Readers Write: The Importance of Accurate Benefits Data in Healthcare

The Importance of Accurate Benefits Data in Healthcare
By Gary Davis

Gary Davis is national practice leader for Noyo of San Francisco, CA.

In the world of healthcare IT, there is so much to talk about. Digital transformation, automation, and new tech in the US health system is paramount, holding the promise of improved patient experiences, better health outcomes, and reduced costs, not to mention alleviating burden and burnout among healthcare workers. This crucial topic in healthcare today runs the gambit, covering everything from super advanced tech like artificial intelligence and blockchain to wearables, remote patient monitoring, telehealth, and interoperability among EHRs and other data sources like HIEs and more. 

I am here to address a less-sexy but important healthcare data topic – accurate insurance benefits data.

About 46% of Americans have employee-sponsored insurance benefits. The top benefit in the mix is healthcare insurance. Insurance benefits are focal to all our lives. It’s how we maintain health and wellness through healthcare, dental, and vision coverage.

Right now, many people are in the thick of the open enrollment season, making selections and completing enrollment paperwork, with teams of benefits administrators, HR, brokers, and insurance carriers fast at work getting everything complete and ready for the coming new year of coverage.

When I say “paperwork,” I mean it literally. The insurance industry is ripe for a technology upgrade. In 2023, carriers continue to rely on paper, web portal entry, email, phone, and electronic data interchange (EDI) for data exchange to support important functions of enrollment and member changes. The last major tech advancement in the insurance industry was EDI, and that was back in the 1970s.

Why the slow pace? The status quo is often the sector’s biggest hurdle. Paper-based systems and manual data entry dominate industry workflows. Many leaders think that it works, but not really. Manual data entry is fraught with inaccuracies and data sits in silos and is inaccessible. The lagging tech makes it challenging for benefits software, insurance carriers, brokers, and employers to keep key employee information in sync and drive innovation.

Our insurance benefits are confusing and hard to use, which that often means that services and money are left on the table by many. Just 9% of employees understand benefits terms like co-insurance. Meanwhile, choosing the wrong health plan can be a $2,000 mistake.

A 2023 Harris Poll consumer survey of 2,000 employed adults with employer-sponsored insurance benefits revealed that nearly half the respondents cited frustration when using their insurance benefits because they are hard to understand. Meanwhile, two in five indicated they have received inaccurate bills, have been unable to access care, or that their family has been negatively impacted due to delays because of errors in their insurance coverage.

Plus, because they don’t clearly understand what their benefits offer, many people wait to use their healthcare coverage until a health crisis hits, which isn’t good for the individual, population health, or payers.

In 2024, we predict that modern, frictionless benefits will take hold, enabled by API technology. These are benefits that are easy to use and to personalize to match the needs of individuals. Foundational to this new path forward, though, is accurate benefits enrollment data. There is a lot of inaccurate enrollment data out there, due in large part to decades-old technology in place in the insurance benefits ecosystem. The bad data is getting in the way of innovation and of people better who are understanding and using their benefits to their fullest.

API technology will pave the way forward. Payer organizations should have an API strategy and roadmap to guide them. You can build it yourself or team up with a trusted, visionary partner. Either way, 2024 should bring business imperatives to replace the technology status quo in the industry.

Readers Write: Trauma Thoughts

Trauma Thoughts
By Nicole Cook, APRN

Nicole Cook, APRN, MSN is a trauma clinical nurse specialist with WakeMed of Raleigh, NC and a clinical advisor for TraumaCare.AI.

The science and technology of healthcare is relentless in its pursuit of improvement and change. Techniques and practices that were once held as best practice have been improved upon or disproven, moved to the files of antiquity to be remembered fondly or with embarrassment as we realized that the sacred cow really wasn’t quite so golden. The evolution of care for traumatically injured patients is no exception.

Trauma nurses from 20 years ago would be flabbergasted to receive a trauma patient not on a long spine board. Mixing high-dose Solu-Medrol for an acutely injured spinal cord was cutting edge best practice. Peripheral IVs were flushed with heparin every eight hours, and we certainly preferred a good bolus of crystalloids before considering blood products. Yet now, every one of these interventions is no longer best practice. Our understanding of trauma pathology and care of trauma patients has evolved and will ceaselessly continue to do so.

Given the inevitability of change, trauma nurses must anticipate future shifts to our profession and the care and assessment of these critically injured patients. No new technology is poised to revolutionize healthcare more than the integration and incorporation of artificial intelligence and machine learning (AI/ML)-driven decision-making models into patient care and assessment. Never has technological and scientific change been so ripe with questions, apprehension, and seemingly limitless opportunity. 

We would be remiss to pretend that the last several years have not harshly affected healthcare and the field of nursing. Nurses have left the bedside, turnover in most healthcare organizations is at an all-time high, and uncertainty and change are our continual companions. As the future approaches, we look to lose more staff due to retirement as our patient population only continues to age and grow. Increasing the number of nursing educators and bolstering our nursing education pipeline cannot be ignored, but the impact of that would be felt years in the future. Staff need assistance now.

As healthcare moved into the digital age and EHRs became the norm, new challenges presented themselves. A deluge of digital data is filed into the record, often automatically. This is intended to improve decision-making, but the sheer volume often ends up overwhelming staff who may miss trends and changes among the pages and tabs of data. What was intended to make healthcare easier is resulting in information overload.

Imagine this not too unusual scenario. A busy emergency department, bursting at the seams. A nurse with a heavy assignment receives a multi-trauma patient after resuscitation who is now awaiting an ICU bed. Inpatient beds are at a premium, so the patient boards in the emergency department. This nurse has been well trained, but with a 1:5 nurse to patient ratio, it’s all they can do to keep up with basic tasks for their patients.

Minute changes in labs and assessment for the trauma patient indicate an impending worsening of clinical status, which is not readily apparent on the vital sign monitor. As the nurse treads water trying to keep up with their patient assignment, the very real risk exists that the nurse and care team will miss these subtle clues, leading to adverse patient outcomes.

Now consider one small change to this scenario. As the nurse logs into the EHR, they receive a notification of the impending clinical deterioration that was calculated by a decision-making model that is integrated into the record. The nurse notifies the admitting physician, who responds to the bedside. The clinical team reviews the notification and the pertinent data, adjusts the care plan accordingly, and the patient stabilizes. The nurse is also able to use this information to advocate that the patient be moved up in the queue to receive the next available ICU bed.

One of the concerns with any integration of technology into healthcare assessment is the potential for loss of clinical expertise and critical thinking that is secondary to overreliance. This concern is not unwarranted. The more our reliance on technology grows, the more it has the potential to pull staff from the direct bedside, facing away from the patient and toward a computer screen.

Nursing is an art and a science, twisted and entangled into one inseparable form. The anticipation of impending clinical deterioration is often described as a gut feeling, or simply “I am worried about this patient.” Artificial intelligence cannot replace nurse intuition and excellent assessment skills at the bedside. But this added layer of safety could be a constant background presence that is assessing and reassessing minute changes and alterations, as bedside nurses juggle ever-increasing documentation and regulatory requirements and a thousand little tasks that keep them from having the time to comb the data and see all the details.

Patient safety is created in layers. The Swiss Cheese Model is a well-known illustration of risk management and prevention. Layers upon layers of preventative measures and mitigation strategies result in improved safety. The integration of AI/ML can be seen as a robust addition to the Swiss Cheese Model due to its potential for adaption and development. Trauma nurses have a responsibility to investigate its potential in the evolution of our specialty to anticipate potential gaps in safety, equity, and education, and to take an active role in shaping this technology to assist us in caring for some of the most complex patients in all of healthcare.

Readers Write: 2024 Regulatory Changes and their Impact

2024 Regulatory Changes and their Impact
By Vatsala Kapur

Vatsala Kapur, MA, MPAff is VP of external affairs for Bamboo Health of Louisville, KY.

