to comprehensively evaluate the impact of other genes on the patient. For instance, obesity has been found to impact the outcomes of breast cancer patients. Therefore, by using MammaPrint you can look at the genes that are differentially expressed, and understand the tumor in a much better way. Using MammaPrint and BluePrint allows you to look at 150 genes, whereas Oncotype DX just accounts for 21 genes, so there is definitely a stark difference in the depth of gene expression change that can be picked up with MammaPrint. The interplay of differential expression amongst genes is something that can and will be further explored in the future across populations, but for now, advanced genomic testing is definitely allowing us to understand and treat breast cancer better.

About Agendia

Agendia’s testing platform provides physicians the ability to comprehensively analyze the biology behind an early-stage breast cancer patient’s tumor, providing unique genomic insights that empower precise treatment decisions. Agendia’s unique, innovative tests include:

• MammaPrint®, its 70-gene prognostic test, determines a specific patient’s breast cancer recurrence risk, and can predict a patient’s response to both chemo and endocrine therapy.
• The 80-gene molecular subtyping test, BluePrint®, identifies the underlying biology of an individual’s breast cancer to provide information about its behavior, long-term prognosis, and potential response to systemic therapy.
• When combined, the two tests capture the underlying biology of a tumor, to holistically inform the most effective treatment approaches for a patient’s unique cancer, regardless of age, menopausal status, race, ethnicity and other clinical factors, enabling physicians to objectively select the best treatment plan.

What You Should Know:

– Sana, a healthcare company that provides Fortune 500-level health benefits to small businesses at affordable prices, today announced a partnership with Little Otter, a digital mental health solution for children and their families. 

– Both Little Otter and Sana are aligned in their goal to provide comprehensive, high-quality mental healthcare to their members and their families. By investing more in primary care and enabling access to more low-cost, best-of-breed providers for small business employees, this partnership reduces the physical and financial barriers to receiving mental health support for the whole family. 

Emerging Partnership to Improve Accessibility to Quality Mental Health Care

Through Little Otter’s app, once Sana members confirm their eligibility, they are invited to answer key questions to inform how to best support their family. With this information, the Little Otter team will have a clearer picture of the family dynamics at hand. They can provide the family with immediate feedback in terms of helpful resources available and invite Sana members to schedule a consultation via the app as a next step. 

Sana has made strides in recent years to improve its health service and insurance offerings to the communities it serves. In early 2022, Sana opened Sana MD, the company’s first primary care health center for members. Located in Austin, Sana MD provides employees with access to $0 comprehensive onsite primary care, urgent care, labs and care coordination, as well as virtual primary care. Sana has also announced partnerships with Bloom and Carrum Health, making this partnership with Little Otter the latest expansion to the growing Sana Care ecosystem. 

“This latest partnership with Little Otter is a huge step forward in our mission to make the highest quality health care available to everyone,” said Sana co-founder and CEO Will Young. “With 50% of mental health disorders appearing before the age of 14, this partnership fills an important role for Sana members, expanding access to mental health services for kids 0-14 as well as support for their families.”

The FDA’s recent accelerated approval of Leqembi was welcome news across the Alzheimer’s community. However, few health systems, medical practices, or providers are prepared for the extraordinary public interest in a treatment for Alzheimer’s disease – especially not one targeting mild cognitive impairment (MCI) and early dementia due to Alzheimer’s disease – that is likely headed their way soon. The unprecedented scale of the public health and marketing campaigns, the high prevalence of MCI in the population over 60 years old, and people’s fear of dementia will combine to create a tsunami of patients presenting to their healthcare providers seeking testing and treatment.

By the end of the summer, if CMS agrees to pay for the anti-amyloid antibody infusions therapies like lecanemab and donanemab, we can expect to see advertisements targeting individuals who may have signs of MCI with simple, attention-grabbing messages like:

– Are friends and family members’ names getting harder to recall? 

– Do everyday tasks like shopping at the grocery store seem more confusing? 

– Are your family or friends concerned about your memory or your thinking? 

– You could have a mild cognitive impairment, also known as MCI. Up to 80% of MCI is due to Alzheimer’s disease, which can now be treated. 

– If you think you may have MCI, you should speak to your physician about if anti-amyloid antibody therapy may be right for you. 

