Harris Data Integrity Solutions, the leading provider of best-in-class patient data integrity services and software, announced today the promotion of Rachel Podczervinski, MS, RHIA, to Senior Vice President. In her new role, Podczervinski oversees Harris Data Integrity Solutions’ mission to ensure accurate patient identity management through innovative services and software solutions.
Podczervinski brings nearly 25 years of healthcare experience to her new role. Previously, she was vice president of professional services for Harris Data Integrity Solutions, which was created by the integration of Just Associates, Inc. and QuadraMed Corp. Podczervinski originally joined Just Associates in 2005 as a patient identity expert, rising through the ranks with positions including quality assurance specialist, identity manager, and director.
“An unwavering focus on quality and innovation has made Harris Data Integrity Solutions the leading partner for hospitals and health systems that recognize the vital importance of protecting the integrity of their patient data,” says Podczervinski. “I am honored to be entrusted with guiding the future direction of this organization and am excited for what the future holds for our team and the healthcare organizations we support.”
A recognized thought leader in the field of health informatics, Podczervinski brings a wealth of knowledge and expertise to Harris Data Integrity Solutions and the healthcare industry. She speaks frequently at leading industry conferences, providing insights on patient identity and EMPI management, has authored numerous articles for leading industry journals and publications, and was named a Rising Star by the Colorado Health Information Management Association (CHIMA). Podczervinski, who holds a master’s degree in health information management and medinformatics, is active with AHIMA and is an avid volunteer and mentor.
MDaudit, an award-winning cloud-based continuous risk monitoring platform for RCM that enables the nation’s premier healthcare organizations to minimize billing risks and maximize revenues, announced today that its MDaudit billing compliance and revenue integrity platform is a finalist in the 2024 Fierce Healthcare Innovation Awards.
MDaudit is a finalist in the Data Analytics/Business Intelligence category, which recognizes innovative data analytics tools that bring actionable information directly to users by either enabling the wide dissemination of clinical, financial or operational data, or helping them make sense of it. Currently, more than 1 million cases and $8 billion in charges are audited annually on the MDaudit platform and more than $150 billion in denials are analyzed for potential reimbursement. Additionally, more than 5 billion claims are used for benchmarking via MDaudit.
“The innovation strategy at MDaudit starts with our customers; they are at the center of everything we do,” said Ritesh Ramesh, CEO, MDaudit. “This recognition from Fierce Healthcare is a huge acknowledgment of our effort to deliver tangible business outcomes to our customers in the U.S. healthcare system. A huge shout out to our team and partners who work with us diligently every day to innovate and make a difference.”
From Questex’s Fierce Healthcare, Fierce Biotech and Fierce Pharma, the Fierce Healthcare Innovation Awards identify and showcase outstanding innovation that is driving improvements and transforming the industry. Two expert panels of judges determined which innovative solutions demonstrated the greatest potential to save money, engage patients, or revolutionize the industry based on effectiveness, technical innovation, competitive advantage, financial impact, and true innovation. Winners will be announced in the Innovation Report on December 2, 2024.
In a LinkedIn post announcing the 2024 finalists, Fierce Life Sciences Events wrote, “These forward-thinking organizations have demonstrated excellence in healthcare technology, patient care, operational advancements, and more, setting new standards across the industry. Their innovations are transforming healthcare delivery and improving patient outcomes.”
AGS Health, a leading provider of tech-enabled revenue cycle management (RCM) solutions and a strategic growth partner to healthcare providers across the U.S., has received a UiPath AI25 Award for the company’s innovative use of automation and AI to support greater accuracy and efficiency in the intake and management of faxed documents.
Despite efforts to eliminate faxing, use of this cumbersome, inefficient, and costly technology by healthcare organizations remains prolific. Over 9 billion fax pages are exchanged annually at a cost of $125 billion, significantly straining already limited resources.
AGS Health’s IntelligentFax Processor automates this process, accelerating indexing, enhancing accuracy, reducing costs, and improving efficiency by leveraging a hybrid workflow model combining GenAI and robotic process automation (RPA) with manual indexers to handle exceptions. The system can handle a wide array of document formats and types, including consultation notes, test results, and medical records. Powered by advanced AI, it learns and adapts to the unique fax templates of each organization, ensuring accurate data extraction and categorization.
The annual UiPath AI25 Awards recognize the 25 most innovative UiPath customers using a combination of AI and automation as a strategic change enabler to accelerate bigger and bolder outcomes. AI and automation are redefining what’s possible—not just in business, but in the ways we work and live. This powerful combination creates fast, comprehensive, and actionable insights to inform decisions—uncovering never-before-seen opportunities for productivity and innovation.
I’m a confirmed AI optimist and believe the technology will improve healthcare on a broad scale, from diagnosis to drug discovery, precision medicine, robotic surgery, record keeping, analytics, population health, and streamlined claims processing.
But there remains one nut that AI, for all its astonishing promise, hasn’t yet cracked – the growing burden of healthcare costs on the American family. No large language models or artificial neural networks are likely to change that in the near future.
Rather, the nearest-term solution to rising premiums, deductibles, co-pays and out-of-pocket costs is embarrassingly analog. It’s a conceptual change in the payment process. We need to change the business model until technology can do more to lower our collective costs.
The cost of care avoidance
The current model is broken. Most Americans are covered by an employer’s health insurance plan, but it’s not a gift. The employer and employee share the premium.
Unfortunately, family coverage premiums have increased by 22% in the last five years, reaching almost $24,000. When a covered employee seeks treatment, they pay out of pocket up to their deductible and often owe a co-pay. Since 1960, out-of-pocket costs have grown nearly twice as fast as the economy.
If the patient can’t pay at the time of service, which is increasingly common, the household carries a balance and pays interest on that balance indefinitely, absorbing considerable financial stress along the way. Providers become de facto bill collectors, something they did not sign up for when pursuing careers in healthcare. Shamed patients avoid the doctor, risking their health and nudging up longer-term healthcare costs for everyone. More than four in 10 adults (43%) say they or a household member have put off or postponed care due to cost.
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.