Healthcare providers are feeling the industry’s talent shortage in their administrative functions as well as clinical areas. One case in point: revenue cycle management. In a recent study, 63% of healthcare providers reported an inability to fill key revenue management roles. Reduced revenues and cash reserves are almost inevitable when providers don’t have sufficient staff to follow up on claims, manage appeals and help patients understand their financial responsibilities and options. 

Fortunately for providers, revenue cycle automation offers timely, cost-effective solutions to the talent shortage. Robotic process automation (RPA) is a proven technology for automating rote, repetitive processes that involve multiple steps and systems and/or substantial human and machine interaction. Using software bots, RPA essentially mimics the keystrokes of human operators. Many bots can be developed and deployed in a matter of weeks. They then work tirelessly and accurately, including during off-hours. At one institution, a software bot cleared a backlog of thousands of claims status checks in just a single weekend. It would have taken humans hundreds of days to accomplish that task. 

RPA is just the start. With software bots streamlining processes and improving data accuracy, the foundation is set for creating more sophisticated automation solutions built on AI and ML models. These can tackle more complex tasks that involve following business rules and making decisions based on the models’ data analysis.  These AI/ML solutions often are more expensive and take longer to implement than RPA. They are best suited for providers that already have standardized processes and cleaner data from their existing automation. 

Unlock revenue fast with robotic process automation

Automating RCM tasks frees up revenue management professionals to take on other, more complex activities, such as providing financial counseling during patient pre-registration activities. RPA solutions will also enable providers to improve revenue cycle productivity without adding additional employees. Many RCM tasks are excellent candidates for automation via software bots and RPA, including: 

Claims status checks. Bots can look up claims data and other information in payer portals, then update systems and even initiate next steps, eliminating these rote tasks and returning time to revenue professionals.

Automated patient pre-registration. RPA bots can link applications and systems together to automate more complex transactions and extract more value from them. Take a patient-facing, self-service registration portal. After a patient agrees to interact digitally with the provider, RPA bots can download patient registration requests; retrieve patient data from an electronic health record (EHR); then update the patient engagement system. The update can trigger the engagement system to send the patient a self-registration and payment link. When the patient completes those steps, the RPA bots can access the payment and patient demographic data and update the provider’s EHR. 

Digitally enabled prior authorization. Bots can easily retrieve patient data, insurance details, CPT codes, physician details, diagnosis codes and schedules from an EHR; flag cases requiring prior authorization; and submit them digitally to a payer portal. Then bots can update records with approved requests. They can also automatically route denied cases requiring additional information to the right clinicians, then refile them when updated. 

What about AI? 

RPA software bots essentially follow sets of rules. While a rule set can be complicated and involve several systems, software bots generally make preprogrammed if/then decisions. Outliers can be routed to finance professionals for follow-up. 

In contrast, automation solutions that incorporate AI and machine learning algorithms can evolve and eventually make autonomous decisions. Put very simply, an ML algorithm learns from the data sets to which it’s exposed, finding patterns and relationships. This makes ML potentially very powerful. ML algorithms can stratify patient accounts by a propensity to pay and automate financial assistance applications. That would reduce costs to collect while improving revenue realization. ML could also identify missing charges and help avoid revenue loss. Those applications, however, are complex. In general, the more advanced the technology, the more time and expense required to implement it. That’s not to take these options off the table. While they undoubtedly will play a role in coding and other tasks, ML and AI applications often are more than many providers need to solve immediate staffing and revenue realization issues. Healthcare organizations must carefully select which processes to automate to ensure the results meet their needs. 

Moving forward with automation

Providers must be clear about what they hope to achieve by automating their revenue cycles and realistic about the time and resources they have available to allocate to the project. The following steps can help guide decisions about which revenue cycle processes to tackle.

• Choose low-hanging opportunities first. Providers should build organizational automation experience before attempting more ambitious projects. The provider that solved its claims status check backlog with RPA initially applied the solution to claims from its largest payer. After succeeding there, the provider then expanded the initiative to claims from its other payers. 

• Choose opportunities that minimize IT involvement. Provider IT professionals often have many competing priorities. Developing RPA software bots requires minimal IT input. 

• Choose a vendor that understands healthcare revenue cycle services. Working with a skilled, experienced vendor helps minimize the time and input a provider’s revenue professionals must give to the engagement. Vendors with RPA and healthcare revenue expertise can build flexible bot frameworks so bots can be extended to other applications with minimal programming.

• Prioritize opportunities that tangibly improve patient and employee experiences. Improving the patient financial experience is a growing priority. Automating tedious, repetitive tasks reduces errors and frees revenue staff to work on more complex issues that deliver more value to patients and the organization. 

• Evaluate the return on investment. Most RPA projects should deliver a return 2 to 3 times greater than the investment. Reconsider projects that have lower anticipated returns or that indicate a long time to ROI. 

The societal changes that have shrunk healthcare’s labor pool are here to stay. Automating the revenue cycle will position providers to improve cash flow, enable their revenue professionals to work at the top of their abilities and offer patients the streamlined digital experiences they increasingly expect. Most importantly, providers will have more of the financial resources they need to focus on their true expertise, delivering patient care and improving outcomes.

About Noel A. Felipe, CRCR
With over 38 years of experience in healthcare accounts receivable management, Noel has a proven track record of developing progressive client-based solutions and building strong cross-functional teams to implement those solutions and maximize client results. At Firstsource Noel maintains direct account management responsibility for strategic clients and leads the development team for Firstsource’s digital collection and digital pre-service collection platforms.  Noel attended Miami Dade College, is a member of the American Association of Health Administration Management (AAHAM); has served two terms as president of the Florida Chapter of HFMA and was appointed to HFMA’s National Advisory Council for Revenue Cycle.

Typically, hearing the terms “Automation or AI” elicits one of two responses– an immediate sense of apprehension and avoidance, or a complete overestimation of its capabilities, though in some cases those two responses go hand in hand. However, neither view is particularly helpful as one is trying to understand the tremendous power of this capability and employ it in appropriate places within their business. 

