Readers Write: Unlocking Hidden Gems: Leveraging RCMTAM for Revenue Cycle Excellence

Unlocking Hidden Gems: Leveraging RCMTAM for Revenue Cycle Excellence
By Kim Waters

Kim Waters, MBA is principal consultant, advisory services with CereCore.

Revenue cycle management (RCM) has become more challenging than ever. With increasing denials, evolving payer policies, and growing patient financial responsibility, healthcare organizations need innovative solutions to optimize their revenue cycles. Enter the Revenue Cycle Management Technology Adoption Model (RCMTAM), a game-changing framework that’s revolutionizing how we approach RCM technology.

As a leader in healthcare IT solutions, I’ve seen first hand how RCMTAM can transform revenue cycle operations. Let’s dive into the hidden gems this model offers and explore how it can drive operational efficiency, improve financial outcomes, and uncover cost-saving opportunities.

The RCMTAM Advantage: A Data-Driven Approach to RCM Excellence

RCMTAM is more than just another acronym in the healthcare alphabet soup. It’s a peer-reviewed, five-stage framework endorsed by Healthcare Financial Management Association (HFMA) that assesses operational performance and the maturity of revenue cycle technology within healthcare organizations. What sets RCMTAM apart is its data-driven approach, linking technology adoption with financial outcomes to create customizable roadmaps for RCM optimization.

Key features of RCMTAM include:

• A five-stage model for assessing RCM technology maturity.
• Financial benchmarks for performance comparison.
• Correlation of RCM technology adoption to financial performance.
• Personalized organizational roadmaps.

Uncovering Hidden Gems: RCMTAM in Action

Let’s explore some specific examples of how RCMTAM can enhance operational efficiency and improve financial outcomes:

• Streamlining eligibility checks. Experian’s recent state of claims survey revealed that 43% of respondents spend 10 to 20+ minutes on secondary eligibility checks. By leveraging RCMTAM to assess and optimize eligibility verification technology, organizations can significantly reduce this time, improving staff productivity and accelerating the revenue cycle.
• Tackling denials head-on. With 38% of respondents reporting claim denial rates of 10% or higher, denials management is a critical area for improvement. RCMTAM can help organizations identify and implement advanced denial prevention and management technologies, potentially saving millions in denied claims.
• Automating manual processes. Nearly 50% of providers still review denials manually. RCMTAM can guide the adoption of AI and automation technologies in the denial management process, freeing up staff for more complex tasks and reducing errors.
• Enhancing data accuracy. Bad data is a leading cause of denials, with 46% of respondents citing missing or inaccurate data as a top reason. RCMTAM can help organizations assess and improve their data management technologies, reducing errors and improving clean claim rates.

The Path Forward: Embracing RCMTAM for Continuous Improvement

As the 2024 State of Claims survey shows, the healthcare landscape is constantly evolving. Payer policy changes are occurring with more frequency (77% agree), and 66% of respondents find submitting “clean” claims more challenging now than before the pandemic. In this dynamic environment, RCMTAM provides a structured approach to continuous improvement.

By regularly reassessing your organization’s position on the RCMTAM scale, you can:

• Identify emerging technologies that address your specific pain points.
• Benchmark your performance against industry leaders.
• Create data-driven strategies for ongoing RCM optimization,

Navigating the complexities of revenue cycle management can be tough. An RCMTAM assessment can provide the performance readout that your organization may need to help uncover the hidden gems in your revenue cycle so you can drive meaningful improvements in your financial performance.

As you embark on your RCMTAM journey, remember that technology is just one piece of the puzzle. Success lies in the seamless integration of people, processes, and technology. By taking a holistic approach and leveraging the insights provided by RCMTAM, you can transform your revenue cycle from a source of frustration to a driver of organizational success.

Readers Write: ViVE 2025 Recap

ViVE 2025 Nashville – The Tale of AI and the Snowpocalypse!
By Mike Silverstein

Mike Silverstein is managing partner of healthcare IT and life sciences at Direct Recruiters, Inc.

Tell me about your agents! No, not one from the CIA, FBI, or your record label. Tell me about your AI agents!

That was the theme of ViVE 2025 in Nashville. Music City was frigid outside, but inside the Nashville Convention Center, the agentic AI blaze was on. 

Two weeks ago, I gave up and finally asked a client on a Zoom call, ”Can you tell me what the heck agentic AI is?” My head is still spinning from large language models (LLMs), GPTs, and generative AI (still not entirely sure what this is). Now if you don’t have AI agents, you are an HIT artifact.

Big tech is coming to healthcare and this time I think it is REALLY here to stay. With the labor crunch and margin pressures being ubiquitous and in full force, an AI agent that can make a phone call to a patient / member / health plan and converse like a real person with whatever tone and accent you prefer might just be a game changer.

The tools are really getting smart, borderline scary smart. I had several people demo products for me that I literally couldn’t tell with certainty if I was listening to a real person or an AI agent. Even more, these agents are being trained on serious healthcare data and workflows, and I believe the dominoes are going to start falling.

At HLTH 2024 in Las Vegas, AI co-pilots were all the rage. Now those firms are racing to stay up the value stream and provide even higher value clinical impact as AI note-taking feels like it will be table stakes very soon. Call centers and one-way SMS texts both seem like they could be on the chopping block, and it feels like we could be on the precipice of patients actually having a real consumer experience like in every other industry.

On the investment front, deal activity seems to be up. The firms I talked to are living less hand to mouth (as opposed to only focused on sales in the next six months) and are back investing in products and technology out of fear of being left in the dust. However, what stood out as interesting to me is that access to this cutting-edge technology seems to be far wider than various technological breakthroughs of the past.

Most of the vendors I talked to are layering their healthcare workflows on top of off-the shelf AI agent tools and platforms, so the speed-to-market has been pretty blinding. New healthcare tools are being developed using publicly available foundational tech and low code development. ViVE 2025 felt a bit like healthcare’s version of a big-time arms race. Everyone is working diligently to stay out in front of, or totally away from, Epic’s roadmap. It feels like this could be the start of a major leap in how we experience healthcare as consumers.

Unfortunately, the other major thing I learned this week is that Nashville is woefully unprepared for snowstorms. At the end of every conversation I had in the past 48 hours, everyone told me, “You had better move up your flight. It’s going to snow on Wednesday and this whole place is going to shut down.” As a result, there was a mass exodus from Nashville Tuesday evening, and the airlines cashed in big on change fees.

Even so, Music City was a great host, and 2025 feels like it’s going to be a pivotal year in the adoption of AI in healthcare.

Readers Write: Solving Healthcare’s $125 Billion Fax Problem

Solving Healthcare’s $125 Billion Fax Problem
By Thomas Thatapudi

Thomas Thatapudi, MBA is CIO of AGS Health.

In the six years since Centers for Medicare and Medicaid Services called for an end to faxing in healthcare, the industry remains stubbornly attached to fax communications. Fax-led communications solutions are prevalent today, as organizations continue exchanging more than 9 billion fax pages each year, representing about $125 billion in annual costs to the healthcare system.

It is a problematic practice in terms of data integrity, productivity, and efficiency. According to information compiled by DirectTrust, 30% of tests must be re-ordered due to lost faxes and 25% of faxes fail to arrive before a patient’s first visit. Faxes also often require manual indexing for integration into the EHR and other health information systems, a time-consuming process that requires human and financial resources that are hard to come by for many healthcare organizations.

Luckily, fax indexing lends itself to automation. In particular, generative AI (GenAI) and agentic AI excel at automating mundane and repetitive tasks. However, it is unrealistic to expect digital workers, such as AI agents that mimic human actions, to accurately index 100% of the faxes from the outset. Thus the best outcomes are realized when digital workers are paired with human counterparts who manage exceptions and handle specialized information and requests, at least until the digital workers have accrued enough on-the-job training via machine learning and deep learning models to take over higher complexity tasks.

Implementing a hybrid fax indexing model accelerates processing and eliminates the care delays that are caused by improperly managed faxes. It also alleviates the strain on increasingly scarce resources, reducing costs and freeing internal staff to focus on higher-value tasks.

However, achieving these outcomes requires careful orchestration of a workflow that seamlessly integrates digital workers (AI agents) and their human counterparts delivering on quality, timeliness, and accuracy.

Designing the Digital Workforce

The heart of a successful hybrid fax indexing strategy is a well-designed digital workflow model that helps orchestrate workflows between humans and digital workers. It starts with mapping the necessary technologies, a step that is best informed by shadowing human indexers to fully understand the process and map any unique needs. This information is also used to plan the implementation and conduct feasibility testing.