Change is on the horizon. This adage has always been true for the ever-evolving healthcare landscape, especially with the introduction of new federal and state policy and regulations.

As we step into the 2024 election cycle, we expect to see additional changes across the behavioral health realm in particular. Policymakers are implementing various financial penalties and incentives to increase accountability in expanding behavioral health access. These changes open a window of opportunity for organizations that are ready and willing to rise to the challenge of addressing our country’s behavioral health crisis.

Let’s delve into just a few of the dozens of changes that are aimed at improving healthcare delivery for our most vulnerable populations that may impact your organization in the new year.

• DHHS establishes disincentives for healthcare providers that engage in information blocking. The Department of Health and Human Services (DHHS) established disincentives for healthcare providers that are involved in information blocking. These disincentives include penalties of up to $394,000 for hospitals and $686 for individual clinicians who fail to share patient data upon request, underscoring the importance of data transparency. For organizations that are hindered by outdated systems, adopting real-time data systems integrated into daily workflows becomes a regulatory necessity and a pathway to improved patient outcomes.
• Introduction of the Rehabilitation and Recovery During Incarceration Act. If enacted, the Rehabilitation and Recovery During Incarceration Act represents a pivotal shift, allowing Medicaid to finance behavioral health treatment for eligible individuals in criminal justice settings. Effectively addressing the needs of justice-involved populations is crucial for hospitals and clinicians aiming to provide comprehensive treatment at all points of care.
• SAMSHA releases $74.4 million in funding opportunities. The Substance Abuse and Mental Health Services Administration (SAMSHA) plans to inject $74.4 million into the healthcare ecosystem through grants that target behavioral health challenges. These diverse grants aim to prevent substance use initiation, reduce the progression of substance use, and address other concerns along the health continuum. Notably, partnerships that focus on reducing substance use disorder prevalence through collaboration, each valued at $15.5 million, hold the potential to not only address behavioral health issues, but also expand access in rural areas.
• CMS shares notice of funding opportunity with the All-Payer Health Equity Approaches and Development (AHEAD) model. The Centers for Medicare & Medicaid Services (CMS) is set to collaborate with states through the AHEAD model, which is designed to curb healthcare cost growth, improve population health, and advance health equity. Increased investment in primary care is a critical element of this initiative, aiming to reduce emergency department burdens and better integrate behavioral and physical health. With a focus on value-based care, the CMS model plans to bolster primary care physicians as the first point of contact for behavioral health issues, thereby reducing the downstream effects of overburdened hospitals.

As federal and state governments focus on the significant behavioral health issues that are facing communities across the country, regulatory changes and evolving funding opportunities will continue to strengthen the ability of clinicians and health systems to address the needs of their patients and communities. By fostering a resilient and responsive healthcare ecosystem, we can collectively rise to the challenges ahead.

Readers Write: Breaking Down Natural Language Processing and Generative AI: How It Is Most Useful to Clinicians Today

Breaking Down Natural Language Processing and Generative AI: How It Is Most Useful to Clinicians Today
By Marty Elisco

Marty Elisco, MBA is co-founder and CEO of Augintel of Northbrook, IL.

Over the last year, the term generative AI has exploded on the healthcare scene, with health and social systems trying to determine if and how they can incorporate the newest tech trend into their day-to-day practice to streamline and improve operations and ultimately improve patient care.

But most organizations have decided to take a measured approach and see how the hype plays out. They have decided to proceed thoughtfully and with diligence before viewing generative AI as the panacea to all things healthcare.

I’ve been working in health tech for 15+ years, and I’ve yet to see any generative AI applications exit the proof-of-concept phase and enter the production phase. Along similar lines, I’ve noticed that almost all articles in healthcare talk about the promise of generative AI rather than its results.

After all, when you consider the true definition of generative AI – the ability to generate language – we must ask ourselves, is this really helpful? Do clinicians really want a tool that can generate language on its own, which treads close to replacing their own clinical judgment? Remember what it is that clinicians really need — to receive the information needed to understand patients and improve the quality of care. Generative AI isn’t needed to accomplish this.

Generative AI has two steps. The first is to identify the relevant historical data. The second is the generative part, to take that historical and reconstruct it as a summary. The first part is accomplished through natural language processing to gather the relevant data. This technology is well proven, and I believe is 90% of what clinicians need.

The second part, using generative AI to summarize this data, is the remaining 10%. This is what has created all the hype. But this part is clearly not yet proven.

The distinction above between “creating new content” and “gathering relevant content” is an important one to make. I believe the latter is significantly more useful to clinicians, because the more that they are informed with relevant content, the more context they have to make decisions with the patient.

In fact, the impact of a tool that can gather content has already been realized and has been proven in clinical settings across healthcare in the following ways:

• Helping clinicians identify critical behavioral and social gaps in care, where this content is completely contained in the unstructured data.
• Understanding relevant patient history so that the clinician can make the most informed decisions.
• Identifying risks, early warning signs, and care quality issues across patient populations that may go unnoticed by the clinician.
• Understanding community-level trends that enable a health system to offer the right balances of services to the populations they serve.

I believe that the value of the above proven use cases, especially with regards to quality of care receive, generally outweigh the value of the top prospective generative AI use cases:

• Drafting patient notes for clinicians to finalize.
• Automating chatbot correspondence with patients.
• Suggesting clinical care plans.

I believe that as we head into 2024, the industry should begin to focus more heavily on the identification of actionable content instead of the creation of new content. As we close out 2023, generative AI has become part of the culture, but let’s avoid getting caught in the hype and focus on how to deliver value today.

Readers Write: How Hospitals Can Harness Identity Access Management to Mitigate Cyberattacks

How Hospitals Can Harness Identity Access Management to Mitigate Cyberattacks
By Ferdinand Hamada

Ferdinand Hamada is managing director of healthcare cybersecurity for MorganFranklin Consulting of McLean, VA.

On Thanksgiving Day, Ardent Health Services was hit by a ransomware attack that disrupted ambulance routes for hospitals in New Jersey, New Mexico, Oklahoma, and Texas and forced them into diversion mode, unable to accept new patients or perform some surgeries. This is just the latest alarming example of rising attacks on healthcare organizations, making it more critical than ever to maintain visibility over who and what is connected to hospital networks.

With these increased risks — coupled with an uptick in mergers and acquisitions (M&A) plus the ongoing issue of attrition in the industry with 60% of all healthcare support workers expected to leave their jobs within five years — ensuring that identities are managed appropriately is critical to mitigate these risks.

To improve security during these times of flux, hospitals should proactively develop a centralized identity access management (IAM) system to combat increased vulnerability to attacks. IAM systems help identify potential access and permissions risks, which makes them an essential part of hospital cybersecurity programs. By detecting access disruptions in advance and implementing solutions to manage them, hospitals can reduce their impact on patient safety, revenue, reputational loss, and operations.

To create a robust and sustainable IAM program, here are three areas that hospital IT and security teams should focus on:

Limit access to reduce risk

In many hospitals, staff have access to more systems than they need to perform their core duties. To keep information safe, access to data and other valuable assets should be limited and permissions requests should be accurately validated. There are several ways to reduce access across hospital systems, but no one approach stands alone. Determining the best combination of strategies will depend on how an organization currently accesses data and its larger security objectives.

• Web single sign-on. Multiple parts of an organization’s internal and external web presence require user authentication and authorization to properly secure sensitive data. Web single sign-on frameworks simplify this process by maintaining a user’s authenticated state throughout their entire web session.
• Adaptive access. Different information and resources carry different levels of risk. Adaptive access enables an organization to easily require more robust authentication for riskier assets while easing accessibility for low-risk resources.
• Reverse proxy. A reverse proxy sits behind the company firewall and forwards web requests to a server for response. This simplifies the user experience and reduces the amount of information about an organization’s internal network structure that is shared with third parties.
• Federation login. Contractors and partners require limited systems access, but creating accounts within an organization’s identity management system is time-consuming and adds complexity. Federation enables secure identity sharing across organizations by simplifying authentication and access management for partner organizations.