The truth is, automation and AI are here and they’re here to stay. Though there are new capabilities and tools in both areas, those tools are really the outgrowth of a technology-focused transition that exists across almost all industries. Businesses that choose not to understand and adopt new technologies will be left behind. Still, others who rely too heavily upon it without proper planning and understanding may put their businesses at risk. Automation, including AI-enhanced automation, is certainly not a magic wand. It’s simply a tool, and like anything else, must be utilized strategically. A thorough understanding of the capabilities and limitations of the technology and a strategic utilization of its functionality are what’s needed to ensure success. It’s all about balance. 

Within the healthcare revenue cycle specifically, automation can be a transformative force in enhancing efficiency, reducing errors and cutting costs. However, for healthcare systems looking to employ automation, whether AI-enhanced or more traditional, there are key principles to keep in mind to ensure technologies are being utilized in the best ways and in the most impactable areas to achieve maximum and sustainable results. 

1. Automation within healthcare systems must always be balanced with a patient-centric approach. Over the years, mainly due to cost-cutting measures, many healthcare systems have discontinued or reduced the scope of patient advocacy and engagement programs. With the recent focus and shift to automation capabilities as an additional cost-cutting measure, it will be critical to keep a patient-centric approach at the forefront, maintaining critical patient touches, patient education, and an omnichannel communication strategy while employing automation. 

2. Automation is not a substitute for effective process design and management. In fact, in most cases, automation requires more. Automation will amplify the accuracy of a well-designed process, and similarly, will amplify the flaws of a poorly designed one. To be effective, automation requires a foundation of meticulously designed and managed processes which must be created before any automation is implemented.  

3. Automation without an understanding of underlying processes and the mechanisms of the automation can be a risk to an organization; there should always be a fallback plan. When organizations choose to implement automation without a thorough understanding of the underlying processes and mechanisms, there can be significant risks to the organization. For example, when an automated system encounters an anomaly that it isn’t programmed to handle, the errors that result can have far-reaching negative impacts on the organization’s revenue cycle and bottom line.  It’s critical that organizations have not only a thorough understanding of the technology doing the automation but also of the systems and processes being automated and the potential errors and anomalies that could arise. A fallback plan should be implemented to handle these issues, including gaps and or lapses in the execution of the automation themselves, to ensure business continuity. 

4. Automation initiatives must consider full costs (design, development, maintenance) as a part of ROI determination. Before undertaking an automation project, all costs must be evaluated. This includes costs of any technology, initial design and development, and regular, ongoing maintenance which will be critical to ongoing success. All these costs must be factored in to determine the true ROI delivered over time. For example, some automation initiatives could require substantial investment in IT infrastructure and ongoing maintenance, so initially, it could appear that labor costs may be reduced, but once the calculations are complete, the anticipated cost savings may not be realized as compared to current processes or alternative approaches. 

5. In prioritizing and evaluating the value of automation initiatives and opportunities, consideration should be given to incremental value and not just cost-cutting opportunities. Yes, automation can reduce labor costs and other operational expenses, but its value extends much further. It also has the potential to enhance accuracy; reducing the rate of billing errors which improves patient safety and trust in addition to any tangible cost savings. It also improves compliance by ensuring that every step of a process is performed consistently, in accordance with regulations. Lastly, it can also speed up processes, enabling the organization to handle higher volumes of work without increasing staffing levels or it can free up human resources from mundane, routine tasks to focus on more critical and strategic objectives. 

Automation, particularly when enhanced with AI, holds great promise and potential for many businesses and specifically within the healthcare revenue cycle. However, to be successful, organizations must make balanced and informed decisions when evaluating these opportunities. With a patient-centric approach, careful process design and management, a deep understanding of the underlying processes and automation mechanisms, a comprehensive view of the costs with a balanced evaluation of the value, automation can truly be a game-changer.  

About John Hataway

John Hataway is the Senior Director of Continuous Improvement and Automation at Savista, a revenue cycle management consulting and staffing company.

Despite assertions that healthcare is “burned out on talking about burnout,” the HIMSS 2023 presentations that have kept attendees talking long after the sessions ended included those that use automation to relieve workforce pressures.

From ways to support smarter, more seamless discharge to remote check-ins with tonsillectomy patients, use cases for automation ramped up considerably during the pandemic. That’s a trend that is poised for takeoff now that ChatGPT is dominating discussions at healthcare trade shows. Each day, new ideas for intelligent automation are surfacing among healthcare teams.

But health systems will struggle to gain value from innovations like ChatGPT and generative artificial intelligence (AI) without a foundation for automation. Such a foundation starts with transforming unstructured data, like digital cloud faxes, into structured data so that insightful information can be extracted to improve clinical decision-making. When repetitive document processes typically require manual intervention to move forward, then you have a great reason to apply robotic process automation (RPA). RPA improves document workflow processes by applying rules-based technology to eliminate repetitive tasks without the need for human interaction.

Making the Right Moves with RPA to Improve Employee Satisfaction

At a time when half of healthcare workers—not just doctors and nurses—suffer from burnout, RPA holds strong potential to ease the burden of one of its biggest causes: tedious tasks, ripe for automation. RPA empowers healthcare professionals to focus on the work that matters most, caring for their patients, by eliminating repetitive and annoying tasks. 

Here are three keys to adopting a value-driven approach to implementing RPA.

1. Make sure you have all the right players at the table for RPA design. One concept discussed throughout the industry is the “moral injury” that occurs when innovation happens to clinicians rather than with their input. Moral injury, says John Mackenzie, clinical program manager and behavioral health specialist for CommonSpirit Health, is a leading cause of burnout. By involving those who will be most affected by RPA in determining use cases and laying out the workflows that make the most sense for automation, health systems can more effectively engage employees in RPA. 

Like most solutions that offer AI and RPA technologies, the use cases are endless. Understanding the problem the technology is supposed to solve helps determine the workflow changes needed and how to effectively measure key process improvements. This further ensures that staff will not try to bypass RPA in their work. It also improves the quality of the output produced. One place to start: Look for tasks that are logical and redundant, require many hours of manual labor, or rely on the availability of file-based data. 

2. Select an RPA solution that works across platforms and systems.
When it comes to gaining the most value from RPA, selecting a vendor-agnostic solution expands the potential for RPA use cases across even the largest, most complex organizations. At Surgery Partners, which comprises 172 hospitals and surgery centers in 32 states, a dozen hospitals operated different versions of the same EHR platform. Leaders sought an RPA solution that could not only integrate with these EHRs but also with other technology systems across the organization’s care network. Once a solution was chosen, team members then developed workflows that could be reused across the same platforms and applied to other systems with slight adjustments. Then, they scheduled the automation to run regularly—with minimal human intervention—at specific times (e.g., specific days of the month) or when pre-specified triggers set the process in motion. The impact: Surgery Partners saves more than $150,000 per year in eliminating repetitive and error-prone manual data entry across functions while freeing employees to focus on more challenging and satisfying work.