Like their human counterparts, digital workers are armed with an array of intelligence and automation tools, including optical character recognition (OCR), to analyze faxed documents and convert them into machine-readable text. They use natural language processing (NLP) models to interpret and manipulate the data contained within. GenAI is then leveraged to classify faxes based on the sender’s documentation format, determine its confidence threshold, and either index it into a documentation management system or EHR or divert it to the validation workflow for manual processing.

Machine learning allows digital workers to adapt to new document formats and categorize data according to providers’ templates and styles. Further, each processed fax enhances accuracy, efficiency, and capabilities while reducing exceptions.

Monitoring effectiveness is crucial to success. Establish clear KPIs, such as the volume of faxes indexed per day, indexing accuracy, turnaround times, and productivity levels to assess progress over time.

AI Grounded in Reality

While automated fax indexing is a relatively new entry into the burgeoning field of healthcare AI, it is quickly making an impact. One health system’s implementation of automated fax indexing has put it on track to save approximately $2 million in annual expenses. Automation has reduced the number of manual indexers that are required to process the health system’s fax volume, which allows key team members to focus on higher-value tasks while achieving a near-perfect accuracy rate and 24-hour turnaround time. As digital workers “learn” over time, the automation rate will increase, while the need for human intervention decreases, adding to the anticipated cost savings.

While it is unlikely that we will see a fax-free healthcare system in the near-term future, leveraging readily available automation and AI tools makes it possible to digitize the process and alleviate its associated cost, productivity, and patient safety burdens.

Automated fax indexing is yet another example of a thoughtful AI application that solves an age-old problem that, until now, has been stubbornly resistant to change.

Readers Write: Are Your Patient Access Metrics Ready for Healthcare Consolidation?

Are Your Patient Access Metrics Ready for Healthcare Consolidation?
By Emily Tyson

Emily Tyson, MBA is COO of Relatient.

The healthcare industry witnessed a surge in merger and acquisition (M&A) activity in 2024, a trend that is expected to gain momentum in 2025. While organizational growth can unlock new potential for patient care and financial performance, it often brings operational inefficiencies that, if left unchecked, can strain staff, frustrate patients, and hinder sustainable success.

One of the biggest hurdles is managing the influx of data from fragmented sources. Adding new providers and locations introduces complexity, making it difficult to maintain consistency in scheduling, patient flow, and care delivery. Without the right tools to consolidate and standardize this data, organizations risk creating bottlenecks that impact the patient experience, disrupt operations, and negatively affect financial outcomes.

To ensure sustainable growth, healthcare organizations need proactive, data-driven strategies that are focused on four key aspects of patient access — provider scheduling performance, call center efficiency, patient experience, and financial outcomes — to not only identify inefficiencies, but also address them before they escalate.

Provider scheduling performance

During periods of growth, whether through acquisition or organic expansion, the last thing healthcare organizations need are scheduling disruptions. Scheduling is a cornerstone of operational success, directly impacting patient acquisition, physician satisfaction, and financial performance.

Accurate data insight is key to identifying gaps and uncovering opportunities for improvement. For example, high patient no-show rates might signal ineffective communication about appointment details, leading to missed visits. Another critical metric is appointment wait time, as patients overwhelmingly identified this as a top frustration in a 2024 survey.

Other essential metrics such as provider utilization rates, rule optimization, and scheduling accuracy reveal how effectively an organization accommodates provider preferences while balancing patient demand. Monitoring these indicators helps prevent overbooking, supports efficient patient throughput, and ensures that providers’ schedules are sustainable.

Metrics like the third next available appointment and waitlist conversion further illuminate the balance between patient access and appointment availability. These insights empower organizations to fill open slots more efficiently, expanding patient access while maximizing financial performance.

Contact center efficiency

During periods of growth and M&A activity, ensuring a seamless transition at the first touchpoint of the patient journey, the contact center, is critical. As new organizations integrate, call volumes naturally increase and require careful management to maintain care quality and consistency.

Proactively measuring and analyzing key performance indicators (KPIs) for both efficiency and patient satisfaction allows healthcare organizations to identify potential gaps. For instance, tracking peak call times allows administrators to allocate resources strategically, ensuring that patients receive timely support during high demand periods. The right metrics provide insights to reduce bottlenecks, streamline scheduling, and lower operational costs. Other KPIs like appointment booking efficiency, minutes per call, and staff training time offer a comprehensive view of contact center performance and areas for improvement.

Patient experience

Today’s healthcare consumers demand convenience, and if scheduling processes are complicated or time-consuming, particularly during periods of growth or consolidation, patients are likely to seek care elsewhere. To meet these expectations and enhance both patient experience and contact center efficiency, organizations must monitor patient experience metrics that reflect engagement and satisfaction.

Given that research consistently shows that patients prefer self-scheduling options, empowering patients to take more control of the scheduling process can lead to better outcomes for both patients and staff.

With the right systems in place, providers can track self-scheduling rates and after-hours scheduling activity to gain deeper insights into patient behavior. Other essential patient experience metrics include patient acquisition, referral conversation rates, and appointment abandonment rates, all of which provide a clearer picture of how well the organization is meeting patient needs.

Financial outcomes

Effective scheduling and data management play a vital role in driving financial performance. During periods of rapid growth, healthcare organizations should closely monitor key financial metrics that are tied to scheduling and payment processes. Doing so enables them to identify opportunities to streamline operations, reduce costs, and maximize revenue.

Crucial metrics that provide insight into a practice’s financial health include payment collection percentages, reductions in accounts receivable, balances collected through payment plans, and the speed of patient balance collection. By tracking these indicators, organizations can pinpoint inefficiencies, implement targeted improvements, and ensure financial stability during times of expansion.

Setting the state for growth

Tracking the right metrics enables teams to address inefficiencies and achieve sustainable growth by focusing on four critical areas:

• Optimizing scheduling workflows. Track scheduling KPIs like no-show rates, wait times, and provider utilization to balance patient demand and provider efficiency.
• Boost contact center performance. Analyze KPIs such as peak call times, appointment booking efficiency, and staff training to improve operations and care quality.
• Enhance patient engagement. Offer self-scheduling options, track patient satisfaction metrics, and resolve issues like appointment abandonment to align with consumer expectations.
• Improve financial health. Focus on payment collection rates, accounts receivable reductions, and patient payment speed to drive revenue stability.

Intelligent patient access tools such as multi-channel appointment scheduling, provider preference management, and automated appointment reminders allow organizations to accurately track the most relevant KPIs, enhancing operations and improving the patient experience. Combined with robust analytics, these tools enable data-driven strategies, optimize performance, and support sustainable growth.

Readers Write: HIPAA Security Rule Update: Why Should Every Practice and Hospital Have to Build Their Own Defenses?

HIPAA Security Rule Update: Why Should Every Practice and Hospital Have to Build Their Own Defenses?
By Joseph Schneider, MD, MBA

Joseph Schneider, MD, MBA is with the University of Texas Southwestern.

I read Jason Ward’s excellent Readers Write and agree that it’s important to have clear best practices for security and that the Security Rule needs an update. However, I strongly disagree that a “one size fits all” approach like the proposed HIPAA Security Rule update is the right approach. The impact on smaller physician practices is tremendous and is not commensurate with the “probability and criticality of potential risks to ePHI” as required by the wording of the original HIPAA legislation.

Here are some comments on the proposed rule that are being sent to HHS:

• HHS states (on page 1004 of the Federal Register) “if the proposed changes in the NPRM reduce the number of affected individuals by 7 to 16 percent, the rule would pay for itself. Alternatively, the same cost savings may be achieved by lowering the cost per affected individual’s ePHI by 7 percent ($35) and 16 percent ($82), respectively.” Logically, the changes should reduce breaches or reduce costs, but there’s no evidence cited (that I could find) that supports this level of improvement. How much will this impact things? We don’t know, and it’s going to cost a huge amount to find out. First-year costs are ~$9 billion, with years 2-5 costing $6 billion annually. The present value of the costs, if I’m reading it correctly, is $32 billion, which coincidentally was just a little less than the original estimated cost of the Meaningful Use program. 
• On page 1007, HHS estimates that “the cost for a one-establishment [location] firm is $1,235 …” That’s absolute nonsense. The cost of doing all these things could be WAY more than $1,235 per practice. The averaging methodology used to come up with this number is flawed. A detailed cost analysis by requirement should be done and published for review. 
• HHS goes on to say, “In the context of the RFA, HHS generally considers an economic impact exceeding 3 percent of annual revenue to be significant…” Three percent of revenue spent on this activity alone is enough to put some small practices and possibly some rural hospitals out of business. No practice has 3% of revenues just sitting around. 
• Finally, HHS says that “In the context of the RFA, HHS generally considers an economic impact exceeding … 5 percent or more of the affected small entities within an identified industry to represent a substantial number.” This is ridiculous and arbitrary. In essence, HHS is saying that it’s OK for up to 4.99% of small practices to be bankrupted or badly damaged. Additionally, it’s easy to say that practices can go out of business, and it’s not significant, but it ignores the impact on the community when the only practice in town or for miles may close. 