A public awareness campaign will be critical for the commercial success of these medications because most patients and caregivers are not familiar with Alzheimer’s disease in its pre-dementia stages. The anti-amyloid antibodies have been shown to reduce the progression of cognitive decline in Alzheimer’s but not improve an individual’s thinking, so it is important that therapy starts as soon as clinically appropriate to preserve as much cognition as possible.

Due to the need for early identification, the campaign to educate consumers will likely be massive. It is expected to be more than six times the size of the public health campaign for COVID-19. The US government spent an estimated $350 million on advertising around the COVID-19 pandemic and COVID vaccine public health campaigns with the combined expenses from the Department of Health and Human Services and the Department of Education totaling $520 million. According to the congressional review of the FDA decision to approve Aduhelm (an early anti-amyloid antibody that received accelerated FDA approval, but not traditional approval), Biogen was expecting to spend $3.3 billion marketing the medication. 

Fewer than 1 in 5 Americans are familiar with MCI, but 12-18% of people over the age of 60 are living with MCI. In the US, if just 5% of people over the age of 60 ask their physician about MCI, it would be like screening the entire population of Los Angeles. Using standard tests, this screening would require a full year’s effort for more than 450 primary care providers. The likelihood that individuals will seek treatment is high: dementia tops the list of diseases people are afraid of having, and up to 85% of people worry about developing dementia. 

Although there are no guarantees for FDA traditional approval of an anti-amyloid medication or for coverage from CMS, health systems and clinics need to start planning now for the ground to shift with regard to patient questions and requests for Alzheimer’s disease testing later this year. Primary care providers are likely to field the bulk of these initial inquiries, which will stress a system that is already dealing with overscheduling and limited access to screening and early detection care. Providers that don’t plan now risk losing thousands of concerned patients to health systems and clinics that do prepare and are well-equipped to meet their demand for access to testing, education, and further diagnostics when necessary.

To prepare, health systems and clinics need to engage clinical and business operations for crucial areas such as: 

– Triage: What assessment(s) will you use? Who will administer them? How will you fit testing into your workflows?

– Confirming the diagnosis: Who should order PET-amyloid imaging? Where and when can your patients get access to imaging?

– Prescribing: Which providers should prescribe anti-amyloid therapy? Who will manage the necessary discussions on risks/benefits?

– Monitoring: Who will manage concerns for side effects and decisions about when to stop the therapy?

The justified excitement over a clinically meaningful medication for Alzheimer’s disease could quickly turn to frustration for providers, health systems, patients, and families – if they don’t prepare. Before patients are knocking on their doors, providers need to determine their pathways for triage, diagnosis, prescribing, and monitoring. This is a historic moment in the treatment of Alzheimer’s disease and we need to move fast to meet the challenges it brings.

About John Showalter, MD
John Showalter, MD, MSIS, is a dual board-certified primary care physician and Chief Product Officer at Linus Health, a digital health company focused on early detection in brain health. He previously spent five years as CPO at Jvion, a leader in clinical AI, and 10 years in leadership roles at health systems, most recently serving as CMIO and CHIO at the University of Mississippi Medical Center, where he also practiced clinically in internal medicine and family medicine.

Transcarent appoints Dr. Randy Hawkins as Chief Medical Officer (CMO) and will report to Transcarent Chief Executive Officer, Glen Tullman. As CMO, Dr. Hawkins will oversee the organization’s clinical quality initiatives and support the organization’s health analytics strategy.

Swift Medical has appointed Brian Litten as its new Chief Executive Officer effective immediately. Litten brings decades of healthcare leadership experience across health plans, provider organizations, regulatory agencies, and technology solution providers, with a proven track record of transforming and growing health technology pioneers. Previously, Litten held various leadership positions in transformational, value-based healthcare companies, including Tabula Rasa HealthCare (clinical pharmacy), StationMD (emergency telehealth), Pearl Health (risk-based primary care), PathForward (medical oncology), and Blue Cross Blue Shield.

GoCheck Kids, the leading digital vision screening platform for children, has named Naveen Kathuria as its new Chief Executive Officer. Kathuria brings deep experience leading healthcare organizations that serve vulnerable populations to his leadership role at GoCheck Kids, which is helping children thrive and pediatricians succeed by streamlining vision screenings into one efficient solution.