Implementing new or updated access procedures should also work with existing internal or external frameworks, policies, and technologies. This enables a seamless transition to a new IAM model, promoting appropriate access to data and resources across an entire organization.

Develop onboarding and offboarding checklists to manage employee permissions

While security programs are often focused on mitigating external threats, employees can pose the same or greater security risk to hospitals and patients, whether purposefully or accidentally.

Human security risks come in a variety of different forms:

• Social engineering and phishing. Social engineering attacks aim to gain physical access to a secure area or system using human interaction. These attacks often occur using convincing messages for phishing. Phishing can happen via email, telephone (voice phishing or vishing), text message (SMS phishing or smishing), and even on social media.
• Insider threats. Insider threats are caused by employees, contractors, and vendors who have access to the hospital’s systems, and they can occur unintentionally, intentionally, or collusively.
• Negligent behavior. Employees can also inadvertently place data and security at risk by doing things like insecurely using applications and devices or sharing passwords.

These types of human-based threats can also increase during transitional periods, so it’s important to have IAM plans and processes in place to minimize their risks. Developing checklists to control access during onboarding and offboarding processes can help ensure smooth changeovers. Additionally, employee security training should include how to manage security risks within your specific organization in addition to traditional threats like phishing and reporting lost devices.

Implementing a centralized dashboard for IT teams that provides real-time monitoring, remote access and automated alerts

User rights and privileges, or simply who in an organization has access to what data and systems, need to be readily visible to an IT team. Using IAM platforms and tools provides a scalable and automated foundation for compliance controls, access requests, password management, and identity-enabled visibility.

Implementing a centralized IAM system enables an organization to achieve full visibility and control over its information. These solutions can also help reduce manual workload and save a security team’s time. For example, automating standard procedures and threat alerts can give IT teams more time to focus on real-time monitoring and intercepting potential remote access threats.

As the healthcare industry continues to face increased cybersecurity threats, hospitals will operate more safely by better-protecting data across their organization. Securing employee and device access and implementing a centralized management system to monitor sensitive information should be a key pillar of any hospital business plan. Ultimately, the robust protection of IAM programs mitigates risk and protects sensitive patient information, systems, reputations, and revenue.

Readers Write: AI: The Prescription for Healthcare Troubles

AI: The Prescription for Healthcare Troubles
By Andrew Lockhart

Andrew Lockhart, MBA is co-founder and CEO of Fathom of San Francisco, CA.

Healthcare in America is grappling with a severe workforce shortage, with the closure of physician staffing firm American Physician Partners (APP) earlier this year adding fuel to the fire. Healthcare leaders are searching for a solid solution to address the workforce shortage, and it looks like artificial intelligence (AI) is the answer.

APP’s shutdown follows Envision Healthcare’s footsteps. Both firms cited financial problems as the reason behind their closures. The shutdown of two staffing giants sent waves of panic throughout the already stressed and understaffed healthcare system, and the fallout has shone a light on the already glaring vulnerabilities within the industry.

The lack of workers is affecting emergency medicine, hospital medicine, and critical care management departments, among others, and the future looks even bleaker. An industry market report by Mercer predicts that by 2025, the US will have a shortage of a shocking 95,000 nursing assistants and 98,700 medical and lab technicians, among other worrying figures. This shortage is already negatively impacting the patient experience and safety, with the Joint Commission reporting a 19% rise in adverse events in 2022.

In response to these challenges, technology, particularly AI, is emerging as a crucial component in healthcare operations. Given the current state of healthcare, there is no way for organizations to provide the volume of level and care that patients expect and deserve without some form of automation. Here are three critical ways AI improves healthcare services.

Augmenting Workforce

As staffing shortages become increasingly prevalent, AI offers a scalable solution to address gaps in critical areas. AI provides a lifeline to stressed-out staff by reducing admin burdens and automating repetitive tasks. It frees up precious time for clinical and administrative staff to upskill and operate at the top of their license, maximizing the potential of the entire workforce.

For example, the American Medical Association (AMA) found that healthcare is facing a deficit of experienced medical coders, 30% to be exact. The average medical coder is aging out, and there are few coders ready to take their place. Autonomous coding helps health organizations improve accuracy, reduce denials, and make quicker reimbursements. Another bonus of AI coding is its ability to adapt to complicated new coding guidelines easily, ensuring compliance and accuracy.

Improving Operating Margins

McKinsey reports that healthcare organizations are feeling the strain of financial pressure because of rising inflation and a faltering economy. AI can support the careful balance of maintaining high-quality patient care and optimizing costs by streamlining revenue cycle management (RCM). AI optimizes RCM by automating processes and reducing paperwork, boosting patient satisfaction. More tangibly, it produces measurable cost savings, reduced denials, faster turnaround times, and improved revenue capture.

Attracting Top Talent

Incorporating AI tools into an organization’s workflow is a great way to entice top-tier candidates in an increasingly competitive labor market. Normalizing AI’s use throughout an organization signals to job seekers that innovation is a priority, which is incredibly appealing to the younger generation. Younger prospects also have higher expectations for AI to enhance their day-to-day operations and associate it with cutting-edge projects.

To proactively address workforce challenges, C-level professionals need to strategize for the future, and AI is a long-term solution to build a resilient healthcare workforce. When bringing on new technology, leaders must foster an environment that encourages using AI and be intentional about change management. Technology is only as good as the people who use it, and any solution requires a robust rollout plan with alignment from the entire company. To successfully deploy new AI, look for a vendor with a dedicated customer success team to walk you through any potential road bumps, or set up a steering committee or other governance to lead and finalize AI decisions.

Aside from the multitude of financial, administrative, and HR benefits, adopting AI will also make disruptive events like the closure of APP easier for organizations to bounce back from. With a sturdy AI strategy, organizations are well-positioned to weather any future storms.

AI is gathering speed and changing the face of healthcare. Leaders need to lean in and embrace it or risk getting left behind. Working with AI, healthcare organizations can help address workforce woes, attract a new generation of talent, and have long-term resilience. The time to act is now.

Readers Write: Embracing the Gig Economy: Why CIOs Should Leverage Digital Platforms for IT Talent

Embracing the Gig Economy: Why CIOs Should Leverage Digital Platforms for IT Talent
By Daniel Schubert

Daniel Schubert is co-founder and CEO of Revuud of Charlotte, NC.

The gig economy has rapidly emerged in the corporate realm, commonly referred to as digital platform work or the freelance economy. It represents more than just a passing trend. It is a revolution that is significantly transforming the traditional work landscape.

While the broader workforce is attracted to the appeal of flexibility and independence, there is a particular emphasis on CIOs. They are encouraged not only to adapt, but to excel in the digital revolution by using talent marketplaces, enabling them to find high-quality IT resources at a significantly reduced cost

According to a recent study, 42% of the total workforce comprises 1099 workers, independent contractors, or freelancers. Additionally, the report highlights a significant trend, with 90% of companies transitioning towards a hybrid model that incorporates both full-time and freelance employees.

This data underscores the evolving landscape of employment in the enterprise tech sector, reflecting a notable shift towards flexible and diverse workforce structures.

Conventional recruiting for CIOs may seem extravagant. Gig workers present a cost-effective alternative, providing specialized skills without the substantial overhead costs tied to full-time employees. By leveraging hiring platforms, CIOs can experience on average 30% savings per contractor within the first six months alone.

The gig economy thrives on technology, and digital platforms can function as matchmakers and entire wedding planning committees. These platforms streamline the hiring process, eliminating the need for extensive recruitment efforts and minimizing the time investment required from CIOs and their teams.

Gigs in the IT sector are akin to short-term relationships without the emotional baggage. They align seamlessly with project-based, task-focused approaches, making them ideal for CIOs who are seeking flexible and efficient solutions to their talent needs. By leveraging hiring platforms, CIOs can scale their IT talent up or down based on organizational needs.