3. Consider return on investment (ROI) from the start. One of the biggest barriers to demonstrating health tech value occurs when leaders fail to determine how they will measure ROI. Without a plan for assessing the value of the investment, it becomes nearly impossible to share the technology’s value in terms of its impact on the organization, its employees and patients. Four common metrics used to track ROI for RPA include time and money saved, reliability of the data produced, ease of usability for staff, and improvements in efficiency (e.g., Did RPA help reduce the number of full-time employees in a particular department? Did it decrease man hours for a specific function, like prior authorization?) In a recent article, McKinsey estimated that AI could automate 50% to 75% of manual tasks. At St. Claire HealthCare in Morehead, Kentucky, the use of cloud-based RPA to speed claim processing and clean up accounts led to a significant increase in accounts billed and payments received. It also resolved delays in over $2 million of billable income and improved productivity throughout the organization. 

Creating a Foundation for Transformation

The new developments we’ve seen around AI, generative AI and automated care in healthcare since the start of the year are thrilling—but they also demand a solid foundation for innovation matched to a specific problem to deliver the desired ROI. By taking the time to establish the right foundation for AI innovation via intelligent data extraction and RPA, health systems can achieve the desired impact more quickly while reducing work frustration and enabling staff to focus on what they do best. 

About John Nebergall

John Nebergall is the COO at Consensus Cloud Solutions,  the world’s largest digital fax provider and a trusted global source for the transformation, enhancement and secure exchange of digital information. . John oversees the commercial operations of Consensus including sales, marketing, ecommerce and customer care. Prior to joining Consensus, he led the J2 Cloud Fax business and architected it’s transformation into an enterprise-grade supplier of interoperability solutions for healthcare.

With over 20 years of executive experience in healthcare and cloud computing at companies including Orion Health, Allscripts and Zynx Health, John brings a deep knowledge of electronic health records and health information exchange technology to Consensus. Prior to entering the healthcare IT industry, he worked as Senior Vice President at Experian, overseeing the North American credit reporting business

Axuall’s CEO & Founder, Charlie Lougheed shares why health administration teams should embrace the power of robotic process automation (RPA).

Built with leading healthcare systems, Axuall is a workforce intelligence company powered by a national real-time practitioner data network. The technology enables healthcare systems, staffing firms, telehealth, and health plans to dramatically reduce onboarding and enrollment time while also providing unique, powerful data insights for network planning, analytics, and reporting. The company’s CEO and founder, ​​Charlie Lougheed, believes that the smarter use of analytics is a core factor in giving health systems the opportunity to build better networks, all while empowering healthcare administration teams with better, more complete, and more timely data — that also complies with industry standards and aligns with existing workflows. 

HITC: To start, why should health administration teams embrace the power of robotic process automation (RPA)?

Lougheed: Robot Processing Automation (RPA) can sound like a threatening term for health administration teams, but in reality, this technology should be looked at as their friend, rather than their enemy. To put it simply, these bots are like border collies because they do the job of constantly herding information (not sheep, of course). 

There was a time when shepherds used to herd sheep themselves, but then along came the sheepdogs, and the process got a lot more efficient. The only shepherds that lost their job were the ones that didn’t take advantage of this new “technology,”  it has nothing to do with “giving up control.” 

HITC: So, it sounds like bots aren’t replacing humans, but rather enhancing their productivity. How can RPA and other healthcare automation tools ensure health administrators can meet the current challenges? 

Lougheed: Exactly. Healthcare administrators should view RPA as a tool to enable – not replace – humans. While this automation isn’t a new concept, its potential to help alleviate some of the biggest trends and challenges facing our country’s healthcare system today has become much more prevalent (e.g., the widening gap between supply and demand, a rapidly growing clinician shortage, and the shrinking revenue and budget that follow as a result).

By combining RPA with the provider big data, for instance, the two can eliminate much of the manual intervention that currently holds administrators back from the truly important activity that requires critical thinking. The widespread adoption of this technology could empower MSPs and healthcare executives to collaborate, analyze, plan, and deploy resources where they’re most needed in a way that’s never been possible before – all while automatically meeting credentialing and privileging regulations at the same time.

HITC: How can RPA specifically help health admin teams optimize their employee staffing?

Lougheed: It’s no secret that staffing has emerged as one of the most immediate concerns in healthcare today. In fact, personnel shortages even just replaced financial challenges as the top concern for hospital CEOs for the first time in nearly two decades, according to the American College of Healthcare Executives.

This “new normal” leaves health systems permanently operating in an extremely challenging environment. The key to successfully navigating staffing will be efficiency and flexibility – two things traditionally not within reach for hospitals due to credentialing and privileging regulations. However, RPA is providing health systems with comprehensive, real-time insight into their current and future clinical workforce, allowing administrators to better navigate the increasing challenges of care logistics. Doing so allows big data to be applied across the provider community that can address gaps in workforce supply, distribute precious resources more efficiently, and optimize care networks.

The result will be a future of healthcare that allows administration teams to become data analysts, not just data aggregators.

HITC: What are some best practices for selecting an RPA vendor for health administrators?

Lougheed: There’s no silver bullet solution that will ever be able to make all of our problems immediately disappear – especially in an industry as convoluted as healthcare. However, I would encourage healthcare administrators who are considering partnering with an RPA vendor to seek out those who can offer the following:

– The ability to analyze and plan through comprehensive real-time insight into your current and future clinical workforce.

– Enabling faster onboarding that allows clinicians to speed up the credentialing and privileging process, become enrolled, and ultimately be deployed where they’re needed to meet demand.

– Continuous updates that ensure an always-ready and compliant workforce.

– Cross-credential across collaborative care networks to expand services and revenue.

– Technology that plugs into and leverages existing systems.

Most importantly, any RPA vendor should be able to ensure health systems can optimize their economics by ultimately reducing unnecessary delays, costs, and barriers to revenue capture.

HITC: What are some of the deployment challenges health administrators should be aware of?