Two additional global thoughts:

This is a gross over-expansion of the original HIPAA legislation wording. As noted on the HHS website: “The Security Rule does not dictate the specific security measures that a regulated entity must use. Instead, it requires the regulated entity to consider the following factors when selecting security measures that meet the Security Rule’s requirements: 1) its size, complexity, and capabilities; 2) its technical infrastructure, hardware, and software security capabilities; 3) the costs of security measures; 4) the probability and criticality of potential risks to ePHI.” By defining specific measures that MUST be taken, HHS is going far beyond what the law says. If the proposed changes are put into place, I expect that they will be challenged based on the Lopez Bright Enterprise v. Raimondo decision that overturned the Chevron doctrine.

Most importantly, the approach that we’re taking regarding security protection requires each organization to do everything. That stems from our culture of individualism. A better alternative would be if we had national approaches to at least some elements of this national problem. 

Here are two examples. Instead of every hospital and practice having to develop its own training, why not have a single national training and re-education program that clinicians and staff need to complete just once? And instead of having every small practice / rural hospital bear the costs of developing their own security plans and pay for audits, why not have the equivalent of the Agricultural Extension Offices provide these? It would cost less than having everyone do everything. Security is a national priority and we need to start thinking about national solutions, just as we do with national defense.  

I’m not suggesting that we keep the status quo of security, but we have to have different thinking about how to approach this so that we don’t damage or destroy small practices and rural hospitals. And while I don’t agree with a lot that’s going on in Washington right now, if this proposed rule died in the transition, I wouldn’t be crying too hard.

Readers Write: HIPAA Security Rule Update: Why Basic Compliance Isn’t Enough

HIPAA Security Rule Update: Why Basic Compliance Isn’t Enough
By Jason Ward

Jason Ward is VP of IT and tech support at Collette Health.

The healthcare sector has become an increasingly attractive target for cybercriminals, with attacks growing in both frequency and sophistication. The scale of healthcare data breaches nearly tripled in 2023, with 140 million individuals affected compared to 51 million in 2022, highlighting the rapidly growing threat to patient privacy. 

In response to these escalating threats, the US Department of Health and Human Services (HHS) has proposed the first major update to the HIPAA Security Rule since 2013. This update reflects a growing recognition that current security measures are insufficient to protect modern healthcare systems. 

While these proposed changes represent a significant step forward, they should be viewed as minimum requirements rather than comprehensive security solutions. In today’s healthcare environment, where increasingly interconnected systems create multiple attack vectors and expand the potential attack surface, organizations need to think beyond basic compliance.

The current security landscape demands a more proactive and robust approach. Many of the proposed requirements — such as annual audits, basic encryption, and standard access controls — are practices that security-conscious organizations have already implemented, and in many cases, exceeded. As we examine these updates, it’s crucial to understand that they represent a foundation upon which to build more comprehensive security measures.

Key Changes and Why They Matter

• Mandatory security documentation and regular auditing. Previously optional security measures will now become mandatory, with few exceptions. Organizations must document all security policies and procedures. Annual compliance audits will be required to verify adherence to these requirements.
• Enhanced asset management and network visibility. Organizations must maintain and regularly update a technology asset inventory and network map. These must be reviewed at least annually and updated whenever there are changes that might affect protected health information.
• Strengthened access controls and authentication. Multi-factor authentication becomes mandatory for accessing systems containing protected health information. Organizations must notify relevant parties within 24 hours when workforce access changes or is terminated.
• Robust incident response and recovery. Organizations must establish documented incident response plans and procedures. Systems and data must be restorable within 72 hours, with clear procedures for reporting and responding to security incidents.
• Comprehensive technical controls. Organizations must implement encryption for data at rest and in transit, deploy anti-malware protection, establish network segmentation, and conduct vulnerability scanning every six months. Penetration testing must be performed annually.
• Enhanced business associate accountability. Business associates must verify their compliance annually through a written analysis by a subject matter expert. They must notify covered entities within 24 hours of activating contingency plans.

Beyond Compliance: Adopting a Shared Security Model

While these updates represent significant progress, healthcare organizations must recognize that meeting compliance requirements alone doesn’t ensure adequate security. True cybersecurity in healthcare requires a shared security model where:

• Everyone plays a role. Security isn’t just an IT problem. It requires active participation from every department and role within the organization. From clinical staff to administrative personnel, everyone must understand their part in protecting patient data.
• Continuous evolution. Cyber threats evolve faster than regulations. Organizations must stay ahead by continuously updating their security measures and adapting to new threats, rather than waiting for regulatory requirements to catch up.
• Cultural transformation. Building a security-first culture means making security considerations part of every decision and process. This includes fostering open communication about security concerns, celebrating security-conscious behaviors, and ensuring that security is viewed as an enabler rather than a barrier to healthcare delivery.

We’re only as secure as our weakest link. By working together and viewing these new requirements as a starting point rather than an end goal, we can build a stronger, more resilient healthcare security ecosystem that truly protects patient data and maintains trust in our healthcare system.

Readers Write: Improving the Healthcare System with Advancements in Data Science and AI

Improving the Healthcare System with Advancements in Data Science and AI
By Hugh Cassidy

Hugh Cassidy, PhD, MBA is head of artificial intelligence and chief data scientist at LeanTaaS.

Healthcare has historically been slow to adopt modern technologies, but recent advances in AI have propelled it into the mainstream, allowing AI to be confidently used in critical systems like healthcare. These advancements, in both computational power and sophisticated algorithms, have made AI not only more popular, but also more reliable for complex, high-stakes environments.

According to a recent survey from the Berkeley Research Group, 75% of healthcare professionals anticipate that AI technologies will be widespread throughout the industry within the next three years. This optimistic outlook highlights the potential of AI to transform healthcare operations and to keep pushing forward with advancements in data-informed technology and predictive healthcare solutions.

However, healthcare’s history of slow technology adoption emphasizes the need for a strategic approach. Without a clear implementation plan, organizations may fail to harness the full potential of AI to improve operational efficiency and outcomes and to meet broader organizational goals.

To fully appreciate AI’s transformative potential, it’s essential to delve into its specific applications across various healthcare challenges.

One of the most pressing issues in healthcare is excessive patient wait times. Many of us have experienced long hospital delays, and the ongoing staffing crisis coupled with rising patient volumes has only made the situation worse. AI can play a pivotal role in streamlining patient flow, helping ensure timely care while reducing operational inefficiencies.

Predictive analytics can sift through historical data to forecast patient inflow, going beyond current conditions to anticipate future trends. However, predictive insights alone aren’t enough. Prescriptive systems are essential to translate those forecasts into actionable schedules. By combining AI-driven predictions with prescriptive analytics, healthcare facilities can generate optimized schedules that not only forecast patient demand, but also suggest the best staffing and resource allocation to handle peak hours. These prescriptive systems are necessary to minimize bottlenecks, reduce wait times, and ultimately enhance the overall patient experience.

Another pain point that healthcare professionals face daily is an overwhelming number of administrative tasks, which inundates staff members and ultimately detracts from patient care. Staff members often work overtime to give patients the best care, yet still have mountains of paperwork to complete once their assigned shift is complete.

AI can make a major impact and alleviate this burden through automating routine tasks such as data entry and billing. Optical character recognition (OCR) and natural language processing (NLP) tools can read and organize clinical notes, reducing the time that doctors and nurses spend on paperwork. AI-powered conversational assistants can handle common patient inquiries and triage less-critical cases, freeing medical staff to focus on more complex and urgent patient needs. By using AI to their advantage, healthcare teams can streamline processes like appointment scheduling and build schedules that are tailored to each facility’s unique demand and capacity.

By streamlining administrative tasks and automating certain aspects of patient care, AI can contribute to increased efficiency in the healthcare system, leading to cost savings and better resource allocation. Tools such as automated billing systems reduce errors and streamline the billing process, reducing administrative overhead. Scheduling tools fill unused time and unlock the full potential of the OR and infusion centers. All of this helps create more revenue and lower costs for health systems and patients alike.

One of the best ways health systems can reduce costs is by accurately allocating their resources and serving their communities by providing consistent and timely access to care for every patient who is in need. This not only improves patient outcomes, but also drives higher revenue and keeps costs low.

The potential of AI and data science to revolutionize healthcare is immense, but it requires a thoughtful and strategic approach to implementation. Health systems should work towards overall workforce adaptation and train and prepare hospital staff to effectively work with AI tools. This will likely require changes to existing education and training programs, as well as require ongoing support to ensure the integration of AI-driven tools into everyday workflows, but it will also help shorten patient wait times, ensure that patients are getting better care, and guarantee that healthcare workers aren’t overworked.

