Revenue integrity has become harder to maintain as audits grow in volume and complexity. Payers are increasing scrutiny and regulatory agencies are reinforcing fraud mitigation. Navigating this evolving terrain requires a reimagined, automated approach to billing compliance, coding, and HIM, optimizing accuracy and efficiency to protect revenue.
We sat down with Dana Finnegan, Director of Market Strategy with MDaudit, to discuss what’s behind the scenes of reimagining revenue integrity and the role automation can play in achieving success.
EHR: What is driving the need for hospitals and other healthcare organizations to reimagine their approach to revenue integrity?
DF: We’ve identified four trends that are influencing the need for healthcare organizations to take a fresh approach to revenue integrity, maximize reimbursement and compliance outcomes, and optimize operational efficiency—all of which are critical to sustaining long-term results.
First, the average denied dollars per claim continues to rise. MDaudit data shows an overall increase in denied dollars per claim of more than 19% between 2023 and 2024 and a whopping 62% increase in Medicare Part A and B denials during that same period. At the same time, initial response times to claim submissions are also trending up and, once again, Medicare is the driver. Professional response time has increased by nine days, from 15 in 2023 to 24 this year, while hospital outpatient response days increased from 15 to 19 and hospital inpatient increased from 18 to 22 days.
A third trend we’re seeing is in denial rates, which were 21% for hospital outpatient and 27% for hospital inpatient segments. Finally, dollars at risk from external payer audits have doubled, with hospital billing driving most of the external audits in terms of risky dollars and commercial payers and RAC driving most external audits in terms of volume.
The good news is that we are also seeing an increase in technology investments among healthcare provider organizations, especially AI and automation, to push back against these trends and gain a competitive advantage in terms of revenue integrity.
EHR: How can automation provide a competitive edge in terms of revenue integrity?
DF: Manual healthcare billing audits are resource-intensive and prone to human error. The intricate nature of billing compliance, revenue integrity, and coding demands meticulous attention to detail, which makes it susceptible to oversights and discrepancies.
Consider that the 40 largest U.S. health systems average just under 55 hospitals per system, and bill to a wide mix of government and commercial insurance plans. Commercial, private and self-pay represent the largest payer group for U.S. hospitals with net patient revenue of nearly $689 billion, or just over 69% of the average payer mix. Clearly, billing compliance is a complex, high-stakes game even without the added scrutiny from payers and regulators.
Automating manual processes is a pivotal advancement during what is a very challenging time for the industry. Automated audit processes help billing compliance teams locate the proverbial “needle in the haystack” by identifying the highest billing risk patterns and mitigating risk while maximizing revenue—and it does so faster and more accurately than any human could manage. This lets providers stay on top of the rising flood of demand letters that regularly flow through their doors and leverage the power of data analytics to drive meaningful audit outcomes.
Various forms of automation have long been present within healthcare revenue cycle management (RCM). However, advances in artificial intelligence (AI) have brought the industry to a significant inflection point, where the use cases for AI tools are expanding as rapidly as their capabilities.
We sat down with Thomas Thatapudi, chief information officer of AGS Health, to discuss the current and future state of AI in RCM and what healthcare organizations need to know about effectively integrating it into workflows.
EHR: How are automation and AI reshaping healthcare’s approach to revenue cycle management?
Thatapudi: Healthcare finance leaders have long recognized the power of simple automation, like simple rules-based workflows or analytics dashboards, to improve billing processes and error rates. Now, advanced AI tools like ChatGPT, large language models, and generative AI – or GenAI – have brought RCM to an inflection point with a variety of viable new AI-driven RCM use cases that could have significant financial impacts. AI and automation can reduce manual labor costs and increase net revenue through a seamless process that follows the entire patient journey, from preventing authorization denials upfront and reducing coding errors to implementing more proactive and efficient accounts receivable follow-up processes.