Carium, a Care Experience Platform (CXP) appoints David McCormick as Chief Operating Officer (COO) effective Feb. 2023. As newly appointed COO, David McCormick will provide leadership and insights into company operations, leading the sales and customer success teams.

In addition to this appointment, the company also announced the promotion within its leadership team of Julie Wolk to Chief Marketing Officer and Jessica Shandrowski to Vice President of Product & Customer Success.

Dr. Bill Roberts ACSM Chief Medical Officer

The American College of Sports Medicine® (ACSM) has named William Roberts, M.D., FACSM, as the organization’s new chief medical officer. In his new role, Roberts will develop strategy, provide guidance and lead collaborative efforts that address the professional needs of ACSM’s clinical membership and help grow, engage and cultivate clinical members and leaders. He also will provide clinical guidance on a variety of member and industry stakeholder issues related to ACSM’s sports medicine and clinical activities. 

Healthcare technology consulting and services firm Tegria appoints Raymond A. Gensinger, Jr., MD, FHIMSS as senior vice president and chief medical officer. A former chief information officer (CIO) and recognized expert on healthcare data analytics, Dr. Gensinger will take a leadership role in Tegria’s work to help provider and payer clients optimize and advance care through clinical transformation initiatives.

HHAeXchange has named Scott Schwartz as Chief Revenue Officer. After serving as Vice President and Senior Vice President of Sales & Marketing at HHAeXchange for six years, Schwartz’s next role will be instrumental in driving the company’s continued growth in the homecare market. 

In his new role as Chief Revenue Officer, Schwartz will lead HHAeXchange’s provider sales, business development, and marketing organizations. He will also continue to lead the company’s innovative Partner Connect program, enabling customers to directly connect their HHAeXchange platform with complementary solutions that drive efficiency and visibility.

Verato names Avi Mukherjee as chief product officer. Avi comes to Verato from Alphabet’s Verily where he served as head of customer solutions. He’s held positions across the healthcare and technology ecosystem including chief product officer at HealthGrades (acquired by WebMD), CTO at MAP Health Management and advisor at Redesign Health.  

CentralReach appoints SaaS finance expert, Rick Russo, as Chief Financial Officer. With over 30 years of experience in the technology space, Rick will be leading the company’s financial operations during this time of growth and will be a strategic thought partner to the leadership team as the company continues to meet the unprecedented demand for its market-leading Autism and IDD Care Platform. 

Tactile Systems Technology, Inc. (“Tactile Medical”; the “Company”) (Nasdaq: TCMD), a medical technology company providing therapies for people with chronic disorders appoints Elaine Birkemeyer as Chief Financial Officer, effective March 20, 2023. Ms. Birkemeyer will succeed Brent Moen, who is retiring.

AI-powered Patient Experience & Growth platform Steer Health announces two new team members: Greg Silvey as SVP of Growth and Beth Fleming as the VP of Customer Success. Greg has a successful career as a healthcare executive with leadership roles in start-ups and large multinational organizations. Beth is a seasoned healthcare executive with over 25 years of experience working in management teams of healthcare organizations and health tech startups. In their new roles, both will help Steer Health expand and deepen its partnerships with healthcare organizations across the U.S.

OFFOR Health appoints Shawn Nason as CEO, replacing CEO Saket Agrawal. Nason brings more than 25 years of experience in executive management, customer service and healthcare innovation to his role as CEO, including direct experience improving healthcare access and outcomes in rural communities.

Clinical-stage biopharma company Clene, Inc. (Nasdaq: CLNN) along with its subsidiaries “Clene” and its wholly owned subsidiary Clene Nanomedicine, Inc. appoints Benjamin Greenberg, M.D., M.H.S. as Head of Medical. An internationally recognized expert in treating disorders of the central nervous system, Dr. Greenberg brings extensive clinical and research experience to Clene as the company continues its development of CNM-Au8® as a potential treatment for amyotrophic lateral sclerosis (ALS) and multiple sclerosis (MS). Gemini BioProducts Holding, Inc. (“GeminiBio” or the “Company”), a portfolio company of BelHealth Investment Partners, LLC (“BelHealth”), a Florida-based healthcare private equity firm appoints Cory Stevenson as Executive Chairman of the Board of Directors

– A recent study by researchers at Intermountain Healthcare in Salt Lake City finds that following up a cardiac event, such as a heart attack, with a statin prescription and cholesterol-measuring blood test, prevents 94% of patients from having or dying from a second cardiovascular event during the next three years. 