Lougheed: A successful deployment relies on top-down support from healthcare leaders. Process change requires aircover and encouragement for those in the trenches. We’ve seen the greatest success in environments where team members are encouraged to make the long-term investments needed to rethink and retain old ways.  

Remember, all old ways were once new ways. Healthy and accountable patience for what it takes to transition is critical to transformation. 

HITC: What would you like our readers to understand about Axuall and the power of analytics? What is the message you hope to spread through this interview?

Lougheed: Automation, when combined with work workforce intelligence, enables leaders to plan their care networks, providing visibility into where resource supply and demand are today and in the future (especially when combined with market data). It streamlines the recruiting process, making it easier for clinicians to apply for positions or privileges.

This doesn’t just improve patient access to care, but it can dramatically improve the bottom line by preventing leakage, reducing burnout, and improving overall financial performance. In fact, a recent study even found that Cleveland-based University Hospitals could generate an additional $74,000 per new physician hire based on a savings of just 16 days. If the health system leveraged Axuall for only a quarter of the newly onboarded physicians annually, administrators could ensure additional revenue capture of between $9.2 million and $13.9 million each year.

The early adopters of big data and analytics, combined with the power of RPA, are set to enjoy a significant advantage over the competition and reap the benefits long into the future.

What You Should Know:

– Element5, the world’s first Automation-as-a-Service solution purpose-built for post-acute care, today announced that it has raised $30 million in a Series B funding round led by Insight Partners.  With the closing of the Series B funding round, Element5 has raised $48.5M in total capital to date.
 

– This investment will strengthen Element5’s position and enable the company to continue the disruption of the health care industry’s $400B post-acute care workflow automation market.

– The investment will also accelerate market penetration in home health, hospice, skilled nursing and senior living facilities.

Workflow Automation-as-a-Service, Powered by AI & RPA

Founded in 2019, Element5 uses artificial intelligence (AI)-powered robotic process automation (RPA) to deliver pre-built workflow automation solutions for post-acute care organizations. Today’s ever-increasing regulatory demands continue to strain and burden teams, forcing them to spend hours manually performing administrative work. Element5’s technology allows post-acute care organizations to automate their processes, eliminating highly repetitive, logic-driven administrative work. This enables  teams to focus on higher-value tasks, improve operational efficiency and combat the ongoing post-acute care staffing crisis.

“We’re overwhelmed with the trust and support provided by Insight Partners, who share our common vision, which is to eliminate the need to perform manual, repetitive work for post-acute care,” said Joe Randesi, Co-founder and CEO, Element5. “The post-acute care industry demands improvements in operational efficiency and a means to overcome chronic staffing shortages. Over the last two years, we have witnessed significant growth in the adoption of our automation technology and the next phase of our growth journey is focused on enabling more health organizations to embrace and operationalize the power of automation to reduce administrative costs and enhance patient outcomes.”

The United States spends about $1 trillion per year on healthcare administration. 95% of healthcare workforce growth since 1990 has been administrative. But adding administrative staff hasn’t helped health systems stay on top of the increase in manual work queues, and it certainly hasn’t been improving outcomes for patients. So when asked if automation can drive better health system outcomes, through my work in healthcare technology, I know for a fact that it already is. 

Research has shown automation’s power to eliminate inefficiencies and reduce waste. The 2021 CAQH Index estimated that the medical industry has already saved $166 billion through automation, and further automation could save an additional 48% of the total money spent on administrative transactions. Greater efficiency yields better financial outcomes as well as a better patient experience. 

Automation Reduces Human Error

As a whole, medical errors cost $20 billion per year. If we examine billing alone, about 80% of medical bills contain an error. Human staff can easily let their attention slip while performing high volumes of repetitive tasks, or details might be captured incorrectly as information transfers from one administrator to another. 

The key here is not just automation, but combining it with intelligence that ensures that the correct data is accurately entered into the appropriate systems. For example, having a patient take a photo of their insurance card, which is then uploaded into a website, and is processed automatically by AI is inherently less error-prone than typing in a number.

This approach also enhances the reliability and consistency of data. The presence of accurate data is key in driving improvements. Software can easily examine claims that were bounced back and compare them to claims that went through, to develop a strategy to reduce denials. Over time, I’ve seen eligibility and registration denials reduced by 83% using this iterative method. 

Automation Increases Overall Productivity

The SelectUSA report, “Robots and the Economy”, estimates that automation could raise productivity by 0.8%, boosting the output of each worker. The same report posits that 45% of work activities could be automated. In particular, there is high potential to automate the collecting and processing of data. Most employees don’t like doing the kinds of repetitive tasks that automation excels at, and one Salesforce survey found that 89% of employees are more satisfied with their jobs after using automation. It gives them time back for skilled work; and in healthcare, this means staff can spend more time with patients. 

Done well, automation has the potential not only to enable staff to get more done, but also to be happier in their roles and less likely to churn. The average cost of turnover across all healthcare positions is around $60,000, and since 2015, the average hospital has turned over 89% of its workforce. Retaining staff is increasingly important in the current labor market, and has a dramatic impact on health system finances. 

Getting creative about reimagining the way healthcare is delivered could yield further savings. With sophisticated enough tools, such as automated outreach to patients and self-serve scheduling, fewer and fewer phone calls are necessary to complete the registration process. Imagine the savings from being able to do away with the call center entirely. 

Automation Means A Better Patient Experience

Today, health systems are well aware that patients expect a digital experience, and are willing to shop around to find it. Patients want to be able to engage with their health systems digitally, at their own convenience, whenever they have the time and would prefer that their providers be proactive in communicating with them. While health systems want to prioritize these goals, many organizations find they have not made as much progress as they would like. 

Currently, much of the onus of remembering care tasks rests with the patient, largely because staff didn’t have the bandwidth to be more proactive. Automation opens up the possibility of proactive outreach, something most health systems struggle to do well because of resource constraints. When health systems reach out to patients to close their care gaps, they can connect with three times the number of patients they would normally see. This drives improved patient outcomes, as it helps patients stay on top of their preventative screenings and prompts them to book any necessary follow-up appointments with their specialists. Patients appreciate the help with staying on top of their care needs.