With front-end revenue cycle tasks such as insurance verification and prior authorization, we have an opportunity to create a completely seamless and interactive process for patients while ensuring the presence of appropriate controls to mitigate revenue leakage. For mid-cycle coding, certain specialties lend themselves to autonomous coding that eliminates the need for human intervention, freeing staff to focus on more complex work. On the back end, the focus can shift to denial management and collection rates, particularly for claims that, due to capacity constraints, were left unworked in the past. This can be particularly beneficial in cases where payer requirements have become more stringent.
These examples are just the tip of the iceberg in terms of potential RCM use cases over the next two years.
EHR: What are some examples of areas where AI tools are being used to improve RCM?
Thatapudi: AI is being used in clinical documentation, patient communication and payments, scheduling, prior authorization, and medical coding. In fact, coding has been utilizing true AI and machine learning in the form of NLP-based computer-assisted coding (CAC) for about a decade. With existing CAC applications reaching a plateau in coding accuracies of approximately 70-75 percent, new autonomous solutions are entering the market that leverage deep learning models and Gen AI to truly increase fully automated coding rates. I expect that coding will be one of the RCM areas that will be most heavily impacted by true AI, machine learning, and deep learning.
EHR: How can finance leaders make use of advanced data analytics and business intelligence (BI) tools to inform RCM decisions and measure their impact?
Thatapudi: BI tools can measure a wide range of metrics, from the number of system users to interactions and accounts, all of which can inform the key performance indicators (KPIs) that are crucial for monitoring financial performance. The problem is that the sheer volume of metrics can easily be overwhelming, which can lead to analysis paralysis. To prevent this, it’s important to take a step back and home in on KPIs such as financial indicators like collection rates per day or per month and the time it takes to collect payments—performance indicators that tell how much in time and money is being spent to recover a dollar so it can be reduced or better managed.
It’s important that senior leadership avoid being overly impressed by the wealth of intelligence that can be collected and displayed on a dashboard. The focus should instead be on determining the KPIs that drive day-to-day operational decisions. For example, predictive analytics services help healthcare organizations better predict denials, anticipate underpayments, forecast payments, and more. This allows for proactive claim correction prior to submission, which improves clean claim rates and cash flow. Creating simulations and projections for customized “what-if” scenarios provide an understanding of the impacts associated with interdependent metrics.
By David Sampson, VP of Cyber Risk & Strategy, Thrive.
In February, hackers took Change Healthcare offline in one of the most high-profile and wide-reaching cyberattacks to date. Change Healthcare serves hundreds of thousands of providers in the U.S. and processes billions of transactions every year. With Change Healthcare’s systems compromised, cash stopped flowing for hospitals and physician offices everywhere. Providers couldn’t submit new claims, pharmacies couldn’t charge appropriately for prescriptions, and prior authorizations couldn’t go through for critical procedures.
Even after Change Healthcare’s parent entity, UnitedHealth Group, paid a $22 million ransom to the group behind the attack, there’s still risk that sensitive patient data could be leaked online. More importantly, the healthcare industry saw how a cyberattack on a third-party vendor could directly interfere with patient care.
Unfortunately, cyberattacks on the healthcare industry are growing – and, like the Change Healthcare attack, can wreak havoc on everyday operations and impact patient safety. However, if hospitals take the right precautions, they can mitigate these risks and better protect themselves from hackers, ransoms, and disruptions to business.
The Importance of Evaluating Third-party Vendor Risk
Healthcare organizations often rely on third-party vendors for various services. Delivering high-quality patient care is complicated in and of itself. Building an ecosystem that includes services and solutions like telemedicine, wearables, digital electronic medical records (EMRs), patient-centered mobile apps, and other cutting-edge innovations is impossible for smaller healthcare providers.
Many times, the best way to extend the range of services offered is to work with third-party vendors. The problem is this outsourcing expands the surface area of attack for cyber criminals. Every third-party vendor relationship comes with a new IT integration and potential entry point for hackers. In other words, more third-party vendors means increased organizational risk.