– Having one cardiac event, like a heart attack or stroke, puts a person at high risk of having a second one. One in five people who have a heart attack will be re-admitted to the hospital for a second one within five years, and there are about 335,000 recurrent heart attacks in the U.S. every year, according to the American Heart Association.

Patient Safety-Oriented Cardiovascular Health Research

Headquartered in Utah with locations in eight states and additional operations across the western U.S., Intermountain Healthcare is a nonprofit system of 33 hospitals, 385 clinics, medical groups with some 3,900 employed physicians and advanced care providers, a health plans division called SelectHealth with more than one million members, and other health services. Helping people live the healthiest lives possible, Intermountain is committed to improving community health and is widely recognized as a leader in transforming healthcare by using evidence-based best practices to consistently deliver high-quality outcomes at sustainable costs.

The question for heart researchers is what can clinicians do to mitigate the risk of having cardiac events, especially soon after the first one.

“We already know that these patients are at a very high risk of having continued heart problems, and dying from heart disease,” said Kirk U. Knowlton, MD, principal investigator of the study, and director of cardiovascular research of the Intermountain Healthcare Heart and Vascular Program. “We wanted to see if interventions like a statin and checking in on their cholesterol levels make a difference. These results are astounding.”

Study results were presented at the American Heart Association’s Scientific Sessions 2022 in Chicago.

In the retrospective study, Intermountain researchers examined 68,411 patients who had a heart attack, stroke, or were diagnosed with peripheral artery disease between January 1, 1995 and December 31, 2016, and who survived that event. Researchers then analyzed whether or not those patients had a subsequent low-density lipoprotein-cholesterol (LDL-C) blood test, which measures for “bad” cholesterol, and/or statin prescription, and how they fared for up to three years or until death.

Researchers found that patients who did not have a follow-up LDL-C blood test or statin prescription were at a 60% risk of a second major cardiac event or death. In comparison, those who had a follow-up LDL-C blood test and statin prescription only had a six percent chance of a second cardiac event or death.

They say these findings reinforce the importance of follow-up care with patients who already have heart disease and are at a high risk of having a second cardiac event. “It’s important to the healthcare system that we make sure we offer patients every opportunity to be treated for their cholesterol levels and to make sure they’re maintaining medically directed therapy,” said Dr. Knowlton. “By following up with their physician, checking their cholesterol numbers, and continuing to take appropriate cholesterol-lowering medication, we can help our patients can extend their lives for years, even decades, to come.”

What You Should Know:

– Maribel Health, a turnkey partner for health systems looking to design, build, and operate a full continuum of advanced home and community services, announced today the completion of a $25 million Series A funding round led by General Catalyst. 

– The new funding will be used to accelerate growth with Maribel’s initial partners, to attract and onboard the talent required to serve its collaborators worldwide and to support continued investment and development of Maribel’s technology platform to manage the clinical workflows, care complexities, and logistics of providing advanced care safely and effectively in the home and community. 

Making home the center of the health system

Health systems face unprecedented challenges with capacity, workforce, and reimbursement. We work for health systems to design, build, and operate advanced clinical care models in the home and community to expand total capacity and improve access​.

In late 2021, Ronald Paulus, MD, a health system CEO, and Adam Groff, MD, a home and community services entrepreneur and hospital medicine physician, came together to enable health systems to respond to inevitable demographic shifts and workforce constraints driving care out of hospitals and into the home. Together, they founded Maribel Health to design, engineer, and operate the capabilities – including technology, clinical models, and operational management services – in order to enable the home and community to be increasingly central to both patients’ and health systems’ success.

Maribel focuses on solutions that augment the home-based workforce to deliver more advanced clinical services. As a technology-enabled operating partner of health systems, Maribel enhances capabilities and integration of existing home and community organizations to expand total health system capacity. Examples of work underway include building out hospital-at-home logistics and clinical operations, community-based palliative care, mobile integrated health / community paramedicine, and longitudinal complex chronic care with our partners.