Automation Is The Future

Not only can automation drive business outcomes for health systems, but it will also be crucial to remaining competitive over the next few years. The old approach of throwing more staff at problems is going to become increasingly outdated and ineffective as patients and staff demand a better experience, and disruptors enter the healthcare market. The question is no longer whether automation can drive better outcomes – we have an abundance of evidence that it already has – the question is which health systems are going to adapt as the market changes. Will yours?

About Pranay Kapadia

Pranay Kapadia is Co-founder and CEO at Notable. After years of hearing his family of physicians object to the state of technology in healthcare, Pranay founded Notable to enrich every patient-provider interaction and eliminate manual burdens for staff and providers. 

Pranay has focused his career on tackling problems at the synapse of data, finance and user experience — defining and building products that simplify ease of use while reducing financial paperwork within highly regulated industries. Prior to Notable, Pranay and his co-founding team worked to revolutionize how millions of people file for mortgages. As Vice President of Product Management at Blend, a technology company reconstructing the mortgage and lending industry, Pranay worked with customers like Wells Fargo, US Bank, and Fannie Mae to bring simplicity and transparency to consumer banking. He also held multiple roles at Intuit, leading Mint.com, Quicken and QuickBooks.

What You Should Know:

– Notable, a San Mateo, CA-based leader in healthcare intelligent automation, today announced it has raised $100M in Series B funding led by ICONIQ Growth, including participation by Greylock, F-Prime Capital, and Oak HC/FT to accelerate growth and innovation within the healthcare industry. 

– The company plans to use the new round of funding to pioneer a novel intelligent automation approach for healthcare with the mission of reducing administrative burden and improving the patient experience – all in one platform.

– Healthcare delivery involves repetitive, manual workflows that account for over $1 trillion in administrative costs per year and compromise the quality of care. Leading health systems, including Intermountain Healthcare and CommonSpirit Health, use Notable’s platform to automate 100s of workflows across patient engagement, population health, and revenue cycle management. With Notable, staff and clinicians report saving 700+ hours of administrative work per provider per year; increased patient visit volume; reduced claim denials and improves patient outcomes while eliminating staff burden.

Intelligent Automation as-a-Service for Healthcare

Notable’s platform leverages AI to continually scan providers’ electronic health record systems (EHRs) and other applications, identifying automated workflows to perform. Common examples include collecting patients’ pre-visit registration information, submitting a prior authorization request, or reaching out to patients who are overdue for care. The platform leverages digital assistants to perform these workflows by clicking into fields, updating records, and uploading documents.

With a unified digital patient experience, Notable empowers providers to automate patient interactions from scheduling and registration to post-visit follow-up and payment collection. Patients are automatically notified when their provider needs information and can provide everything required through an intuitive digital interface. This eliminates the need for staff to support these workflows with manual phone calls, legacy paper forms, and repetitive data entry.

“Healthcare faces a staffing crisis, and overwhelming administrative burden challenges providers’ ability to deliver high-quality, affordable care and world-class patient experiences,” said Pranay Kapadia, co-founder and CEO of Notable. “This investment accelerates the execution of our vision to digitally transform and enrich patient-provider interactions with intelligent automation.”

In recent years, the healthcare industry has fully embraced the potential for artificial intelligence (AI) to transform healthcare practice and delivery. From the advent of big data to the arrival of EHRs, the industry is familiar with the hype that accompanies technology advancements. While these innovations have certainly been useful in many regards, healthcare remains deeply fragmented, inefficient, and prone to waste. 

Many experts believe that AI will deliver on the long-promised transformation of healthcare by providing the connective tissue that ties our other technology advancements together. The industry will finally be able to merge data from multiple sources to provide valuable insights at the point of care. Workflow advances and time-saving automation will help decrease the administrative burden for both providers and payers, while new consumer uses for AI-enabled healthcare will more effectively engage patients in their own care.

In fact, researchers estimate that AI applications could potentially reduce annual U.S. healthcare costs by $150 billion as early as 2026, due in large part to a systemic shift from a reactive to a proactive approach to medicine.¹ 

AI Within Case and Utilization Management 

With the availability and abundance of data comes the opportunity to transform case and utilization management to be more efficient and proactive. However, the human brain can’t possibly process and synthesize all the data in a timely manner, leaving most data underleveraged. This is where AI comes into play.

Predictive AI, an increasingly popular form, identifies patterns and trends within data to provide clinical predictions. Robotic process automation (RPA), another form of AI, is widely used to replace time-intensive manual tasks, such as the completion of medical reviews. When a significant portion of their administrative burden is lifted, case managers are free to spend time with patients who require additional focus.

But when it comes to patient care, can we rely solely on an algorithm to know what’s really best for the patient? Can any form of AI be intelligent enough to potentially “understand” the nuances and complexities of patients and the healthcare system? And when it comes to defending the care that was delivered, can providers simply claim that they followed what the AI told them to do?  

Technology as a Navigation Aid 

Of course, AI does not—and was never intended to—replace evidence-based medicine and clinical judgment. In my work with InterQual^®, I see AI as a tool that complements clinical evidence and expertise. 

When people share their reservations about the place of AI in clinical practice, I like to use the analogy of navigation. Hundreds of years ago, we relied on the stars and a compass to navigate; fifty years ago, we used a giant Rand McNally road map. Now, we have multiple GPS applications which not only give us directions but also inform us about traffic jams and suggest alternate routes. However, at the end of the day, we are literally in the driver’s seat: we make the decisions. We can choose to take a slower route, as we want to make a stop along the way. 

Clearly, the existence of technology does not necessitate our utter dependence upon it. Innovations like machine learning, natural language processing, and predictive analytics are simply tools that enhance our ability to make better, more informed decisions. They give clinicians insight into the bigger picture so that they can make the most optimal decision.

By the same token, the existence of AI does not relieve us from the responsibility of making informed decisions. Any program that relies exclusively on AI to drive patient decisions—by relying on an algorithm alone to automate patient classification—is neither transparent nor trustworthy. 

Pairing AI With Clinical Expertise, Evidence, and Care Management

Evidence-based medicine is the foundation of patient care. All of the uses for AI—from automating medical necessity reviews or providing advanced clinical insights—rest upon or complement that foundation. For patient care decisions to be clinically defensible, AI must be used in conjunction with evidence-based criteria, and the results evaluated by trained professionals using expert clinical judgment. 