Healthcare leaders must recognize this tradeoff and think intentionally about how best to strike the balance between healthcare excellence and IT integrity. Before onboarding a new vendor, providers must conduct thorough audits, identify all vulnerabilities, and work constantly to ensure systems are integrated in a safe, secure, and resilient fashion. This is not a point-in-time exercise, but one that both healthcare providers and vendors have to engage in regularly to keep intruders away from sensitive patient data.
By Janet Campbell, Chair, EHR Association Social Determinants of Health & Health Equity Task Force
A patient’s risk within social determinant of health (SDOH) domains is typically assessed by social care and healthcare professionals through either conversation, standard screening questionnaires, or validated testing instruments. The challenge is the lack of consensus on which specific domains should be assessed for patients – and how they should be assessed.
This lack of uniformity reflects the absence of a consistent, universally agreed-upon, and prioritized list of domains for assessment, the result of which is overlapping domains that complicate the exchange and interpretation of this data.
Inconsistency Inhibits Interoperability
The absence of clear guidelines for risk assessment and standardized representation of risks in EHRs also hinders effective data exchange to inform interactions at the point of care. The receiving EHR may not be able to interpret data in a way that is helpful to the user, nor can data be aggregated across multiple systems to gain insights into social risks at a broader geographical or environmental scale.
A comprehensive new survey that includes responses from more than 1,500 US patients conducted by Hyro, a leading healthcare AI-powered communications company, reveals that patients throughout the US health system are not only frustrated by poor provider support but are also experiencing tangible health setbacks as a result of these friction points.
Hyro’s “Voice of the Patient” survey and accompanying report highlight significant gaps between patient needs and the current support available through healthcare delivery channels. These care challenges are particularly glaring during appointment settings and when patients attempt to refill prescriptions.
While the survey’s findings provide a plethora of information that may impact patient engagement and patient well-being, the following points suggest providers have some important ground to cover in their service delivery outside of the exam room.
Key findings include:
21% of patients delay or forgo refilling prescriptions due to lengthy hold times and cumbersome provider-created processes
32% of patients report experiencing health complications due to postponing prescription refills
81% of patients believe there should be more self-service options for scheduling appointments with their medical provider
84% would prefer to speak with an AI assistant rather than wait on hold for a live human agent
66% of patients expect their healthcare provider to employ generative AI technologies to enable better online and phone support – this year
“Our Voice of the Patient report clearly shows that patients are ready for more advanced, AI-powered healthcare experiences to reduce their pain points and improve their experience with their providers,” said Israel Krush, CEO and Co-Founder at Hyro. “They’re demanding the same level of convenience in healthcare that they experience in other industries, and providers who fail to meet these expectations risk patient disengagement and potentially exacerbating negative health outcomes of their patients.”
Biologics have revolutionized the field of medicine, offering advanced treatments for a wide range of diseases, including cancer, autoimmune disorders, and genetic conditions. These therapies, which include complex molecules such as monoclonal antibodies and therapeutic proteins, are produced using living cells.
As a result, the development and optimization of cell lines are critical steps in the production of biologics. This article delves into the importance of cell line development for biologics, highlighting the key components and the role of specialized services in ensuring the success of biologic therapies.
Understanding The Role Of Cell Line Development
Cell line development involves creating and optimizing cell lines that can produce the desired biologic product efficiently and consistently. These cell lines serve as the foundation for the production of biologics, making them a crucial component of the entire manufacturing process. The cells used in biologics production are often derived from mammalian sources, such as Chinese hamster ovary (CHO) cells, due to their ability to produce complex proteins with human-like post-translational modifications.
Key Steps In Cell Line Development
The development of a cell line for biologics production involves several critical steps, including:
— Gene Insertion: Introducing the gene of interest into the host cells to produce the desired therapeutic protein.
— Selection: Screening and selecting cell clones that exhibit high productivity and stability.
— Expansion: Scaling up the selected cell line to produce larger quantities of the biologic product.
— Characterization: Conducting thorough testing to ensure the cell line’s genetic stability, productivity, and safety.