Considering AI’s immense popularity these days, hospitals should capitalize on staff members’ excitement about new tools. The future of healthcare lies in the intelligent use of data and AI, and these technologies are already helping many healthcare systems overcome current limitations and deliver superior care. Along with better patient care, hospitals are also maximizing revenue and improving overall hospital operations, leading to happier staff and hospitals that are more capable at handling growing patient volumes.

Readers Write: Social Care Data: The Key to Unlocking Community Health

Social Care Data: The Key to Unlocking Community Health
By Carla Nelson

Carla Nelson, MBA is senior director of healthcare policy at Findhelp.

Rising healthcare costs in the US demand innovative solutions, and social care data is emerging as a critical tool for driving informed decisions and improving community health. Policies that are promoting high-value care and funding for social services like transportation and medically-tailored meals show promise but face significant hurdles, including a lack of standardized data. Without a clear picture of community needs and resources, decision-makers struggle to optimize investments and implement effective strategies.

Social care data – such as health-related social needs (HRSNs), referrals, services received, and program availability — fills critical gaps in understanding community health. Technology can play a pivotal role in collecting, analyzing, and sharing this data, enabling its integration with datasets like healthcare claims, Medicaid member files, and public data sources such as Census data or CDC indices. These combined datasets provide actionable insights, empowering organizations to identify unmet needs, allocate resources efficiently, and improve service delivery. By integrating social care data with healthcare and other datasets, technology can enable more effective policies, investments, and service delivery strategies.

Analyzing patterns in social care searches or service usage can uncover gaps in available programs. For example, if a region shows high demand for food assistance but limited service availability, this insight can guide resource allocation and program expansion. Similarly, aggregated data on social care needs can help measure the capacity of community organizations and inform targeted investments.

As social care systems become increasingly digitized, ensuring the privacy of sensitive data is essential. Unlike healthcare data, which is protected by HIPAA, social care data lacks comparable safeguards. Organizations and governments must prioritize stringent privacy measures, ensure consent-driven data collection, and adopt policies to protect individuals’ sensitive information as they seek assistance.

To harness the potential of social care data, readers can take these key steps:

1. Invest in Data Infrastructure

• Advocate for and allocate funding to modernize data collection and sharing systems.
• Support community organizations in adopting technology that enables real-time data sharing and analytics.

2. Promote Cross-Sector Collaboration

• Build partnerships between healthcare providers, community organizations, and government agencies to share data and insights.
• Facilitate the integration of social care data with other datasets to create a comprehensive view of community needs.

3. Advance Data Standardization

• Participate in initiatives to develop and adopt standardized formats for social care data to enable consistent use and sharing.

4. Prioritize Privacy and Consent

• Implement robust privacy policies and ensure individuals provide informed consent for the use of their data.
• Stay informed about evolving regulations to protect sensitive information.

5. Leverage Data for Decision-Making

• Use data to identify gaps in resources, track outcomes, and guide investments in social care programs.
• Share insights with policymakers to advocate for targeted interventions and funding.

6. Educate Your Community

• Raise awareness of the importance of social care data among stakeholders, emphasizing its role in improving community health.
• Provide training on how to use data tools and analytics for effective decision-making.

Advancing the infrastructure for social care data is essential to make informed policy and investment decisions. Challenges remain, including limited technological capacity for many community organizations and early-stage standardization of social care data. However, progress is underway. States and organizations are leveraging new technologies to integrate health and social care, building seamless referral systems, and creating platforms for effective data sharing.

As social care data capabilities mature, they will unlock new opportunities to understand and address community needs, leading to more effective policies, smarter resource allocation, and improved health outcomes. Investments in data systems and technology today are paving the way for a healthier, more equitable future for all.

Readers Write: AI Meets the Front Lines: The Contact Center of the Future

AI Meets the Front Lines: The Contact Center of the Future
By Bill Smith

Bill Smith is director of Epic practice at Cordea Consulting.

Hospitals are always striving to deliver a better patient experience. Unfortunately for many health systems, the front line of patient interactions, the contact center, is often the weakest link in the chain. Burned-out agents, lengthy hold times, and frustrated patients are the norm.

What if AI and the cloud could turn the tide? What if health systems could reduce call volumes, capture valuable patient insights, and drive down operational costs by using AI-powered contact centers?

Practical, cloud-based AI tools are ready to make life easier for agents, patients, and healthcare execs alike. This is the low-hanging fruit of AI in healthcare, delivering results today while paving the way for tomorrow’s tech innovations. As it turns out, AI-powered contact centers are the low-risk, high-reward solution health systems need right now.

Every day, hospitals handle countless calls: appointment scheduling, prescription refills, billing questions, you name it. Patients expect quick, accurate, empathetic responses, but most contact center agents are working with outdated tools, incomplete patient data, and scattered knowledge bases.

Throw in staffing shortages and fluctuating call volumes and it’s no wonder long wait times and unresolved issues are the norm. Today’s patients also expect to connect through multiple channels — phone, chat, email — but many hospitals just don’t have the infrastructure to keep up. And those legacy systems? They’re buckling under the weight of modern demands.

Now for the good news.  AI and cloud-based contact centers can tackle these problems head-on with minimal disruption and cost. These technologies aren’t pie-in-the-sky aspirations. They are operational game-changers that are already delivering these kinds of quick wins:

• Automating the everyday. AI-powered chatbots and voice assistants can handle routine tasks like appointment scheduling and FAQs, freeing up human agents for more complex cases. Interactive voice response systems (IVRs) use natural language processing to direct patients to the right department without the endless “Press 1 for…” menus.
• Smarter triage. AI can assess patient symptoms through virtual tools or integrate data from remote monitoring devices, alerting clinicians to potential red flags. Patients get quicker answers, and fewer calls are escalated to clinical teams unnecessarily.
• Personalized interactions. By analyzing patient data, AI can tailor responses to individual needs. It can even pick up on emotional cues, like frustration in a caller’s tone, and prompt agents to respond with extra empathy.
• Streamlined workflows. No more toggling between five systems to answer one question. AI unifies data and tools into a single interface, cutting down call times and improving first-call resolution rates.
• Data-driven insights. With AI monitoring of call trends and patient sentiment, managers can identify bottlenecks, predict call surges, and optimize staffing in real time. Agent training becomes more targeted and precise, with AI creating simulations based on actual patient scenarios.

Imagine this. A patient calls to reschedule an appointment. Instead of waiting on hold, they’re greeted by an AI assistant that offers new time slots in seconds. If the issue requires a live agent, the AI assistant hands it off to an agent with all the relevant information already on-screen, saving time and reducing stress. After the call, the system updates the EHR automatically, reducing admin work for clinicians.

Now multiply that scenario across thousands of interactions daily. Patients are happier, agents are less stressed, and hospitals save money. Everybody wins.

One standout solution is Amazon Connect, a cloud-based, AI-powered contact center platform. Its pay-as-you-go model appeals to cost-conscious health systems, and its integration capabilities make it a natural fit for EHR and ERP systems. Features like sentiment analysis, real-time agent guidance, and automated follow-ups are helping hospitals improve patient satisfaction scores, reduce costs, and boost agent productivity.

Healthcare organizations often approach AI with caution, fearing high costs and uncertain ROI. But contact centers offer a low-risk AI entry point. The stakes are manageable, the technology is already being used with great success in healthcare, and the benefits are immediate. In an era of tightening margins and growing patient expectations, AI-powered contact centers are the rare innovation that checks all the right boxes.

The contact center of the future isn’t just about answering calls. It’s a hub for patient engagement, seamlessly integrating with clinical and administrative workflows. It captures real-time insights to improve operations, outcomes, and experiences across the board.

Here’s the bottom line. Healthcare doesn’t need to wait for AI to revolutionize clinical care. The revolution can start today, in the contact center, with tools that deliver immediate, meaningful improvements for patients, providers, and staff alike.

Readers Write: The Future State of AI and Automation in the Revenue Cycle

The Future State of AI and Automation in the Revenue Cycle
By Patrice Wolfe

Patrice Wolfe, MBA is CEO of AGS Health.

Like many heavily regulated industries, healthcare has seen limited progress towards the use of artificial intelligence (AI) and automation, despite the enormous potential they hold for improving productivity, accuracy, care access, and the bottom line. Much of that promise comes from use cases that span the revenue cycle management (RCM) continuum, where legacy automation tools are already having a positive impact through activities like patient reminders, insurance verification, coding, and claims status transactions.

Today, generative AI (GenAI) is poised to upend, in a positive way, healthcare’s approach to front- and back-end financial operations. It has the potential to re-imagine the massive volumes of historical and real-time revenue-related data that is flowing through RCM departments and create entirely new approaches to optimize revenue and minimize financial risk.