In decision support systems, it is vital that AI, clinical expertise, and evidence-based criteria should work together. For example, before the decision to admit is made, predictive AI can provide the probability that a patient belongs in an inpatient or observation bed, which helps case managers prioritize patients. Once a patient is admitted, AI provides key insights into the length of stay and discharge destination, helping case managers adjust care accordingly.

The most effective and efficient decision support systems also leverage robotic process automation to map structured and unstructured clinical data from the EHR to codified, evidence-based criteria to automatically populate a  medical review. Automated reviews not only reduce the administrative burden, but they are also transparent and trusted by payers, as they contain embedded clinical data for each criteria point. 

In these instances, AI functions as a workflow efficiency tool, helping case managers to prioritize their workload, support appropriate care, and begin transition planning well in advance. However, even the best AI and RPA technologies do not help the case manager with what to do to help the patient progress along the optimal path; they cannot provide care guidance when there are delays, complications, or additional episode complexity. That’s where evidence-based guidance comes to play: during the stay.

State-of-the-art evidence-based guidance provides admission considerations that account for social determinants of health and includes the expected clinical progress for that condition, along with what to do if the patient isn’t progressing. It drives the key actionable components for facilitation to the next level of care. As delays in care can lead to serious financial implications for the hospital, evidence-based guidance is essential for helping case managers get care back on track. 

While AI is useful for increasing workflow efficiency and providing predictive insights, case managers need relevant evidence to support and defend their decision-making process. Evidence-based guidance can advise case managers on how to best coordinate care so that discharge planning and follow-up care are arranged appropriately to prevent readmissions. 

Making Clinically Defensible Decisions

As patients are complex, case managers cannot depend on AI alone to progress care. Its predictions can never be completely clear-cut. And AI’s inherent lack of transparency also makes defending a care decision based on AI alone a very poor choice. 

Medical necessity is about documenting why a patient requires a certain approach to care so that this approach can be supported downstream when dealing with payment and audit processes. Once care is provided and the claim submitted for payment, payers look for the clinical evidence that supports the claim of medical necessity. 

Providers that rely on AI alone might answer this request by sending payers a simple score based on an AI algorithm, along with bits and pieces of clinical data that are potentially (but not necessarily) relevant to the decision to admit. This approach is not helpful in appealing a denial or defending against a RAC audit, as there is no complete information about how the AI algorithm derived its score. 

To ensure the medical review is defensible, providers must align patient-specific data with evidence-based criteria to support medical necessity. That requires giving payers full visibility into the process of clinical decision-making, including date and time stamps for findings plus record locations for each data point. They can easily see the connection between the patient’s clinical condition and the evidence-based criteria used to justify the care delivered. 

Empowering Clinicians 

Ultimately, the goal of responsible AI is not to supplant the clinician’s expertise or eliminate the need for clinical evidence. The goal is to empower clinicians by giving them as many relevant data points as possible to help them make better decisions—and to provide that information as quickly as possible, as decisions are being made. 

AI-enabled clinical decision support must be built on a foundation of evidence-based medicine in order to truly be of use. When paired with evidence-based criteria and clinical judgment, AI can support proactive, efficient, defensible care management to help care teams reduce denials, deliver appropriate care, and ultimately improve the patient experience. 

About Laura Coughlin

Laura Coughlin is vice president of Clinical Innovation and Development at Change Healthcare, leading clinical content strategy and product innovation across the InterQual suite.  She is a registered nurse and has served in leadership roles at Healthsource, New England Deaconess, and Olsten Kimberly Quality Care.

References

¹Adam Bohr and Kaveh Memarszadeh, “The Rise of Artificial Intelligence in Healthcare Applications,” Artificial Intelligence in Healthcare, June 26, 2020. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7325854/

– AKASA™, an automation company for healthcare revenue cycle management,  released a report titled, “New Productivity Benchmarks For The Healthcare Revenue Cycle” that includes the first-ever publication of the average time it takes health system staff to complete critical tasks within revenue cycle operations based on AKASA’s proprietary data.

– These revenue cycle management benchmarks are some of the first for the revenue cycle industry and accurately forecast how to measure productivity for tasks within focus areas, like financial clearance, billing, and denials. 

How AKASA Is Helping Create Benchmarks

AKASA works with provider organizations of all sizes (with operations in all 50 states) to automate revenue cycle functions. AKASA’s models and algorithms have been trained on nearly 250 million claims and remittances. AKASA’s proprietary software provides valuable insights for health systems into where their staff spends their time and what baseline costs are involved. AKASA’s “New Productivity Benchmarks For The Healthcare Revenue Cycle” is based on its proprietary data and informed by the expertise and experience of its team.

The RCM benchmarks outlined in the report include:

“It’s challenging for healthcare revenue cycle leaders to access accurate benchmarks in terms of actual staff productivity,” said Amy Raymond, head of revenue cycle operations at AKASA. “You often can’t pull productivity metrics on someone working eligibility, for example, because it often gets mixed in with other tasks within financial clearance that are being completed at the same time. With AKASA’s new report, leaders can fill in the information gaps and identify a reasonable number of claims or tasks to be worked daily. These benchmarks will also help managers set goals and forecast their staffing and resource needs.”

Healthcare organizations are investing in automation solutions for time-consuming, repetitive, and laborious tasks that are necessary but are often a less strategic use of staff time and talent. This can help organizations improve retention in revenue cycle positions, known for high rates of turnover.

Nearly 84% of healthcare revenue cycle teams say they use productivity standards or quotas to meet goals, according to a recent AKASA survey of healthcare financial leaders. Of those who indicated using productivity measures, nearly 70% report scaling these across all focus areas within the revenue cycle, including claims management, insurance follow-up, coding, denials management, and financial clearance.

Report Background/Methodology

Commissioned by AKASA, the survey fielded responses from nearly 400 chief financial officers and revenue cycle leaders at hospitals and health systems across the United States through the Healthcare Financial Management Association’s (HFMA) Pulse Survey program between May 27, 2021 and June 28, 2021. The national survey was designed to assess the adoption of automation in revenue cycle operations at hospitals and health systems across the U.S.

What You Should Know:

Half of the healthcare administrative staff report seeing an increase in the amount of manual data entry in the past 12 months — and 92% of clinicians agree that too much time spent on administrative tasks is a major contributor to healthcare worker burnout. This and other findings are revealed in the new Internet of Healthcare Report, produced by independent research firm Wakefield Research on behalf of Olive. The report uncovers how 1,700 patients, healthcare professionals, administrative staff and executives view the healthcare patient and employee experience.