Gone are the days of the traditional 9-to-5 grind. Gig workers seek the freedom to craft their professional endeavors on their terms. The gig economy’s appeal lies in the liberation from conventional work structures, making it imperative for tech leaders to consider alternative approaches to sourcing talent.

Gig opportunities emerge and vanish swiftly. The conventional snail-paced recruitment processes are inadequate in this scenario and are unnecessarily costly. CIOs need to channel their inner Flash with a laptop, adapting quickly to the demands of the gig economy. Lengthy recruitment cycles are relics of the past. The emphasis is now on agility and responsiveness.

In the gig economy, it’s not about impressive degrees or a wall adorned with certificates. It’s about skills. For CIOs who are seeking high-quality IT talent, leveraging hiring platforms becomes paramount. These platforms connect businesses with IT professionals based on demonstrated capabilities rather than relying solely on formal qualifications. It’s akin to ordering a customized solution – precise and efficient.

In conclusion, the gig economy is not merely a passing trend. It signifies a profound shift in the professional landscape. As individuals increasingly gravitate toward the flexibility and independence offered by gig work, CIOs should abandon old norms and capitalize on the transformative potential of the gig economy to position themselves not just as adaptors, but as thriving pioneers in the ever-evolving digital realm.

Readers Write: The Interoperability Revolution Continues

The Interoperability Revolution Continues
By Mark Gingrich

Mark Gingrich, MS is chief information officer of Surescripts of Arlington, VA.

Remember when you would leave your doctor’s office with a handwritten paper prescription, and then need to bring it to the local pharmacy to be filled? Hard to believe that was the norm just two decades ago.

The height of innovation was swapping out this piece of paper for an electronic transaction. It was a simple enough concept, but the impacts have turned out to be profound. Electronic prescribing helped revolutionize how care providers and patients shared information, making prescribing safer and faster and connecting prescribers and pharmacists like never before.

Now, 60,000 pharmacies are connected and 2 billion prescriptions were filled using this technology in 2022 alone. E-prescribing serves as the basis for what we now consider healthcare interoperability, but the scale of healthcare interoperability advances every day. Our company, through subsidiary Surescripts Health Information Network LLC, has submitted its application to become a Qualified Health Information Network (QHIN) under the Trusted Exchange Framework and Common Agreement.

But what does healthcare interoperability mean for patients and clinicians? The definition can be something different depending on the stakeholder, yet the definition is far less important than the impact that healthcare interoperability has had and will continue to have in transforming patient care.

The impact is seen when clinicians have the right patient information, such as medication history and clinical documents, at their fingertips, at the right time, and can provide safer, better informed, and less-costly care for their patients. This means stronger, trusted relationships between patients and care providers.

Our company’s master patient index makes it possible for health information for nearly every patient to be accessible by 2 million care providers. Interoperability means connecting 250,000 clinicians across all 50 states and Washington, DC to access 100 million clinical documents each month in 2022, delivering the information they need to care for their patients in the most meaningful way possible. Applying to become a QHIN is the next step towards amplifying our impact in ensuring that care providers can quickly and easily access the information that they need to provide safe, quality, and lower-cost care for their patients.

Readers Write: Five Takeaways from The Sequoia Project’s Annual Meeting

Five Takeaways from The Sequoia Project’s Annual Meeting
By John Blair, MD

John Blair, MD is CEO of MedAllies of Fishkill, NY.

I recently attended the annual meeting in San Diego of The Sequoia Project, a non-profit that advocates for health IT interoperability, and was impressed with the spirit of collaboration and optimism as stakeholders look forward to taking the next steps toward making interoperability a reality.

Without a doubt, interoperability has been a top-of-mind subject for many years for many of us in attendance, but the issue has gained renewed focus recently, as Qualified Health Information Networks (QHINs) are poised to launch.

QHINs are an essential component of The Trusted Exchange Framework and Common Agreement (TEFCA), a new regulation backed by the federal government and intended to improve interoperability. TEFCA’s goal is to establish a universal floor for interoperability across the country by developing the infrastructure model and governing approach for users in different networks to securely share basic clinical information with each other.

In addition to QHINs, other key issues discussed included: interoperability use cases, the benefits of Fast Healthcare Interoperability Resources (FHIR), the unique challenges to health information exchange for public health, and how today’s patient experience can be improved leveraging existing technology and investments.

My five biggest takeaways include:

1. QHINs will be quickly migrating customers from their current networks to the new QHIN networks.
2. Although QHINs will be competing for customers, they plan to cooperate with each other as the networks become operational. They understand that a network of networks is only as good as the weakest network, and it’s essential that they help and support one another in day-to-day operations. Without cooperation, customer support will suffer and the overall success of QHINs will be at risk.
3. Interoperability stakeholders are anxious to get the current uses up and running. These use cases include treatment, individual access services, payment, health care operations, public health, and government benefits determination.
4. Although the treatment use case has been active for many years, there is still work to be done around data quality, quantity, and end-user workflow.
5. Data usability is set to take center stage. A plethora of health data is already being exchanged, but its value is often limited due to issues with normalization, fragmentation, and usability. QHINs will help solve these limitations by driving greater accuracy and completeness of patient health data.

Open questions remain regarding the ultimate effect that TEFCA and QHINs will have and their ability to generate nationwide interoperability improvements. However, the energy and enthusiasm that were palpable at the Sequioa Project’s annual meeting will likely fuel efforts to overcome inevitable roadblocks as stakeholders work to address current and future regulations and advance efforts to increase the volume and utility of health information exchange.

Readers Write: Navigating the Telehealth Regulatory Labyrinth

Navigating the Telehealth Regulatory Labyrinth
By Sheeza Hussain

Sheeza Hussain is chief growth officer of SteadyMD of St. Louis, MO.

Telehealth has the potential to amplify its impact on healthcare access while further reducing costs, but a web of state regulations is hindering that promise.

Telehealth became a household term for millions of Americans in 2020, emerging as a vital component of healthcare delivery. It helped bridge the gap caused by clinician shortages, tackled certain social determinants of health, and facilitated care for rural patients who otherwise struggle to access it.

However, the rapid expansion of telehealth has exposed a glaring issue – a labyrinth of regulatory and legal obstacles. State licensure variability, reimbursement policies, telehealth parity laws, cross-state regulations, and other hurdles continue to impede adoption.

Licensure is just one complicating factor in the telehealth regulatory maze. Many states have differing regulations on nurse practitioner scope of practice, with variance in whether NPs can operate independently, require physician oversight, or are restricted entirely. This patchwork hinders multi-state advanced practice clinician telehealth.

Additionally, certain modes of virtual care like asynchronous visits face ambiguity, as some states allow reimbursement while others prohibit or fail to address it. Like licensure, these state-by-state discrepancies in nurse practitioner and asynchronous visit policies make scaling telehealth availability and minimizing legal risk complex for providers. Overcoming the regulatory headaches requires close tracking of each state’s evolving rules.

Among the three primary challenges, the perplexing variations in state licensing rules are the most significant.

Healthcare providers are required to be licensed to practice in the state in which their patient resides. In some cases, patients are forced to cross state borders to receive telehealth services from their chosen physicians.

The disparities in telehealth policy between states are glaring. For instance, North and South Dakota, as well as Virginia and West Virginia, don’t see eye to eye on telehealth regulations. This patchwork of policies is emblematic of the broader problem – 50 states, each with its own set of laws, medical communities, and stakeholders, all contributing to the complexity of telehealth regulation.

The existing state-by-state licensure processes are antiquated, leaving telehealth companies that operate in multiple states grappling with a complex and ever-changing regulatory landscape. A common requirement is that telehealth providers must hold licenses in the state where their patients are located. However, this doesn’t simplify telehealth; it complicates it further. Most providers are licensed only in one or two states, limiting their usefulness to telehealth companies operating across several states.