AI is an advanced set of tools run by algorithms that use data to simulate human intelligence. GenAI takes things several steps further by leveraging that same data to not only tell the story of what it sees, but to also create entirely new, more effective approaches to RCM.

Already present in many RCM functions, AI and automation represent a continuum of capabilities that can be broken down into four major categories:

• Basic. Rules-based processes for repetitive tasks that typically follow pre-defined instructions without exceptions. Examples include a claim status or transaction query submitted by a provider using a basic bot or ANSI transaction that returns a response based on a predefined set of values.
• Advanced. Leverages more complex algorithms and machine learning to make predictions based on past performance, which allows for proactive intervention based on those probabilities. For example, a machine learning model may be able to identify claims that are likely to be denied and can be corrected before being submitted to the payer.
• Intelligent. Here is where AI enters the continuum with the addition of natural language processing (NLP) that uses unstructured data and human-like reasoning to process ambiguity. An example in RCM would be the use of machine learning, deep learning, and NLP models that recommend “next best actions” to prevent denials from even happening in the first place.
• GenAI. Uses neural networking and large language models (LLMs) with deep learning and other techniques to automate design and do complex problem solving, often aided by visual and written materials. An example would be a human-like chatbot that negotiates with payers to reverse claim denials using the clinician’s notes and imaging studies to develop an argument complete with appropriate medical terminology.

While healthcare remains in the early stages of the AI continuum, more complex and sophisticated Intelligent and GenAI use cases are on the horizon.

While all eyes are on GenAI, earlier-stage AI and automation is already impacting RCM outcomes and efficiencies. Meanwhile, ample opportunity exists to further influence RCM as capabilities grow. In fact, just as AI and automation fall on a continuum, so too do the RCM processes and workflows that can be boosted by their adoption.

Scheduling and Registration

Legacy automation has a stronghold in scheduling and registration with the use of basics like automated patient reminders now nearly ubiquitous among healthcare organizations. Looking toward the future, scheduling chat bots, integrated scheduling across care sites and clinical specialties, and comprehensive scheduling packages for patients that include cost estimates are high-priority investments for their potential to reduce patient friction, enhance the patient experience, and make a provider “stickier” by strengthening the provider-patient bond and improving patient retention.

Patient Access

Insurance and benefit verification are already close to fully automated. RCM’s holy grail of future automation use cases is prior authorization, particularly as payers build more complex and ever-changing policy requirements for prior auth. AI can help manage the prior auth process, maximize the probability of approval, and automate the appeals process if an authorization is denied. The challenge is the enormous amount of information that is required from both providers and payers who have little incentive to be transparent with those details.

Coding/HIM

Computer-assisted coding (CAC) enjoys broad adoption for inpatient coding and billing, delivering reported productivity gains of 10% to 30% for hospitals. Computer-assisted professional coding (CAPC) is beginning to make inroads on the professional side. Future use cases include autonomous coding, which has limited use in a handful of specialties due to the significant amounts of data needed to properly train the specialty-specific LLMs. Early work is also underway around ambient charting, which converts voice dictation into coding and promises to save physicians up to 4.5 minutes per chart by some estimates.

Patient Financial Services

As with prior authorization, AI and automation adoption in patient financial services is influenced by increasingly aggressive payer policies around denials, delays, and underpayments. There is enormous potential for streamlining collection workflows, including touchless A/R. Other promising areas are automated denials management and the movement to a reduced friction patient experience.

Clinical Services

Though farther behind other stops on the RCM continuum, future AI and automation use cases within clinical services include real-time patient status monitoring in utilization management (UM) to ensure accurate reimbursement. Other potential applications include professional fee UM and automated clinical documentation integrity (CDI) that uses NLP and other advanced tools.

Revenue Integrity

Also behind the adoption curve, revenue integrity AI and automation use cases include charge master maintenance, late charge identification, and coding/billing compliance audits. AI and automation are also used to proactively identify and resolve problem areas.

Healthcare has taken a cautious approach to adopting GenAI and other advanced forms of AI and automation within RCM, due in part to the industry’s necessarily risk-averse nature. Also at play are the complexities that are involved with adapting critical workflows to advanced AI and the need to balance the application of limited resources between multiple and sometimes conflicting strategic priorities.

For example, while advancements like ambient documentation are crowd pleasers that promise to deliver improvements in physician productivity and satisfaction, they won’t necessarily improve the completeness of clinical documentation. As such, CDI will remain a critical part of the RCM process.

The reality is that while GenAI and its AI peers hold great promise for optimizing RCM, these technologies can be expensive to use, staff, and support. Health systems and other provider organizations will have to place bets with scarce resources, and it’s more likely that AI use cases that improve physician and patient satisfaction will come out on top.

GenAI and advanced automation also require close collaboration between operating departments like RCM and their IT colleagues to create and test APIs, move/share data between systems, and access datasets to test predictive models and train LLMs and other advanced AI models. This collaboration may be hampered by information and data silos that were created by legacy technologies. This also impacts the opportunity to leverage AI and automation to create a seamless patient experience, which requires integration across multiple settings of care, systems of record, and data siloes.

As GenAI and other advanced automation solutions continue to deliver on their promise, the impact on healthcare RCM has the potential to be transformational. They also have the potential to reduce the challenges that are confronting providers across the RCM continuum, while streamlining patient access, increasing coding and billing accuracy, improving utilization management, and speeding the revenue cycle.

When the productivity and accuracy promises are fully realized, investing in GenAI and its predecessors becomes a true win for the entire healthcare industry.

Readers Write: What We Can Learn about Mental Healthcare from a Cattle Farm

What We Can Learn about Mental Healthcare from a Cattle Farm
By Teira Gunlock

Teira Gunlock, MHA is CEO of First Stop Health.

What does mental healthcare in the United States have in common with a farm? As a healthcare executive who grew up on a cattle farm in Missouri, I can tell you there are more similarities than you might think.

Let’s start with what we know. Mental healthcare in the US is in crisis. One-third of Americans say they can’t get the help they need, and both individuals and employers face the same barriers to care of cost and access. Mercer reports that 94% of large employers have increased their investment in mental health coverage over the last three years, a trend we’ve also seen in small- and medium-sized businesses.

And yet, people aren’t getting the care they need because it’s too expensive and there aren’t enough providers to meet the demand. Costs will only continue to rise, making it increasingly more challenging for employers to provide adequate coverage.

Virtual care has the potential to fill this gap. For employers, virtual care offers the promise of low administrative costs, high utilization, ease of engagement, and a positive patient experience. For patients, virtual mental healthcare means that they can see providers on their own schedule, with fewer barriers to getting care.

Seems like virtual care is the silver bullet, right? Not exactly. A lot of virtual mental healthcare models have fallen short where it counts. With low engagement rates and poor patient satisfaction scores, the current model has proven unsustainable. Many providers are cutting out telehealth options altogether. 

Clearly, the system is broken.

This is where the farm analogy comes back in. On the farm where I grew up, things are constantly broken – fences, machinery, you name it. I learned that small fixes each day can make a big impact over time. A problem may seem overwhelming, and healthcare surely is, but big problems just don’t get solved overnight. They require a series of small, ongoing fixes rather than a one-and-done solution. I bring that mentality to my work in healthcare every day.

Revolutionizing the mental healthcare landscape is a lofty goal, and no one company can do it alone. It requires insights and innovative ideas from people with a wide variety of expertise and experience who are passionate about being part of the solution.

During the pandemic, when mental health services were desperately needed, we saw a proliferation of virtual mental health solutions enter the market. Those early solutions addressed some of the problems, but we learned there was more to fix.  

Effective care requires removing the barriers that prevent people from accessing it. In mental healthcare, high costs, difficulties in connecting with providers, and lack of long-term support all hinder patients from getting the care they need. Moreover, mental healthcare can’t be siloed from the rest of a patient’s care; it must be integrated to treat both the mind and body as a whole. 

The right virtual model can address many of these roadblocks. First, effective virtual care, particularly in rural areas, combined with on-demand access to licensed therapists and mental health coaches, can connect patients wherever they are. 

Second, a streamlined payment model allows for flexibility for providers and patients. It eliminates both out-of-pocket costs and the complicated and expensive reimbursement process.

Third, progress with mental health looks different for everyone, and care works best when it’s ongoing and sustainable. Long-term care models that also support provider selection allow patients to build a relationship with a provider they choose, making them more engaged and invested in their care journey. 

It’s unlikely that the demand for mental health services will decline any time soon, making it more important than ever to have sustainable models that can get patients the care they need. Virtual mental healthcare works best when patients have options that increase their access, are low-cost, and allow for relationships to build between patients and providers over time.

Just like on the cattle farm, fixing what’s broken requires constant problem-solving and resilience. To make meaningful change, we must leapfrog over the status quo and commit to reshaping mental healthcare into a system that emphasizes whole-person health, seamless access, and that puts patients first.