– The key findings of the report signals that these processes are in need of updating, not just to alleviate worker overload, but to deliver for patients. 91% of healthcare professionals agree that fixing the burden of time-intensive, manual administrative processes is the most important thing they can do to improve the quality of patient care.

Healthcare Must Adopt Automation to Keep Pace With Demands

The healthcare industry is among one of the top industries grappling with “The Great Resignation,” exacerbated by workers who are in desperate need of support both due to the pandemic and to ballooning administrative loads. At the same time, 93% of healthcare professionals believe applying automation to remedy these processes will be good for their careers. 78% of administrative staff agree, with nearly half (49%) of C-level healthcare executives fearing that employee turnover will be the most likely consequence of their organization not automating in the next one to two years.

“The healthcare industry deserves the automation that so many other industries have already experienced to empower it to function at its best, ultimately creating a new health experience for humans. For far too long healthcare workers have completed the same mundane administrative tasks over and over, and patients have shared the same information time and time again,” said Jeremy Friese, President, Payer Market at Olive. “The Internet of Healthcare Report reveals that across the healthcare industry, workers and patients — rather than running from change — want to run towards it to improve their jobs, the patient experience and ultimately, their health. This is the only industry to still largely rely on fax machines. The need for change is painfully obvious.”

Other key findings of the report include:

– Patients are done with filling out forms: Patients are having to constantly repeat the same information (55%), be the one to inform healthcare professionals of medications other physicians have prescribed (40%) and deal with delays in treatment due to insurance review processes (51%). And, this lack of integrated healthcare systems is taking a toll on patients’ health: 57% agree that having their medical history easily accessible to any healthcare provider they see would do the most to improve their health outcomes.

– Manual processes lead to errors: Due to disjointed systems, administrative staff suspect an average of 21% of patient records have at least one error, including 48% who suspect 20% or more of their records contain at least one error, if not multiple errors.

– The lack of intelligence is impacting patient care: Misdiagnosis can be a patient’s worst nightmare, delaying the care they need, or worse — AI’s chance to prevent this outcome is perhaps its greatest attribute. Many clinicians (40%) predict AI will decrease the risk of incorrect patient diagnosis. On top of this, healthcare executives think their staff could get over 90 minutes back a day to spend with patients through automation.

– Healthcare will leapfrog other industries in innovation: While healthcare has historically lagged in innovation, it will soon lead. Nearly 8 in 10 healthcare executives believe the industry will emerge as a leader. Virtually all healthcare professionals (98%) predict AI-led advancements to be widespread throughout U.S. healthcare by 2026. While executives are optimistic, patients remain skeptical, with only 25% believing healthcare will become a leader in innovation. However, executives predict that AI-led advancements will include fully automated data entry (58%), patient access to medical records from anywhere (56%) and virtual visits/remote monitoring (52%) becoming the norm.

Report Background/Methodology

The survey was conducted by Wakefield Research online between July 2 and July 14, 2021, and included 200 Healthcare Provider/Payer C-Level Executives; 250 Healthcare Professionals, with qualifying roles of physicians, specialists, registered nurses (RNs), nurse practitioners (NPs) and physician assistants (PAs); 250 Non-Clinical Administrative Staff who are working in patient care environments such as hospitals, clinics, and medical practices; and a nationally-representative audience of 1,000 U.S. adults aged 18+.

The adoption of chatbots and virtual assistants, coupled with the integration of artificial intelligence and machine learning technology, has revolutionized the healthcare industry. In many ways, chatbots have become ubiquitous, providing a more optimized user experience through digital means.

The healthcare industry has already benefited immensely from this technology, namely through greater access to valuable services and information, more accuracy in determining what care patients require, and reduced costs for patients and providers alike. Below, I take a deeper look into these benefits.

Improved Access to Quality Care and Information

For many patients, actually visiting a physician or specialist can be challenging; the commute often takes a considerable amount of time, which is difficult for working individuals and those without reliable transportation, and in some cases, patients may feel that their concerns are not worth the hassle of a trip. Chatbots can provide a simple solution to these issues by reducing unnecessary transportation and associated costs and providing insight into patient concerns to determine whether an in-person consultation is essential.

Similarly, the adoption of chatbots in healthcare, especially in areas like skilled nursing facilities where there tend to be problems with staff shortages, can reduce the strain on limited resources, allowing skilled professionals to dedicate more of their time and energy to cases that demand the full use of their expertise.

By providing individuals who have questions or concerns about their health with immediate access to medical insight and guidance, chatbots can help efficiently clerk and triage patients through preliminary, automated queries and notation which doctors can then easily access and reference.

Additionally, some chatbots have proven effective in the healthcare industry by operating in an informational or conversational fashion. Users can easily query chatbots for more information about symptoms, conditions, complications, and treatments, allowing them to have increased access to vital information that might otherwise be difficult to locate or understand. While the internet at large offers an expansive amount of data, factual and verified information may not always be present, and chatbots can facilitate the dissemination of approved information to users, reducing the risk of harmful misinformation.

The use of natural language processing (NLP) and natural language understanding (NLU) can enable chatbots to effectively engage with users, granting them appropriate answers and insight to better educate their healthcare decisions.

More Accurate Connections to Suitable Care Providers

Improving efficiency and accuracy of healthcare recommendations and relevant information to patient queries has been a top priority in this digital age, and the use of chatbots has already helped users make more informed decisions so that they can acquire better care.

Chatbots like Grace have improved healthcare recommendation accuracy through queries and interactions. By informing a chatbot of their symptoms, users can receive appropriate recommendations for next steps in seconds, expediting the process. In some cases, chatbots can assist with the next steps by helping users schedule appointments, providing insights into expected costs and copays, transferring user medical records to the desired facility, and more.

The use of chatbots has become increasingly popular, especially for patients looking to receive immediate attention and answers. Chatbots can be effective for users seeking same- or next-day appointments with healthcare providers by collecting important information, conveying this data to practitioners, and assisting in scheduling matters to ensure users are connected with the appropriate facilities.