Obtaining licenses in additional states is a costly and time-consuming endeavor for telehealth companies. They must build a roster of multi-state providers, carefully manage supply and demand, and ensure compliance with the laws of each state they serve.

Calls for modernizing licensure portability have gained momentum, with some advocating for a standardized federal system akin to driver’s licenses. However, this transformation won’t occur overnight. As telehealth becomes increasingly integrated into healthcare, state regulations may eventually become more uniform, but this change is unlikely to happen soon. The healthcare industry can advocate for greater licensure portability, such as the implementation of a standardized federal licensing system, but providers need relief now.

In the meantime, telehealth providers are seeking alternative solutions. Many are opting to partner with telehealth infrastructure providers that guarantee compliance with state laws, recruit and manage providers, and stay current with shifting regulations. By entrusting an external partner to navigate the intricate regulatory landscape, telehealth providers can focus on what truly matters – providing the best care to their patients.

Readers Write: Surviving the Blizzard: How Technology Can Ease Specialty Medication Re-Enrollment Season

Surviving the Blizzard: How Technology Can Ease Specialty Medication Re-Enrollment Season
By Julia Regan

Julia Regan, MBA is founder and CEO of RxLightning of New Albany, IN.

One of the most challenging times of the year for providers, medication access staff, biologics coordinators, and other team members who support specialty medication onboarding is re-verification and re-enrollment season, which is aptly known as Blizzard Season.

While insurance selections are finalized and patients are counting down the days until the new year, coverage modifications on the back end can cause significant challenges in medication access. Most common adjustments include updates to a coverage policy and a new prior authorization requirement, reset deductibles, the end of co-pay assistance and patient assistance programs (PAP), or the selection of an entirely new insurance provider.

Some of these changes can wholly prevent the continuation of medication fulfillment, while others – like deductible and financial assistance resets – may surprise patients enough to forego the unexpected costs and immediate adherence to their meds.

Manufacturers, hubs, and patient support groups often hire small armies of workers to meet the influx of benefits verification demands, but this model is inefficient and expensive. While much of the work cannot be started until updated forms and insurance details are finalized, a robust Blizzard Season plan is a necessity.

To accelerate the benefits verification process and reduce the resources and costs required, providers should understand which plans, manufacturers, FRMs, and hubs they may be working with, and proactively collect as much information about coverage changes and patient health changes so that re-submitting paperwork can be more nearly seamless. Additionally, teams should communicate with patients early to understand who may be changing plans, alert them of potential upcoming requests such as signatures required and plan details, and support them through this confusing time.

While many programs transition on January 1, enrollment or PAP forms are often available 1-2 months ahead of time, enabling teams to get a head start on the re-enrollment process. With the right plan of attack, as well as the right technology, Blizzard Season can be more efficient and straightforward.

There will always be a need for real people to manage some of the more complex patient cases, wherein new coverage restrictions, financial assistance, or prior authorization is required to continue a patient’s care regimen. However, a significant portion of re-enrollments and re-verifications can be streamlined by using technology.

In many cases, the first step for re-enrollment is finding the appropriate medication or PAP paperwork and completing the paper form correctly. While this may seem simple, completing thousands of paper forms is a tedious and error-prone task. With new digital enrollment technologies, providers and care teams can be assured that they are completing the most up-to-date form with no missing information, greatly reducing the risk of a downstream issue in the application.

Another important step that can be streamlined with technology is (re)confirming the patient’s insurance and completing an eligibility and benefits check. Instead of manually scrolling through documents on a plan’s website or calling a representative to confirm coverage, real-time connectivity can accurately display a patient’s plan details while providing insight into cost and restrictions required, reducing time spent confirming details and allowing stakeholders to move on to more complex steps of the process.

Next, collecting consent. While patient and provider signatures are necessary to re-enroll for a specialty medication or PAP, with the click of a button, email and SMS notifications can be sent to appropriate stakeholders to securely sign documents from wherever they might be. No waiting until the next in-person visit or stop by the desk to collect a signature. Instead, consent can be collected remotely in a matter of seconds.

As mentioned, with deductibles, co-pay, and PAP all resetting, it is essential for technology to surface affordability options that can support patients, whether through long-term PAP enrollment, foundation or grant support, or short-term, low-cost options that a patient can receive in the interim while their specialty medication enrollment is being finalized. With an interconnected network of coupon and discount providers, care teams can easily identify and communicate with patients about affordable options that are available to them.

One of the most time-consuming tasks of the re-enrollment process is filtering which patients are qualified for PAP or financial assistance programs. Major credit check companies now allow technology vendors to connect into their systems to provide real-time insight into income and credit score, enabling an initial verification of assistance eligibility. Using this technology can greatly fast-track certain patient cases over others.

The unfortunate truth is that manufacturers, hubs, patients, and providers all have work to do to complete a specialty medication re-enrollment successfully. However, from digitized forms to automated eligibility checks, and digital consent collection to real-time notifications, the process to re-enroll a patient is more streamlined, personalized, and error-free than ever before.

With a thoughtful plan, innovative technologies, a robust ecosystem, and proficient staff, Blizzard Season can require less resources and time, enabling what matters most, consistent care with no lapse in medication access.

Readers Write: Bracing for the Silver Wave: How to Design a Healthcare Technology Stack Built for the Future

Bracing for the Silver Wave: How to Design a Healthcare Technology Stack Built for the Future
By Amanda Hansen

Amanda Hansen is president of AdvancedMD of South Jordan, UT.

For some time now, the healthcare industry has been focused on preparations for the coming Silver Wave, the first time in our nation’s history that adults over the age of 65 will outnumber children 18 years old and younger. This dramatic shift in age demographics has major implications for healthcare providers and the patients they serve. As patient populations age, physicians and their staff will need to reconsider everything from the services they provide and the ways they deliver care to the technology solutions that underpin their systems.

Private medical practices are especially vulnerable to the coming changes. Without the resources and budgets of large healthcare networks, many private practices will face a number of challenges associated with the Silver Wave, some of which have already taken root. Chief among these challenges is ineffective technology solutions that fail to meet the needs of an aging patient population. Few private practices have a crystal ball to help them plan for the future, but there are definite steps healthcare providers can take now to prepare for transitions ahead.

As we enter the beginning stages of the Silver Wave, EHR systems will be even more critical to the patient experience. The increased demand for healthcare services that come with caring for older patient populations translates to increased EHR use and greater need for truly interoperable systems.

The impending shifts associated with the Silver Wave require technology solutions that can effectively manage multiple components of care, from basic patient demographics and healthcare records to complex healthcare services often related to elderly patients. Private practices will need EHR systems that can accommodate and support patient records with multiple healthcare providers, complex treatment plans for chronic illnesses, and increased prescriptions, all dynamics connected to elderly care.

EHR platforms are a crucial component of every healthcare technology stack, now and even more so in the future. Without the right solution in place, interoperability becomes a major obstacle that can significantly impair patient outcomes, the financial health of the private practice, and the overall patient experience, a challenge that will be more difficult to overcome as we near the massive shift in patient ages.

During the pandemic, telehealth became an essential healthcare delivery model. It also opened the door to all new opportunities for underserved patient populations, giving rural areas access to a broader selection of healthcare services and providers. In the last few years, telehealth adoption rates have continued to skyrocket. Now, as the healthcare industry faces a future with more patients over the age of 65 than under the age of 18, telehealth and other alternative healthcare delivery models will become integral to the healthcare experience.

Fortunately, many private practices have already tapped into the potential of telehealth, offering virtual visits to patients who desire more flexibility and convenience when scheduling doctor appointments. For aging patient populations, telehealth is no longer a “nice to have,” instead, it becomes a critical need for people unable to leave their homes. Telehealth, combined with at-home care services and remote patient monitoring (RPM) devices, enable healthcare providers to deliver comprehensive treatment to those most in need.