Readers Write: Healthcare’s Hidden Cost Crisis: How Middlemen and Outdated Tech are Bankrupting America

Healthcare’s Hidden Cost Crisis: How Middlemen and Outdated Tech are Bankrupting America
By Navin Nagiah

Navin Nagiah, MS is co-founder and CEO of Daffodil Health.

Recent articles, including those in The New York Times, have shone a spotlight on how middlemen contribute to rising healthcare costs, notably out-of-network (OON) pricing companies like MultiPlan and pharmacy benefit managers (PBMs), whose fees often obscure and inflate costs. While these analyses are thorough, they often focus on single facets of a sprawling, deeply rooted problem.

The truth is more intricate and defies simplistic solutions. High costs in US healthcare have accrued over decades, shaped by actions across the board, from government policy to insurer practices, provider pricing, and patient behavior.

The presence of intermediaries such as PBMs, OON re-pricing firms, and healthcare consultants reflects the US healthcare model’s structural complexity. As a hybrid of public, private, and even cash-based systems, it has produced a $4.1 trillion industry — 22% of the total economy — where $1 trillion alone goes toward administrative costs, with an estimated $500 billion of that deemed unnecessary or wasted.

For ordinary Americans, this complexity translates into hardship. Forty-one percent are burdened with medical debt; 46% forgo needed care due to cost; and 58% of debt collection involves medical bills. This financial strain is unsustainable for individuals, society, and the nation at large.

An underlying issue is healthcare pricing, which is inelastic, opaque, and tethered to outdated systems. Unlike typical markets, healthcare prices in the US do not respond to supply and demand. The pricing framework is labyrinthine, requiring deep domain expertise to navigate tens of thousands of procedural codes and varied pricing methods. Additionally, administrative systems used by both payers and providers often rely on outdated technology, exacerbating inefficiencies.

However, this does not make the primary actors — whether insurers, providers, or third-party entities — the villains of the story. In a capitalist framework, each stakeholder is incentivized to prioritize revenue and profits. Healthcare is no exception. It’s probable that any rational actor in similar roles would make comparable decisions.

The question we must address is: How do we move forward? What changes are necessary to begin mending this broken system?

The solution demands both regulatory and technological reform. First, let us take a closer look at regulation, where bipartisan consensus on the need for reform offers rare common ground. The No Surprises Act, for instance, was enacted under one administration and implemented by another, underscoring shared political will to mitigate healthcare’s impact on everyday Americans. Yet if we are to achieve genuine change, regulatory bodies need to adopt a more thoughtful and strategic approach.

Understand the market dynamics of payers and providers

Insurers and providers operate with the goals of revenue and profit growth, which regulators and regulations often fail to consider. Laws that don’t account for potential loopholes simply shift costs rather than reduce them, creating the illusion of progress. It is imperative to keep in mind that rising healthcare costs implies higher revenue for providers; a higher revenue for providers means higher premiums, i.e. revenue for payers.

The stock market rewards revenue growth way more than improved margins. This provides extensive incentive to payers and providers to be innovative in how they “shift costs” when regulations are passed.

Regulation must be crafted with an understanding of its potential impact on healthcare costs for ordinary people, avoiding the squeezed balloon effect, where costs shift without any overall cost reduction.

Recognize healthcare’s local monopolies

While other sectors, like technology, are subject to national antitrust scrutiny, healthcare operates across many local micro-markets with localized monopolies. Regulation should reflect this structure, addressing these micro-monopolies with tailored policies that account for regional market dynamics.

Stop adding to the middlemen problem

Regulations must be enacted with caution to avoid inadvertently inflating the healthcare sector’s administrative footprint. The Transparency in Coverage Act, for example, while intended to increase transparency, has spawned a cottage industry of compliance tools companies and consultants — more middlemen — with minimal impact on consumer costs. Future regulations should include clear expectations and mechanisms for affordable, effective compliance without adding new categories of middlemen to the already bloated system. Additionally, regulatory enforcement should be robust, ensuring that non-adherence results in significant penalties that deter cost-shifting practices.

Without these considerations, regulatory measures may perpetuate the inefficiencies they aim to resolve. Now more than ever, Americans need a healthcare system that prioritizes access, transparency, and genuine affordability. Legislative reform, combined with strategic enforcement, could be the first step toward this elusive goal.

Second, let us take a closer look at technology. Once a system, any system, reaches a certain level of complexity, simplifying it again becomes a near-impossible task. However, technology offers a pathway to managing complexity in ways that improve usability and efficiency. Consider the internet. It’s an enormous, convoluted system, yet search engines allow us to find information quickly and (usually) accurately.

In healthcare, however, technology has so far largely added to both complexity and the cost burden rather than easing it. Generative AI could mark a turning point. This technology is unique in its ability to emulate human skills like storytelling, a talent that was once thought exclusive to humans, which helps achieve shared understanding and collaboration. The potential is enormous. AI systems can now analyze, interpret, and convey information much like a human, which could impact healthcare administration, a sector valued at $1 trillion, half of which is estimated to be wasteful expenditure.

Take the process of claim re-pricing and payment as an example. After a doctor generates a bill for reimbursement, that claim may pass through as many as 10 companies and 12 software systems, each with its own requirements and procedures, before the doctor is paid. This labyrinthine process stems from decades of regulations, changing market dynamics, and piecemeal ad hoc solutions. Yet by deploying Generative AI and semi-autonomous agents, we could digitize and automate this entire process from end to end, significantly cutting down on time, costs, and redundancies.

Similar opportunities exist across other healthcare administration processes, whether in prior authorizations, member enrollment, or patient management. I am not suggesting that technology or Gen AI is a silver bullet. This is a long-term undertaking, demanding deep expertise in both healthcare and technology, a rigorous attention to detail, and considerable patience. Still, nothing in the nature of the problem makes it unsolvable.

Companies routinely embark on “moonshot” projects that demand decades to bear fruit, like Facebook’s Metaverse, Elon Musk’s SpaceX and Neuralink, and Google’s Waymo, Wing, and Loon. These projects capture public imagination and dominate media cycles, but moonshots in healthcare administration, though less glamorous, offer far greater potential for transforming lives.

We need to encourage visionary entrepreneurs to pursue these difficult challenges within healthcare. Initiatives that, though unglamorous, offer substantial benefits to consumers and society at large. Government support is also crucial. Legislation that promotes competition within local healthcare markets and policies that encourage innovative solutions for complex healthcare issues would drive meaningful progress.

Readers Write: Tackling Diabetes Distress in Dual Eligibles Requires Integrated Care Management

Tackling Diabetes Distress in Dual Eligibles Requires Integrated Care Management
By Barbara Greising

Barbara Greising, MBA is chief commercial officer at Podimetrics.

Diabetes is a demanding condition. Slipping up even a little can quickly lead to devastating outcomes, and there’s never, ever a day off. 

The constant stress can lead to feelings of discouragement, isolation, frustration, and exhaustion, especially when the consequences of suboptimal self-management can be so severe. For example, every 3.5 minutes, someone in the US loses a limb due to complications of type 2 diabetes (T2D), and up to 50%of those individuals may face death as a result within just two years.

For people living with diabetes and behavioral health challenges, such as a large number of the socioeconomically complex dual-eligible Medicare/Medicaid (DE) population, the outcomes could potentially be even more catastrophic, with mortality risks up tofour times higherthan people with either condition alone.

Up to 45% of mental health conditions and cases of severe psychological distress go undetected among people being treated for diabetes. And with nearly a third of DEs experiencing a serious mental health disorder of some kind, including major depression, that’s a potentially huge number of high-needs people who are not getting appropriate care.

Without proactive, personalized mental health support for these individuals, “diabetes distress” can take root, leaving up to half of people with diabetes feeling overwhelmed, defeated, disengaged, and less equipped to manage their everyday needs at some point in their health journey.

It is crucial to understand the root causes of diabetes distress, particularly in high-risk, highly complex DE populations, and develop proactive, personalized strategies rooted in integrated case management techniques that merge effective mental healthcare resources and socioeconomic support with more traditional approaches.

The first step for assisting people with diabetes is knowing if they need help. Standardized questionnaires like thePHQ-9 can be helpful, but these tools are not usually designed to uncover diabetes-specific concerns, nor are they always used at the most effective points in the diabetes management process.

Providers and health plans may consider augmenting data collection efforts with more targeted measurement tools for diabetes distress, such as the American Diabetes Association’s Problem Areas in Diabetes (PAID) Scale. This check sheet asks detailed questions, such as if the person feels scared, angry, or discouraged when thinking about living with diabetes, what their support system looks like, and how much energy diabetes care takes from them each day.