The Importance Of Cell Line Development For Biologics Ensuring Consistent And High-Quality Production
One of the primary reasons why cell line development is crucial for biologics is its role in ensuring consistent and high-quality production. The stability and productivity of the cell line directly impact the efficiency of the manufacturing process and the quality of the final product. A well-developed cell line can produce the biologic product at high yields and with the necessary purity and potency required for therapeutic use.
Organizations specializing in cell line development services provide the expertise and infrastructure needed to develop and optimize cell lines that meet the stringent requirements of biologics manufacturing. These services play a critical role in maintaining the consistency and quality of biologic therapies.
Losing weight can really make a difference in daily life. However, changing attitudes and habits is very difficult for many people, and often seems even impossible.
Fortunately, with the help of specialists and doctors, it is possible to achieve the figure of your dreams in a safe, healthy and effective way.
How to effectively lose weight?
Medical weight loss – what is it and how can it be helpful?
How can you effectively shed excessive pounds? Let’s find out more about this topic.
How to effectively lose weight?
To lose weight, if it is not the result of disease but an inadequate lifestyle, you need primarily diet and physical activity. Many people try to change their habits on their own.
However, this is very difficult. It should be remembered that self-prepared diets are very often ineffective. Many people make numerous mistakes when trying to plan a healthy menu with a caloric deficit. As a result, food cravings, feelings of hunger, fatigue often make it easy to break the resolutions made. As a result, a hungry, tired person throws himself on food, wasting all the effort made.
According to one report, business executives mentioned Artificial Intelligence (AI) more than 30,000 times in earnings calls at the end of 2023. AI, and debates around fears, capabilities and ethics have dominated discussions in both the board room and at the water cooler in most industries. I’ve experienced several major technology shifts and innovations throughout my career but the buzz around AI is groundbreaking.
In behavioral health, we’re talking about AI every day and uncovering how it can be a great complement to other technologies used in treatment centers and practices. Our provider clients have reported it boosts note-taking and documentation processes with improvements in accuracy and efficiency. Data produced by Eleos shows providers have reported that documentation time has been reduced up to 50%, allowing clinical teams to spend more focused time with patients.
Providers leveraging AI also said they have 90% of their notes submitted within 24 hours, reducing documentation backlog and avoiding denials due to late submissions. Another key benefit is care teams indicate they’re able to use AI insights to deliver evidence-based best practices, which is excellent for improving patient outcomes.
Testing the waters
Our colleagues at All Points North (APN), a multi-site, 77-bed Behavioral Health system based in Colorado, decided to move ahead with an AI solution. APN was already using Kipu’s EMR, so they chose to go with Eleos, which is integrated with the Kipu EMR. Eleos focuses on supporting documentation and note taking in therapeutic sessions through their AI solution, which was a key area APN was hoping to improve.
Andrea Boorse, senior manager of operations at APN, shared that their clients have two individual therapy sessions each week, rather than one—which means double the documentation. When they became aware of AI solutions that could listen in on sessions and help with that documentation, they decided to test the waters with Eleos’s Scribe solution, which automatically transforms raw conversations into progress note suggestions.
APN found that the tool started to understand and recognize therapists’ style and language, making the notes get more specific and tailored to each client. This has been a big help for APN since it now takes an average of 11 minutes to complete a note, compared to the industry standard of 15 minutes.
Embarking on AI implementation
With benefits like APN has experienced, I’ve seen a shared, cautious excitement across our industry that continues to suffer from provider and staffing burnout and attrition. By removing some of these administrative burdens, they hope to combat staffing issues and improve patient reach and care.
And while there is good reason to remain cautious, I think providers can confidently move towards AI solutions by focusing on three key areas.
By Janet Campbell, Chair, EHR Association Social Determinants of Health & Health Equity Task Force
A comprehensive new survey that includes responses from more than 1,500 US patients conducted by Hyro, a leading healthcare AI-powered communications company, reveals that patients throughout the US health system are not only frustrated by poor provider support but are also experiencing tangible health setbacks as a result of these friction points.
Losing weight can really make a difference in daily life. However, changing attitudes and habits is very difficult for many people, and often seems even impossible.