Similar to effective EHR platforms, alternative healthcare delivery models demand technology solutions that enable seamless processes. Telehealth platforms that are safe and secure, but also offer intuitive user-interfaces ensure physicians can care for all of their patients. At-home care requires technology that allows healthcare providers to update patient records in real-time outside of their office. Same with RPM devices: physicians need technology platforms that effectively integrate with RPM solutions to monitor things like blood pressure, heart rate data, and other medical details for at-risk patients managing chronic illnesses.

Many of the technology solutions that will help bolster healthcare services for the coming silver wave are primarily implemented and managed by the healthcare provider, but it’s important to acknowledge how they will impact the patient. While some may assume that an elderly patient population may be tech-averse, recent reports have revealed just the opposite.

After surveying more than 21,000 adults over the age of 55, McKinsey Health Institute discovered the smartphone was the preferred technology device for the vast majority of respondents ages 55 to 64. Nearly 50% of this same age group listed a tablet or laptop as their preferred device. In fact, when it came to barriers around embracing technology, survey participants cited cost and lack of knowledge. In other words, cost-effective technology paired with effective training that teaches patients how to use various tech devices and apps could mitigate many of the technological challenges facing older patients.

It’s worth noting that the silver wave will include a segment of Generation X, the first generation to use email, search the internet, and download songs to their iPod. If ever there was a generation primed for digital healthcare services, Gen X is it. In the same way an early diagnosis allows for improved patient outcomes, early investments in highly effective technology will enable private practices to establish a robust foundation that not only delivers immediate gains but will sustain their practice during the coming silver wave and all the challenges it will bring.

Readers Write: Easing HCC Coding Adoption by Using Insights and Assessment for More Accurate Data

Easing HCC Coding Adoption by Using Insights and Assessment for More Accurate Data
By Shahyan Currimbhoy

Shahyan Currimbhoy, MS is vice president of product of Edifecs of Bellevue, WA.

Healthcare provider organizations that are participating in Medicare Advantage plans are acutely focused on the adoption and execution of Hierarchical Condition Category (HCC) coding. HCC is a healthcare risk adjustment model that is used to predict the healthcare costs of individuals or populations based on medical conditions. Adoption requires disciplined and accurate documentation and coding of all relevant medical conditions to properly reflect the health status of patients. Accuracy is critical. Even the slightest inconsistency or error can impact risk scores and subsequent reimbursements to providers.

HCC coding is an important model for healthcare reimbursement risk adjustment because it offers the benefit of accurately predicting healthcare costs. Unfortunately, as it has been put into practice, it has elevated some operational challenges. It’s no secret that coding has long-been an administrative burden on the healthcare system. Over time, we’ve learned that automated, integrated, and system-wide technology can help reduce these burdens. In the present evolution of our healthcare system, we also know the viability of value-based care (VBC) desperately depends on alignment between documentation, provider engagement, and claims coding.

The implementation of HCC coding requires a thoughtful approach. If done right, organizations could quickly see opportunities to refine and improve the encounter documentation process and care delivery.

Your HCC Coding Approach: Collaborate with Clinicians

As care teams recognize HHC coding as a critical component of an organization’s business model, identifying the right deployment approach is an important early step. Each health system will take a different approach, but change must be met with ease and collaboration. Organizations that attempt to move into alternative payment models (APM) by flipping the switch overnight on new processes or technologies will encounter pushback from care teams and coding staff. Value-based payment participants will have a better outcome if they ease into the transition, including starting with tools that are made for VBC, and weaving them into the existing team structure and processes.

Care teams and coding staff will have questions. Will HCC coding be addressed before, during, or after the visit? Will coders and clinicians collaborate in person or electronically? Consult your clinicians before determining the best approach. Excluding them will undoubtedly result in a missed opportunity to best understand how strategy could impact their day-to-day workflows, which can lead to a more challenging implementation process.

A collaborative approach will result in more accurate coding in the long run, playing a huge role in reducing the time providers are spending confirming or rejecting a suspected condition.

Coding Insights and Provider Education Support Entering High-Risk Sharing Arrangements with Confidence

Even with automation and collaboration tools, care teams that have incorporated HCC can still find themselves coding inconsistently. For leadership to understand where education and resources are needed, there needs to be provider-level visibility of coding efficacy. Without data-driven insights into provider quality risk operations, this can prove challenging.

With the proper sources, providers can build patient registries, identify where the patients are, and build standard care pathways to ensure that patients are getting proper care. Leadership can gather the clinicians to share knowledge and identify variations in care. Treating HCC coding as a discipline, rather than as an administrative or financial function, helps ensure alignment between providers and the coding team, which drives improved patient outcomes.

Organizations with confidence to move into high-risk sharing arrangements can use automation and natural language processing (NLP) to drive scalability, collaborative tools that allow care teams to work in unison, and performance analytics to help the whole care team continue to improve.

Using “MEAT” to Fully Assess New Conditions Against Patient History

VBC payment models often require a comprehensive understanding of a patient’s medical history, always culled from various sources and locations. Consolidating diagnostic codes linked to HCCs becomes difficult when a patient is treated at multiple departments within a clinically integrated network (CIN) with separate EMRs. In today’s state of financial resources, the right integrations and automation tools are key.

Organizations are empowering clinical review specialists by giving them a comprehensive view of each patient’s medical history, as well as the tools needed to help identify the gaps in care. If medical history is reviewed prior to an encounter, it can reduce some of the burden on clinicians during the patient visit. With the comprehensive view and additional time, providers can better assess new potential conditions using the acronym “MEAT” as suggested by the AAPC (monitoring, evaluating, assessing/addressing, and treating).

MEAT serves as the connective tissue between documentation, provider intervention, and claims coding, and is essential for any reliable risk adjustment program. VBC relies on this alignment, confirming that money is flowing to organizations that are most at risk, and ensuring that patients with chronic conditions are served efficiently. Combined with tools that simplify HCC recapture, such as artificial intelligence and machine learning, these approaches can save time across the care team and ensure care continuity and revenue capture for chronic disease management.

Stop Using Old Solutions for New Practices

Automation tools and assessments like MEAT help care teams, providers, and coders ensure that HCC coding accurately reflects the true burden of patient populations. Without the necessary systems and technology infrastructure in place, following the guidelines in practice can be challenging. Health systems that are incorporating VBC arrangements often expect to solve new problems with old solutions, and that is just simply not realistic. Organizational efficiencies leading to increased clinician satisfaction, improved financial performance, and better clinical outcomes can be realized with the right operational components to support automation, visibility, and collaboration for both provider organizations and health plans.

Readers Write: It’s Time to Hold Payers Accountable For Their Games

It’s Time to Hold Payers Accountable For Their Games
By Matt Seefeld

Matt Seefeld is EVP of MedEvolve of Little Rock, AR.

Payer, provider, and patient alignment — it’s the holy grail of healthcare’s focus on value to ensure the best care is delivered at the lowest cost. And while industry stakeholders have the best intentions to achieve this critical big-picture goal, the average healthcare organization sinking in denials management knows that we still have a long way to go.

A report issued by the Kaiser Family Foundation in 2022 reveals the continuation of year-over-year trends of high rates of claims denials. The report found that approximately 18% of in-network claims were denied on average during the reporting period, but some plans reached as high as 80%. This reality equates to increased burdens on revenue cycle teams and delayed reimbursements, two challenges today’s healthcare organizations must mitigate amid burnout, staffing challenges, and tight operational margins.

While provider organizations are wise to implement infrastructures and automation to ensure clean claims are delivered to payers on the first try, they should also consider how to improve reimbursement through the lens of payer accountability. For instance, understanding payer mix and where an organization is getting the most bang for its buck can provide a foundation for better negotiating power.

Jumpstarting a payer accountability strategy starts with visibility into key payer trends and data, or the ability to maintain a payer scorecard.

Payer Scorecard: Laying the Foundation for Payer Accountability

Improving operational margin is imperative for today’s physician practices. As shifting reimbursement models place more financial responsibility on patients, healthcare organizations must have a holistic strategy that proactively addresses the full lifecycle of billing processes to maximize use of limited and expensive internal resources.