Providers should also look at patient barriers from every angle to reveal hidden challenges. For example, when one patient stopped engaging in daily self-monitoring for diabetic foot ulcers, it wasn’t because she didn’t understand the importance. It was because she couldn’t get to her doctor’s office to get a refill of her blood pressure medication. The frustrating situation and negative health effects from being off her meds meant she wasn’t feeling able to take care of herself fully.

When the patient received help to get connected with plan-based home care benefits to see a primary care provider for a refill, she reengaged with her foot care immediately, and at the same time, avoided an ED visit for potential hypertension complications.

Regularly fielding holistic questions about self-care competencies in the routine primary care environment is important, but plans and providers should also consider refreshing their data at other key points, such as during specialty visits for associated complications and before discharge from a hospital due to a diabetes-related event. This can ensure that individuals get the help they need when they need it, before diabetes distress becomes overwhelming.

Case managers can assist with this process by spearheading the development of compassionate, informed patient-provider and/or member-health plan relationships. These care team “quarterbacks” can help connect individuals with social workers, psychologists, psychiatrists, substance abuse counselors, and other behavioral health professionals to augment clinical care. 

Case managers, especially those with nursing backgrounds, often have the training, intuition, and experience to identify people who may be struggling with a variety of non-clinical concerns and can successfully pair these insights with their clinical knowledge of diabetes management to support and guide people with diabetes to better glycemic control and improved overall mental health and well-being.

To be effective, however, case managers must be equipped with the tools and resources to perform this work appropriately. For example, health plans and provider networks will need to ensure that high-quality mental health resources, such as patient support programs, social workers, and counseling options, are consistently available for referral in a timely and affordable manner. 

Case managers also need digital infrastructure to make referrals to socioeconomic support organizations, monitor the use of personal medical devices like continuous glucose monitors, and interact with individuals according to their preferred communication channels.

Diabetes distress is not a condition that can be wholly cured by a single pill or one-and-done injection. Instead, it requires ongoing attention and flexible degrees of management to establish and maintain emotional and mental equilibrium in the face of prolonged stress.

That means Medicare and Medicaid health plans, providers, case managers, patients, and unpaid caregivers must collaborate closely at all times to build a scaffolding of support around every individual.

Care team leaders should ensure that people with diabetes understand how, when, and why to use their medications and personal devices, especially when adding new technologies to the mix. Regular follow-ups around socioeconomic concerns and mental health status will be essential to success, including periodic refreshes of questionnaires and other patient-provided data. Health plans, health networks, and other industry stakeholders will need to remain dedicated to expanding access to mental and behavioral healthcare resources, especially in communities with a higher prevalence of diabetes.

By collecting the right information and getting people connected to the most appropriate resources for their needs, case managers can reduce the impact of diabetes distress on dual-eligible individuals and create the conditions for success for the tens of millions of people living with diabetes.

Readers Write: Collaboration, Trust Remain Essential to Connecting the Last Mile for Healthcare Interoperability

Collaboration, Trust Remain Essential to Connecting the Last Mile for Healthcare Interoperability
By Matt Koehler

Matt Koehler is vice president of product innovation for Surescripts.

Successful collaboration in healthcare, while easier said than done, almost always results in meaningful improvements, such as better quality, safer, and less-costly care for patients. Collaboration is essential to innovation because it reinforces the trust that is needed between stakeholders. It’s especially critical when the safety and lives of patients are at stake. 

Stakeholder collaboration and industry input have been key in the development and implementation of the policy changes that are reflected in Common Agreement Version 2.0 that was released in July 2024 by the Assistant Secretary for Technology Policy / Office of the National Coordinator for Health Information Technology (ASTP/ONC) and The Sequoia Project or the Recognized Coordinating Entity (RCE). 

Beyond the technical aspects of this work, it’s worth emphasizing that ASTP/ONC and the RCE purposefully did not go it alone. They brought together the very healthcare technology stakeholders who would be directly impacted to weigh-in and develop the Standard Operating Procedures (SOPs) or the guidelines their organizations would ultimately be required to follow. They are the same guidelines that future healthcare technology innovations that are aimed at advancing interoperability would be built upon.  

The stakeholder-developed SOPs introduce new exchange purposes (XPs) to reflect the need to be more specific and intentional about why patient information is requested and exchanged. For example, TEFCA Required Treatment was introduced to clarify when Participants and Subparticipants must respond to a request. Additionally, three new Health Care Operations Level 2 XPs were introduced to require future exchange for Care Coordination/Case Management, HEDIS Reporting, and Quality Measure Reporting.

These changes provide a framework to illustrate the scenarios where future use cases will be required: 1) scenarios that fall under existing HIPAA definitions for use of healthcare information; and 2) have well-defined requirements for what data must be exchanged. The new XPs will be required in February 2026, marking an exciting evolution of information exchange. 

This new guidance is widely supported by industry experts who agree that it will deliver on its promise to advance interoperability, better enabling clinicians to provide safer, quality, and less-costly care for patients.

Another recent example of collaboration driving innovation is the Sequoia Project’s new Pharmacy Workgroup. As part of their Interoperability Matters program, this work looks to advance clinical interoperability for pharmacies. Specifically, to address barriers that they experience today related to the exchange of clinical data to provide clinical services by developing practical guidance to prepare and adopt these new standards. 

At a time when the challenges facing healthcare seem insurmountable, every example of cross-industry collaboration that led to a successful outcome, like developing the new SOPs, should be a hopeful reminder that together we can make meaningful progress towards improving care for patients and clinicians.   

We should remain committed to this work because of what it means for patients and the future of healthcare across the country: an exciting new framework for safe and effective interoperability with trust at the center of every new healthcare innovation. 

Readers Write: Rethinking Specialty Care in the Shift to Value-Based Care: Getting the Orchestra in Tune

Rethinking Specialty Care in the Shift to Value-Based Care: Getting the Orchestra in Tune
By Najib Jai, MD

Najib Jai, MD, MBA is co-founder and CEO of Conduce Health.

In a value-based care world, the healthcare system operates like an orchestra that is attempting to perform a symphony. Primary care has led this effort — taking on risk, coordinating care, and striving to keep patients healthier in a more efficient way. Specialty care, however, has historically been left to play its own tune, disconnected from the overarching melody that defines value-oriented models.

This paradigm leaves patients navigating a seemingly divided ecosystem that often struggles to align around what’s best for them. Most visibly, individuals who are living with complex chronic conditions — especially those who are from historically marginalized and underserved communities — are left deserted somewhere in the middle.

As these models mature and we enter into the next frontier of value-based care, specialty care must come into alignment, which will allow every part of the system to contribute to the same score.

One of the biggest challenges that I have experienced, both as a physician and through my work with value-based care organizations, is the misalignment between specialty care and the core value-based ethos that has increasingly guided primary care. Primary care physicians (PCPs) are rewarded for keeping patients healthier and out of the hospital, while specialists often remain in a fee-for-service model, incentivized by the volume of care provided rather than quality and patient outcomes. Akin to a talented violinist who performs a beautiful and isolated solo, this fragmented care may be technically impressive, but is ultimately disconnected from the collective performance.

This issue isn’t just about efficiency or cost control, it’s about equity. Patients from underserved communities, who often face the highest barriers to specialty care access, are disproportionately affected. These patients, who may be burdened by multiple chronic conditions such as kidney and heart disease, require coordinated efforts from primary and specialty care providers. They shouldn’t have to experience the vertigo of moving among different worlds when visiting various physicians. This disconnect can lead to conflicting advice, confusion, and missed opportunities for early and effective intervention.

If we truly want to begin addressing disparities in health outcomes, building bridges between primary and specialty care is a critical effort. Excellence in isolation, much like a disjointed symphony, is jarringly insufficient. Different components must work together seamlessly to create a beautiful melody.

To bring specialty care into the fold of value-based care, we must address the incentive structures that keep it siloed. Specialists need to be rewarded for their contributions to patient outcomes. Bundled payments, shared savings, and capitation agreements are all imperfect tools standalone, but can make a significant difference if implemented effectively.

When incentives align, specialists are more likely to collaborate with primary care teams, contributing holistically to patient outcomes. Much like a symphony, physicians are a part of one group that has the single aim of taking care of patients. Aligned incentive structures solidify this implied connectivity.

Lack of integrated data has become a ubiquitous healthcare challenge and impediment to the symphony of value-based care. Too often, specialists must make decisions without access to the full picture of a patient’s longitudinal medical history and lived experiences. These data silos make it difficult for well-intended physicians to deliver coordinated care. Interoperability remains a buzzword, but true integration is paramount for specialists and PCPs to operate from the same “sheet music.” A cardiologist who is treating a patient without seeing their recent visit notes from their PCP is like playing a solo without knowing the key of the piece. At best, it creates dissonance, and at worst, it causes harm.