Who Is Marbel?

Maribel Health is named in honor of Maribel Sanchez Souther who died in 2016 at age 41 after a two-and-a-half-year battle with triple-negative breast cancer. She lived an amazing life as a wife, mother of three, friend, Ivy League coach, and All-American runner. During her treatment, Maribel had multiple hospital admissions that took her away from her young family. Often, these issues could have been addressed more effectively in the home with the right support and technology. Maribel Health exists so that patients like Maribel receive the care they deserve where they need it most – in their home.

Maribel combines deep operating expertise with novel technology to help its partners design, build, and operate advanced clinical care capabilities in the home and community, including hospital-at-home, to sustainably expand total system capacity. Ultimately, Maribel’s mission is to make home the center of the health system so that all patients have access to high-quality, reliable, and compassionate care where they live and increasingly work.

Recent Traction

Collectively, the Maribel team has overseen over 15,000 hospital-at-home admissions, led the design of eight successful advanced home care programs, advised over 100 hospitals and health systems, and designed, developed and deployed technology used in the care of more than 8,000,000 patients.

In conjunction with this financing, Maribel also officially announced founding anchor partnerships with Mercy Health System and BAYADA Home Health Care in separate, joint statements. Both partnerships involve the end-to-end design, build, and operation of hospital-at-home programs that can serve as a chassis for other advanced home care models including community-based palliative care, SNF-at-home, and mobile integrated health.  

What You Should Know:

– Protai, a proteomics and AI-powered drug discovery startup revolutionizing the way new drugs are discovered, today announced a $12 million extension of its seed round, bringing the total amount to $20M.

– The round includes existing investors Grove Ventures and Pitango Healthcare and was joined by Copenhagen-based Maj Invest Equity Fund. The additional funding will be used to build Protai’s oncology drug discovery pipeline, expand data acquisition as well as increase its discovery activities via pharma partnerships.

Portai Launches Collaborations With Leading Hospitals and Expands Advisory Board

Genomic biomarkers are only relevant for approximately 15% of tumors, thus limited in use. Protein-level biomarkers can predict patient populations not seen by genomic means, by directly measuring proteins, their interactions, and their functions. To tap into the potential of protein-level data, Protai has built a proteomics AI-based platform that comprehensively maps the course of a disease on the protein level. Its technology allows it to better predict which patients will respond to a given drug, as well as discover novel drug targets that were missed by genomic approaches. These discoveries may be the key to significantly accelerating drug discovery and clinical development, lowering the time and costs of R&D.

Since its initial funding last year, Protai has opened laboratories at its Israel R&D center for data acquisition, biological validation and drug discovery activities and recruited an experienced drug discovery team with significant experience in successfully bringing drugs to the clinic. Additionally, Protai established collaborations with several leading hospitals, and now has access to over 100k well-defined banked samples for its comprehensive tumor mapping process, focused on gyno-oncology and lung cancer indications.

With the additional funding, Protai will expand its activities to include an oncology drug discovery pipeline, initially focusing on targets with a clearly-defined novel patient population biomarker, derived from its AI proteomics platform. To help navigate these efforts, the company has added Dr. Sharon Shacham, a serial biotech entrepreneur and Founder of Karyopharm Therapeutics, to Protai’s Board of Directors. In addition, Protai is supported by leading oncology experts, including Prof. Giulio Draetta, Chief Scientific Officer at MD Anderson and former Pharma executive; Prof. Bradley J. Monk, Director of Gynecologic Oncology at the St. Joseph’s Hospital and Director of GOG Partners; Prof. Funda Meric-Bernstam, Chair of the Department of Investigational Cancer Therapeutics at MD Anderson Cancer Center, and Dr. Jurgen Moll, former Head Molecular Oncology, Sanofi Vitry.

“We are excited to announce this funding that supports our mission to enhance the drug development pathway from discovery through to commercialization,” said Eran Seger, CEO and co-founder of Protai. “I am extremely proud of our talented team and the achievements we have made to date. We look forward to scaling our organization and its important work towards revolutionizing the drug development landscape.”