A More Humanized, Patient-Oriented Approach

One of the most promising and productive advantages of chatbots in healthcare relates to their potential for human engagement, personalization, and efficiency. Early iterations of AI and chatbots were certainly limited in their capacity for human interaction, but through machine learning, NLP, and NLU, chatbots are now more capable of processing users’ messages and responding in organic, practical, and helpful ways.

One example of this is Woebot, a chatbot that uses cognitive-behavioral therapy (CBT) to help users who are suffering from emotional distress or mental health issues like depression or anxiety. Woebot can help users cope with their symptoms through guided exercises and prompts for self-reflection. Many users find that communicating with a chatbot in this way is easier than speaking to a real person, and the technology available allows chatbots to be engaging, effective, and useful.

Other companies like QliqSOFT have developed technology that allows the creation of “digital humans.” In essence, these AI-driven chatbots are able to empathetically communicate with patients, document important data, and convey information to patients and healthcare professionals alike. These abilities facilitate a more efficient, effective, patient-oriented approach to healthcare without detracting from existing practices or standards.

Chatbots cannot (and should not) replace humans, but they can be used alongside human care to improve the patient experience, provide personalized answers and insights, and encourage an individualized approach to patient care.

As healthcare technology continues to advance, the implementation of chatbots in the industry, especially in specialized institutions like skilled nursing facilities, is both inevitable and promising. By providing healthcare professionals and patients with opportunities to collect important user data, share vital information, spread verified facts, and provide expert guidance outside of a traditional medical setting, chatbots will certainly continue to be an asset in the industry. Capitalizing on this trend and investing in the future of chatbots will be a wise choice for healthcare professionals moving forward.

About Bent Philipson

Bent Philipson is the founder of Philosophy Care, a consulting firm providing a range of services to skilled nursing facilities throughout New York and New Jersey dedicated to providing each resident with individualized care. Philipson is recognized as a leading expert in nursing home care, advancements in rehabilitation technology, and changes in the healthcare landscape.

Olive Launches In-House Venture Studio for Digital Health Startups

What You Should Know: 

– Olive, the $4B healthcare automation company, today announced Olive Ventures, a new in-house venture studio that works hand-in-hand with early-stage entrepreneurs to create digital health companies through Olive’s platform. 

– Olive Ventures offers visionaries a secure, compliant tech environment (i.e. Olive’s tech stack) that’s designed to rapidly validate, deploy, distribute and commercialize digital health innovations and specialized products for the healthcare industry.

2 Companies Built by Olive Ventures

Two companies already built by Olive Ventures include Violet, a new kind of bank aimed at giving patients peace of mind against large medical bills and Rotera, an AI consulting and custom development company for health systems, payers and healthcare vendors. Rotera was the first company created in the Olive Ventures Studio and is currently helping thousands of healthcare workers nationwide. 

“We’re bridging the ‘valley of death’ in the healthcare startup landscape,” said Sean Lane, CEO of Olive. “I’ve seen far too many great ideas be shot down without ever completing a pilot project. We’re charting a new path for digital health innovators by killing the traditional pilot and rewriting the entire process to be better, smarter and faster.”

What You Should Know:

– 78 percent of health systems are currently using or are in the process of implementing automation in their revenue cycle operations, according to recent survey results from AKASA, a South San Francisco-based revenue cycle management automation company. The key findings signal automation in healthcare is no longer an emerging trend but is mission-critical for driving efficiency and cost-effectiveness in revenue cycle operations.   

– According to the survey, health systems (versus hospitals) are statistically more likely to be currently using or implementing automation tools in their revenue cycle operations. Survey results also show that as the size of the organization increases so does their use of automation tools with the largest healthcare providers, those with $1B – $10B net patient revenues, most actively using or implementing these tools.

COVID-19 Impact on Revenue Cycle

COVID-19 has placed many healthcare organizations under intense cash-flow pressure and created volatile claim volumes and workloads for revenue cycle teams. These dynamics are driving more revenue cycle leaders to look to automation to provide flexibility and resiliency in their operations while minimizing their organization’s cost to collect. The survey also found that 37% of organizations currently not using automation plan to do so this year or sometime in 2022.

Increase Focus of Digital Transformation in Healthcare

Commissioned by AKASA, the survey fielded responses from nearly 400 chief financial officers and revenue cycle leaders at hospitals and health systems across the United States through the Healthcare Financial Management Association’s (HFMA) Pulse Survey program between May 27, 2021 and June 28, 2021.

Results demonstrate that the increasing focus on digital transformation efforts in healthcare has driven the adoption of automation to help manage claims, billing and reimbursement processes. The majority of health systems and hospitals, (more than 66 percent) say they are now using or implementing  automation in their revenue cycle operations.

“The findings underscore that automation serves as a backbone for healthcare financial leaders looking to streamline complex staff workflows,” said Malinka Walaliyadde, co-founder and CEO of AKASA. “The opportunity going forward for provider organizations is to expand their ambitions and scope for automation. Instead of identifying dozens of small, discrete use-cases and never getting past the first few due to high setup and maintenance costs, leaders should consider solutions that can be deployed rapidly with minimal disruption. The goal is foundational, end-to-end automation for entire functions, driving giant leaps in efficiency.” 

What You Should Know:

– Olive, the AI healthcare company, announced today the adoption of Amazon Web Services, Inc. (AWS) as its preferred cloud provider, now leveraging AWS’s computing capabilities to improve healthcare efficiency and reduce costs for patients and organizations.

– Olive’s workflow automation solution will run on AWS to connect the disparate systems used by healthcare organizations to help automate and optimize administrative tasks for healthcare providers, freeing them to spend more time with patients in more than 950 hospitals across the U.S.

– Olive will further support the industry by working with AWS and its community of builders and developers with AWS + Olive Helps. By combining the AWS developer community with Olive Helps, healthcare’s AI coworker, Olive will continue to transform healthcare by closing the gap between work and wisdom for healthcare workers by providing real-time, task-specific information.

What You Should Know:

– Kareo, a provider of cloud-based clinical and business management software solutions for independent healthcare practices and billing companies, today announced the acquisition of PatientlySpeaking, a process automation technology company for billing companies and medical practices.

– Together with Kareo’s intuitive billing platform, PatientlySpeaking provides an integrated data connection for billing companies and medical practices to automate redundant daily tasks with the power of robotic process automation (RPA) bots. With those tasks out of the way, billers are free to focus on managing their business and being a valued resource for their practices.