While data may present a challenge, it also represents an opportunity. Leveraging data-driven insights to personalize specialty care can ensure that patients are connected with the right specialist at the right time. Instead of generic referrals, predictive models and frictionless workflows can help identify which specialists are best suited for each patient’s nuanced needs while maintaining the clinical autonomy of providers.

Understanding performance through the lens of a patient’s’ comorbidities, social drivers, care preferences, and the specialist’s experience with similar patients unlocks a novel, personalized approach to integrated specialty care. Analogous to an esteemed flutist not playing the cello, specialists have skills and training that positions them to serve certain patient populations better than others. This approach ensures that referrals are not only timely, but also meaningful, leading to better outcomes and a more efficient care journey.

The cultural shift that is required to bring specialists into value-based care is perhaps the most challenging part of this transition. Specialists are highly trained and adroit experts who are focused on their specific area of practice. However, creating a value-driven system means that all physicians must think beyond their individual role and understand how they fit into the broader picture of a population’s health.

This requires fostering a culture of collaboration, where specialists are enabled to see themselves as part of a broader healthcare orchestra rather than isolated soloists. It’s about creating an infrastructure in which their expertise is more clearly seen as one critical component of a larger effort to provide patient-centered care.

If we get this right, the potential for positive change is immense. By aligning incentives, improving data access, and fostering a culture of integration, we can create a coordinated and cohesive healthcare chassis. While simple in theory and challenging in practice, a meaningful opportunity remains – ameliorating a system of incongruous care that so many patients experience, particularly those who are already struggling due to systemic inequities.

It’s time to do away with the solos and grow towards a unified symphony, one that prioritizes the patient’s experience and ensures that every provider is working from the same score. It’s time for “value-based care 2.0” where specialists have a seat in the orchestra.

Readers Write: HLTH 2024 Did It Again

HLTH 2024 Did It Again
By Mike Silverstein

Mike Silverstein is managing partner of healthcare IT and life sciences at Direct Recruiters, Inc.

Once again, HLTH 2024 delivered. In my opinion, HLTH has become the most important healthcare conference on the calendar, and this week’s event in Las Vegas did not disappoint. While sales teams manning booths may have found it less fruitful for direct lead generation, that’s not the true purpose of this conference. HLTH and its sister conference ViVE are where healthcare’s biggest strategic moves are set into motion.

No other event except perhaps the JP Morgan Healthcare Conference brings together such a diverse mix of healthcare investors and vendors from around the world under one roof. HLTH plays a crucial role in shaping the industry’s three- to five-year outlook, and I would argue that it’s even more impactful than JPM since it fosters face-to-face connections in one concentrated venue.

Despite ongoing political uncertainties, the market flywheel is starting to spin again. After a year and a half of valuation struggles, investors and companies are finding common ground. Investment bankers who I spoke with mentioned that deals are once again flowing, and I expect a wave of health tech and healthcare services companies to announce successful funding rounds in the coming months.

Interest rates are beginning to tick down, and HLTH serves as a prime meeting point for key players across the ecosystem — vendors, payers, providers, life sciences, and employers. As healthcare costs continue to rise, software designed to reduce expenses and drive system-wide efficiency is becoming indispensable. Unlike HIMSS, which is more narrowly focused on health systems, HLTH brings together the entire healthcare economy, providing early-stage investors with access to companies on the cutting edge of innovation.

AI was the dominant theme at HLTH, and its influence is only expanding. The companies that are making the most traction attracted significant attention from investors who are eager to deploy capital from the funds raised in 2022, which remained largely untapped in 2023 and early 2024. These companies are focusing not only on cost reduction, but also on addressing the looming clinician shortage that will hit the healthcare system over the next decade.

Solutions that reduce time spent by doctors and nurses on administrative tasks, allowing them to focus more on patient care, are in high demand. Technologies like ambient scribing and workflow tools that augment Epic are gaining traction, helping clinicians operate at the top of their licenses. Additionally, AI is finally showing real potential to address healthcare’s persistent interoperability challenges, a problem that has long frustrated the industry.

While the upcoming election could reshape parts of the healthcare landscape, HLTH 2024 reaffirmed a more immediate truth: the healthcare industry is primed for growth and innovation, with investors ready to fuel the next wave of transformation.

Readers Write: Primary Care Mental Health Support Requires a Whole-Person Care Approach

Primary Care Mental Health Support Requires a Whole-Person Care Approach
By Cynthia Horner, MD

Cynthia Horner, MD is chief medical officer of Amwell. 

Primary care physicians started seeing a dramatic uptick in the number of patients with mental health concerns even before COVID took a toll on the country’s mental health. Now, as the nation struggles with record-high rates of distress and a lack of access to mental health support, there’s a critical need for the healthcare industry to embrace an integrated, whole-person approach to care.

Nearly one out of four adults experienced a mental, behavioral or emotional illness of some type in the past year, according to the latest report from the Substance Abuse and Mental Health Services Administration. For primary care physicians, the swell in the need for mental health support reflects a pattern they have seen during the past two decades:

• From 2006 to 2018, primary care visits that addressed mental health concerns grew 50%, from 10.7% to 15.9%, according to a study in Health Affairs.
• Between 2016 and 2018, about 40% of patients who were diagnosed with anxiety, depression, or any mental illness saw their primary care physician for treatment.
• The percentage of people suffering from anxiety and depression has doubled since before the pandemic. Medicaid data illustrates the enduring impact of COVID, with prescriptions for mental health-related conditions outpacing prescriptions for other conditions in 2022.

To help as many people as possible, we must initially reach patients where they are most likely to be seen: by their primary care providers.

The shortage in the behavioral health workforce may be why more people are turning to primary care physicians for support. The National Center for Health Workforce Analysis reports that as of December 2023, more than half the U.S. population—169 million Americans—lives in a mental health professional shortage area. Compounding the issue is a lack of primary care physicians to meet patients’ health needs.

Given the shortfall of mental health and primary care professionals, virtual care is vital to ensuring that patients have access to the right resources for a whole-person, integrated approach to care. Adopting hybrid care models that include telehealth is crucial to closing care gaps and enabling continuity and access for all.

Primary care physicians have a foundational understanding of mental health conditions. However, a whole-person approach to care — including comprehensive and ongoing mental healthcare from digital programs and behavioral health specialists — is vital to positive outcomes.

That’s one reason why it’s important to continue managing patients even after referring them to a specialist for support. This integrated approach can effectively bridge the gap between physical and mental health.

When it comes to which mental health conditions primary care providers should treat, the acuity matters more than the diagnosis. For example, earlier in my career as a family medicine physician, I managed a patient who was living with schizophrenia. His condition was well controlled and he complied with his regimen and his follow-up. For these reasons, I could continue to treat him. But had his disorder been more acute, or if he had been a new patient and the severity of his schizophrenia was unclear, I would have referred him to a behavioral health specialist.

Ideally, even after that referral, I would have remained part of his care team, received progress updates, and helped manage his other care needs. That’s the best scenario for patients and their primary care providers when they begin working with a mental health professional and receiving care through digital programs.

Whole-person care—delivered in-person, virtually, and through automated care—facilitates collaborative care. It removes the challenges of geography at a time when nearly 80% of U.S. counties are considered healthcare deserts. Whole-person care also offsets the challenges that patients face when they need support from a behavioral health specialist but can’t find one.

As the industry looks for ways to integrate mental healthcare into the primary care setting, here are ways providers can foster whole-person care for overall patient well-being.

• Lean into virtual technologies for support. With virtual primary care, network providers can manage referrals and care across digital behavioral health, urgent care, specialty care programs, and digital companions. This facilitates personalized care and optimal health outcomes by giving providers medical and mental health updates, helping to inform clinical decisions. Embracing virtual technology also minimizes instances where underserved communities can’t access the support they need. Today, 60% of psychologists report that they do not have openings for new patients.
• Establish stronger relationships between primary care providers and behavioral health specialists. Care teams that share assessments, treatment plans, and test results support an integrated model for healthcare. The adoption of health tech solutions nurtures this collective approach to care. It also improves the patient experience and helps align specialty referrals and digital care program enrollments, which empower patients to take an active role in improving their health.
• Partner with health plans to provide the right support for digital populations. This may include investment in a platform that blends in-person care with digital health tools. Evidence shows that patients who are receiving primary care services regularly see 33% lower healthcare costs. In 14 studies that examined the relationship between engagement and efficacy, 64% found that increased engagement with digital interventions was significantly associated with improved patient outcomes.

The movement of patients who are seeking care for mental health conditions from trusted primary care physicians isn’t going to slow or reverse. The industry can strengthen health outcomes by embracing a whole-person care approach, in-person and virtually. We can also keep primary care providers close to a patient’s physical and mental health care, offering the complete, integrated, and personalized support that patients want and need.