Effectively negotiating with payers is a key part of this strategy, yet few provider organizations understand where they are getting the most ROI against work effort with their health plan partners. For example, can your executive team answer the following questions?

• How many claims touches did it take to get paid from Payer A compared to Payer B?
• What is the ratio of zero-touch rate (claims paid without humans getting involved), denials, and work effort between Payer A and Payer B?
• How does at-risk AR, collection effectiveness, and work effort stack up between payers?
• What is your denial overturn rate and associated work effort to achieve this result?
• Which health plans are having the greatest impact on gross collection rate (GCR) and net collection rate (NCR)?

When providers can identify payers that are creating the most internal revenue cycle havoc or have poor ROI when compared to work effort, they are empowered to confront issues head on. For example, it’s fair to ask why reimbursement from Payer A appears in 14 days while Payer B takes 28 days on average. Or why my organization is getting 60 cents on the dollar from one managed care contract and 70 cents on the dollar for another. In either case, maybe it’s time to stop seeing a particular carrier’s patients and opt for better contracts and partnerships.

Increasing Zero-Touch Rates Through Payer Accountability

The goal for any healthcare organization’s revenue cycle is to achieve the highest zero-touch rate possible. Not surprisingly, this measure reflects claims that are processed and paid without any human involvement. When that happens, work effort and cost to collect automatically goes down, and revenue cycle teams operate more efficiently.

A 26-location, 75-provider orthopedics and neurosurgery group set a course to improve its zero-touch rate with payer accountability as a key part of the strategy. To do this, they needed visibility into the daily work of every staff member and a way to track payer interactions. Because EMR and practice management systems do not have the analytics capabilities to produce the level of granularity and visibility to answer key questions, the organization deployed a framework of effective intelligence to identify where breakdowns were occurring along the revenue cycle that required human intervention.

They created a dashboard to measure zero touch visits against claims edits, refiles, denials, and actions required by the billing team to get paid. This strategy complemented other payer accountability use cases that compared work effort against at-risk AR as well as how each payer was impacting net collection rates (NCR). In essence, the team developed and maintained an ongoing payer scorecard.

Since implementing this dashboard, the organization has been able to improve its payer contract negotiations and refocus efforts around the greatest ROI. Early results have been promising:

• 98% NCR, above industry benchmark of 97%.
• 77% increase in production from redesigned processes.
• 62% zero-touch rate.

At a time when insurance companies are reporting billion-dollar profit margins and providers are finding it increasingly difficult to stay independent (or in business), it’s important that healthcare organizations have proactive visibility into payer insights. Payer accountability must become a strategic part of broader revenue cycle processes to maximize bottom-line impact and position for a viable future.

Readers Write: Accelerating Redetermination: Social Drivers of Health and 1115 Waivers

Accelerating Redetermination: Social Drivers of Health and 1115 Waivers
By Jaffer Traish

Jaffer Traish is COO of Findhelp of Austin, TX.

Medicaid Redetermination

Medicaid continues to be the largest healthcare funding vehicle in the United States. From February 2020 to April 2023, Medicaid and the Children’s Health Insurance Plan (CHIP) enrollees increased 33% to 94 million individuals.

The declaration of the public health emergency (PHE) by Congress in March 2020 enacted a “continuous coverage” requirement, where Medicaid agencies couldn’t disenroll anyone unless they asked, moved out of state, or passed away. Traditionally, there is a churn or loss of enrollees due to non-responsiveness to forms requests, regular eligibility reviews, income changes, and so forth. When the PHE ended on May 11, 2023, state Medicaid agencies were given 12 months to initiate renewals and 14 months to complete them. For many states, unwinding from the PHE will last well into 2024.

Redetermination processing is an enormous undertaking. States are under pressure from the Centers for Medicare and Medicaid Services (CMS) which can track call center metrics and procedural terminations (for example, if the person couldn’t be reached). CMS could even request corrective action plans and implement financial penalties in the event of missed unwinding reporting as required by the Consolidated Appropriations Act.

Being a Medicaid director is a critical yet unenviable position for PHE unwinding, and some states have requested waivers to use simplified criteria to process redeterminations. It has been estimated by Kaiser Family Foundation that a staggering eight to 24 million enrollees may lose Medicaid coverage.

Innovating with CMS Waivers

One approach available to states, and growing in popularity, is the 1115 Waiver. The Secretary of Health and Human Services (HHS) can approve a waiver for a pilot or demonstration project that federal rules would normally not allow, including changes to eligibility, benefits, and provider payments.

As of August 2023, there are 68 approved 1115 waivers across 48 states. Interestingly, 19 of these have social drivers of health provisions. There are 33 more waivers pending approval, and 12 of these also include social drivers of health provisions.

Beneficiary Stability

By investing in non-traditional case management, housing, and nutrition, states are adding stability for enrollees with specific health-related social needs and anticipate a positive impact on redetermination. New York, for example, is awaiting approval on a several billion dollar waiver proposal to invest in creating major social care network structures.

Amanda Lothrop, COO of Medicaid for New York State, shared the significant role social care networks will play in the 3.5 year demonstration waiver to a large group of NY stakeholders on September 27.

Centene, UnitedHealth Group, Elevance Health, Molina, and Aetna control about half of the Medicaid Managed Care market across 40 states. They receive requests from states for both updated enrollee contact information to better process redetermination and to meet requirements for social care provider networks and claim processing as part of their benefit administration.

Three Themes: Understanding the Evolving Medicaid Population

In discussing these challenges with managed care organizations, government, schools, hospital systems, and community organizations, we hear three consistent themes:

• States are in the dark about the non-medical risks of enrollees and how this is impacting churn and cost. In particular, MCOs need early notification about the clinical and social risks of both adults and children. Not only to work to address them, but to conduct benefit eligibility determinations and proactive engagement.
• Hospital systems need to adapt to new Medicaid-led financial incentives to assess needs and initiate interventions. States may take for granted the community engagement (trust-building), network contracting, and technology implementation that is required for successful non-medical services delivery.
• A single care coordination technology mandate does not substitute for community interoperability. Care coordination is cross-sector and collaboration goes far beyond traditional healthcare. All industries should look to United States Core Data for Interoperability (USCDI) standards and follow rules such as the Michigan Health Information Network (MiHIN) interoperability pledge.

The Future of Redetermination

To stay rooted in reality, waivers come and go, as do the officials that approve them. In the long term, states should invest in enhancing their member engagement channels to reduce procedural termination, updating their public health analytics to include social risk, and reducing paper friction in the state benefit eligibility processing.

The Kaiser Family Foundation estimates that more than 4 million people have lost Medicaid coverage so far. States do not have to make redetermination data public, so the full scope is unknown until federal numbers are published later this year.

Imagine if:

• The MCO could retrieve current member contact information and social risk through hospital electronic health record (EHR) connectivity to contact members for redetermination and support. Epic Payer Platform and SchoolCare are two examples of vendors supporting these efforts.
• The acute and post-acute care providers could order waiver-approved social services based on automatic benefit authorization. CalAIM is an example of this enhanced care management.
• The community social service provider could document services and reimbursement codes would automatically associate in the system for claims. MassHealth supports codified services in this approach.
• States aggregate anonymized social risk, supply, and demand to inform future capacity investments and waiver services to expand or retract. CRISP HIE in Washington, DC is leading efforts in aggregated social services management.

The large redetermination effort nationwide and the requests by states to fund social services for beneficiary stability are fueling a renewed look at antiquated state benefit eligibility systems and processing. One prediction – we will start seeing API-based application submissions that enable fast determination and financial disbursements for state benefits.

We will be watching (and supporting) waiver implementations closely along with private sector investments in social drivers of health to better understand public benefit needs, direct service delivery, and accelerated redetermination.

Readers Write: Navigating the Early Days of Healthcare AI Integration

Navigating the Early Days of Healthcare AI Integration
By Michael Burke

Michael Burke, MBA is founder and CEO of Copient Health of Atlanta, GA.

Have you tried using any of the AI tools that have taken the world by storm recently? This article will probably be more helpful if you have some knowledge or experience with ChatGPT, Google Bard, Anthropic Claude, or any other LLM/chat model tool.

If you haven’t already, try asking one of these tools a specific question or give it an assignment to produce a specific document and see where it leads. You may be surprised at just how useful the results can be.

If you’ve used these tools to answer questions or generate content (e.g., a legal document, a policy document, an email, or an article like this one), you have some sense of their potential. Imagine what could be done with a tool that leveraged an LLM like ChatGPT on your hospital’s data. The software vendors you use are all either investigating or actively releasing tools powered by LLMs to leverage your data. At Copient Health, we are, too.

It’s my belief that these tools will fundamentally change the way you interact with those vendor systems and ultimately, in both the way that you do your work and the results that you get.

A comprehensive list of all use cases is impossible because we’re so early in the process, but here are a few obvious low-hanging fruit uses that are relevant for software vendors:

• LLMs are already powering chart notes that are built in real time from patient conversations.
• Dashboards and reports will become unnecessary, because you will always have the specific data or chart that you need just a query away. The LLM can even proactively push the appropriate information in the appropriate format for the appropriate context.
• You can forget about manuals, indexed help systems, or frustrating first-generation chat bots that perform poorly. LLM-powered solutions are better at finding what you’re looking for using a similarity search of a vector database.
• You might even abandon memorizing complex commands or menu hierarchies and ask the LLM to accomplish the task instead.

But ChatGPT and other public-facing LLMS were trained on public data. How can they be leveraged for use cases that require knowledge of private data?

The answer to that question used to take a lot of time, money, and a team of data scientists to train your own LLM, or at least fine tune an existing open source model. That has changed dramatically, mostly in the last 6-8 months, based primarily on a term that you may have heard: “prompt engineering,” and one that you probably haven’t: “in-context learning.” Here’s a quick summary:

LLM models are text-in, text-out black boxes. But the text-in doesn’t have to be limited to a simple question. It can include prompts of background information, examples of questions and answers to similar scenarios, chunks of data, or simply directing the LLM to “think step-by-step.”

These are all basic forms of prompt engineering. The LLM temporarily “learns” from this prompt data, at least enough for your current conversation. LLMs can be used as an inwardly-directed service to decide what data or tool to use based on the prompts that it receives. This design pattern has demonstrated better results than the more cumbersome fine-tuning approach for the smaller data sets that we’re talking about.

An entire ecosystem of software tools has emerged to support the use of these pre-trained LLMs on private data. These tools convert the challenge from what was once an arcane AI data science problem to a data engineering problem, primarily built around prompt engineering and in-context learning.

Here’s an illustration of how quickly these tools have evolved and been adopted. One of the most widely used tools in the ecosystem, LangChain, was first introduced in October last year as an open source project from two college students. In a few months, its use expanded globally. The founders incorporated and raised $20 million in venture funding from Sequoia Capital. Since last October, they have garnered 60,000 GitHub stars, which is a measure of its popularity among software developers. For context, Python, the language the LangChain toolset is written in, has fewer stars over a significantly longer time period: 51,500 stars over six years. ChatGPT itself captured one million users in just five days.

This head-spinning rate of change gives an advantage to startups, given their rapid iteration and integration of new tools and ideas. Some large healthcare software vendors that are infamous for relying almost exclusively on internally developed tools find themselves in a challenging situation. It’s impractical for them to build their own LLMs, as they would likely never rival the performance of commercially available options, and it would take forever. And since they are not used to relying on third-party software as part of their solution, they aren’t prepared for the rate of change at which these solutions are evolving.

For instance, just yesterday, LangChain had 18 separate commits (i.e., changes) to their codebase. That’s fast! Adapting to rapid changes and advancements requires a new level of agility.

We’ve recently heard announcements and partnerships from big tech and big healthcare IT. It will be interesting to see if these announcements produce real value in the near term, or if they are just a way to buy time for the vendor to figure out this rapidly evolving space.

Readers Write: It’s Time for a National Patient Identifier

It’s Time for a National Patient Identifier
By Gregg Church

Gregg Church is president of 4medica of Marina del Rey, CA.

Congress has the power to make healthcare safer and less expensive for patients, payers, and providers. It can do this by removing the ban that prohibits using federal funds for the development of a unique national patient identifier.

The patient identifier system would give each patient a single ID that would follow them through their healthcare journey, regardless of provider or payer, while still protecting their private information. It would reduce medical and billing errors and denied claims, while eliminating countless hours insurers and hospital systems spend resolving patient matching errors. It would also aid medical research and make it easier for our healthcare system to respond effectively during national emergencies, like the COVID-19 pandemic.

The federal ban on a national patient identifier was born from good intentions. Former US Rep. Ron Paul in 1998 added the provision to the Labor-HHS appropriations bill. The physician and libertarian cited concerns about patient privacy and the dangers of the federal government collecting and centralizing medical records. His son, Sen. Ron Paul, also a physician and libertarian, now leads the opposition with the help of the ACLU and other groups.

Congress has come close to ending the ban. For the past four fiscal years, the House has removed it from its version of the appropriations bill; the Senate did likewise the past two years. Each year, however, it has been reinstated in the final budget.

In 2021, Patient ID Now, a coalition of more than 40 healthcare organizations, including the American College of Surgeons, American Heart Association, American College of Cardiology, The Joint Commission, and American Health Information Management Association, was formed to push for a nationwide strategy to address patient identification.

The group noted that the ban was put in place 25 years ago at a time when patient records were still largely kept in manila folders. It’s now a hindrance to the necessary digitization of healthcare. While concerns over patient privacy are real, a national patient identifier could be implemented in such a way that it protects patients.

I like to believe that much of the opposition to a universal patient identifier is due to a lack of awareness of the volume of incomplete, duplicate, missing, and overlaid medical records and the problems they cause.

Imagine if your personal finance records had a roughly one in five chance of being duplicated or mixed up with someone else’s accounts by financial institutions. Think of the chaos and damage and the ensuing demands to fix the problem.

Duplication of patient records is one of the most serious problems with healthcare data quality, and it’s more common than many think. Duplication rates are as high as 30% in some healthcare organizations, and a 10% rate is common. Up to half of patient records are not matched in transfers between healthcare systems. 

Patients are endangered by low-quality records, particularly duplicate and overlaid records, in which the data for two patients is mixed.

Approximately 70% of care decisions are based on lab tests, which are performed by techs working in relative isolation from the care team. Labs frequently create duplicate records while entering patient information into computers. That bad data can then be multiplied and disseminated throughout a hospital system and between systems.

Clinicians working from bad data can misdiagnose, prescribe the wrong course of treatment, and order duplicate tests, which delay necessary treatment.

Black Book in 2018 surveyed health technology managers about problems with patient identification processes. It found that the cost of medical care due to duplicate records averaged $1,950 per patient per inpatient stay and more than $800 per ED visit.

Those surveyed also estimated that 33% of denied claims were due to inaccurate patient identification or information. That cost the average hospital $1.5 million in 2017 and the US healthcare system more than $6 billion annually.

That unnecessary expense could be eliminated with a standard patient identification system.

True interoperability among patients, providers, and payers is a goal of the healthcare industry, one that could be made more achievable through a patient identifier system that allows for the disruption-free exchange of patient records.

While recent improvements in patient identification processes, such as hospitals adopting Enterprise Master Patient Indexes and the use of machine learning, have improved record matching, it’s barely keeping pace with the explosion in medical records and the sharing of data among different healthcare organizations.

Adopting a national patient identifier would be a significant step toward building a safer, and more effective and affordable healthcare system. It’s time for Congress to listen to the experts and remove the ban. We’ll all be better off for it.